Predictive Maintenance Modelling Guide Python Notebook.html

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}
.glyphicon-triangle-bottom:before {
  content: "\e252";
}
.glyphicon-triangle-top:before {
  content: "\e253";
}
.glyphicon-console:before {
  content: "\e254";
}
.glyphicon-superscript:before {
  content: "\e255";
}
.glyphicon-subscript:before {
  content: "\e256";
}
.glyphicon-menu-left:before {
  content: "\e257";
}
.glyphicon-menu-right:before {
  content: "\e258";
}
.glyphicon-menu-down:before {
  content: "\e259";
}
.glyphicon-menu-up:before {
  content: "\e260";
}
* {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
*:before,
*:after {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
html {
  font-size: 10px;
  -webkit-tap-highlight-color: rgba(0, 0, 0, 0);
}
body {
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-size: 13px;
  line-height: 1.42857143;
  color: #000;
  background-color: #fff;
}
input,
button,
select,
textarea {
  font-family: inherit;
  font-size: inherit;
  line-height: inherit;
}
a {
  color: #337ab7;
  text-decoration: none;
}
a:hover,
a:focus {
  color: #23527c;
  text-decoration: underline;
}
a:focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
figure {
  margin: 0;
}
img {
  vertical-align: middle;
}
.img-responsive,
.thumbnail > img,
.thumbnail a > img,
.carousel-inner > .item > img,
.carousel-inner > .item > a > img {
  display: block;
  max-width: 100%;
  height: auto;
}
.img-rounded {
  border-radius: 3px;
}
.img-thumbnail {
  padding: 4px;
  line-height: 1.42857143;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 2px;
  -webkit-transition: all 0.2s ease-in-out;
  -o-transition: all 0.2s ease-in-out;
  transition: all 0.2s ease-in-out;
  display: inline-block;
  max-width: 100%;
  height: auto;
}
.img-circle {
  border-radius: 50%;
}
hr {
  margin-top: 18px;
  margin-bottom: 18px;
  border: 0;
  border-top: 1px solid #eeeeee;
}
.sr-only {
  position: absolute;
  width: 1px;
  height: 1px;
  margin: -1px;
  padding: 0;
  overflow: hidden;
  clip: rect(0, 0, 0, 0);
  border: 0;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
[role="button"] {
  cursor: pointer;
}
h1,
h2,
h3,
h4,
h5,
h6,
.h1,
.h2,
.h3,
.h4,
.h5,
.h6 {
  font-family: inherit;
  font-weight: 500;
  line-height: 1.1;
  color: inherit;
}
h1 small,
h2 small,
h3 small,
h4 small,
h5 small,
h6 small,
.h1 small,
.h2 small,
.h3 small,
.h4 small,
.h5 small,
.h6 small,
h1 .small,
h2 .small,
h3 .small,
h4 .small,
h5 .small,
h6 .small,
.h1 .small,
.h2 .small,
.h3 .small,
.h4 .small,
.h5 .small,
.h6 .small {
  font-weight: normal;
  line-height: 1;
  color: #777777;
}
h1,
.h1,
h2,
.h2,
h3,
.h3 {
  margin-top: 18px;
  margin-bottom: 9px;
}
h1 small,
.h1 small,
h2 small,
.h2 small,
h3 small,
.h3 small,
h1 .small,
.h1 .small,
h2 .small,
.h2 .small,
h3 .small,
.h3 .small {
  font-size: 65%;
}
h4,
.h4,
h5,
.h5,
h6,
.h6 {
  margin-top: 9px;
  margin-bottom: 9px;
}
h4 small,
.h4 small,
h5 small,
.h5 small,
h6 small,
.h6 small,
h4 .small,
.h4 .small,
h5 .small,
.h5 .small,
h6 .small,
.h6 .small {
  font-size: 75%;
}
h1,
.h1 {
  font-size: 33px;
}
h2,
.h2 {
  font-size: 27px;
}
h3,
.h3 {
  font-size: 23px;
}
h4,
.h4 {
  font-size: 17px;
}
h5,
.h5 {
  font-size: 13px;
}
h6,
.h6 {
  font-size: 12px;
}
p {
  margin: 0 0 9px;
}
.lead {
  margin-bottom: 18px;
  font-size: 14px;
  font-weight: 300;
  line-height: 1.4;
}
@media (min-width: 768px) {
  .lead {
    font-size: 19.5px;
  }
}
small,
.small {
  font-size: 92%;
}
mark,
.mark {
  background-color: #fcf8e3;
  padding: .2em;
}
.text-left {
  text-align: left;
}
.text-right {
  text-align: right;
}
.text-center {
  text-align: center;
}
.text-justify {
  text-align: justify;
}
.text-nowrap {
  white-space: nowrap;
}
.text-lowercase {
  text-transform: lowercase;
}
.text-uppercase {
  text-transform: uppercase;
}
.text-capitalize {
  text-transform: capitalize;
}
.text-muted {
  color: #777777;
}
.text-primary {
  color: #337ab7;
}
a.text-primary:hover,
a.text-primary:focus {
  color: #286090;
}
.text-success {
  color: #3c763d;
}
a.text-success:hover,
a.text-success:focus {
  color: #2b542c;
}
.text-info {
  color: #31708f;
}
a.text-info:hover,
a.text-info:focus {
  color: #245269;
}
.text-warning {
  color: #8a6d3b;
}
a.text-warning:hover,
a.text-warning:focus {
  color: #66512c;
}
.text-danger {
  color: #a94442;
}
a.text-danger:hover,
a.text-danger:focus {
  color: #843534;
}
.bg-primary {
  color: #fff;
  background-color: #337ab7;
}
a.bg-primary:hover,
a.bg-primary:focus {
  background-color: #286090;
}
.bg-success {
  background-color: #dff0d8;
}
a.bg-success:hover,
a.bg-success:focus {
  background-color: #c1e2b3;
}
.bg-info {
  background-color: #d9edf7;
}
a.bg-info:hover,
a.bg-info:focus {
  background-color: #afd9ee;
}
.bg-warning {
  background-color: #fcf8e3;
}
a.bg-warning:hover,
a.bg-warning:focus {
  background-color: #f7ecb5;
}
.bg-danger {
  background-color: #f2dede;
}
a.bg-danger:hover,
a.bg-danger:focus {
  background-color: #e4b9b9;
}
.page-header {
  padding-bottom: 8px;
  margin: 36px 0 18px;
  border-bottom: 1px solid #eeeeee;
}
ul,
ol {
  margin-top: 0;
  margin-bottom: 9px;
}
ul ul,
ol ul,
ul ol,
ol ol {
  margin-bottom: 0;
}
.list-unstyled {
  padding-left: 0;
  list-style: none;
}
.list-inline {
  padding-left: 0;
  list-style: none;
  margin-left: -5px;
}
.list-inline > li {
  display: inline-block;
  padding-left: 5px;
  padding-right: 5px;
}
dl {
  margin-top: 0;
  margin-bottom: 18px;
}
dt,
dd {
  line-height: 1.42857143;
}
dt {
  font-weight: bold;
}
dd {
  margin-left: 0;
}
@media (min-width: 541px) {
  .dl-horizontal dt {
    float: left;
    width: 160px;
    clear: left;
    text-align: right;
    overflow: hidden;
    text-overflow: ellipsis;
    white-space: nowrap;
  }
  .dl-horizontal dd {
    margin-left: 180px;
  }
}
abbr[title],
abbr[data-original-title] {
  cursor: help;
  border-bottom: 1px dotted #777777;
}
.initialism {
  font-size: 90%;
  text-transform: uppercase;
}
blockquote {
  padding: 9px 18px;
  margin: 0 0 18px;
  font-size: inherit;
  border-left: 5px solid #eeeeee;
}
blockquote p:last-child,
blockquote ul:last-child,
blockquote ol:last-child {
  margin-bottom: 0;
}
blockquote footer,
blockquote small,
blockquote .small {
  display: block;
  font-size: 80%;
  line-height: 1.42857143;
  color: #777777;
}
blockquote footer:before,
blockquote small:before,
blockquote .small:before {
  content: '\2014 \00A0';
}
.blockquote-reverse,
blockquote.pull-right {
  padding-right: 15px;
  padding-left: 0;
  border-right: 5px solid #eeeeee;
  border-left: 0;
  text-align: right;
}
.blockquote-reverse footer:before,
blockquote.pull-right footer:before,
.blockquote-reverse small:before,
blockquote.pull-right small:before,
.blockquote-reverse .small:before,
blockquote.pull-right .small:before {
  content: '';
}
.blockquote-reverse footer:after,
blockquote.pull-right footer:after,
.blockquote-reverse small:after,
blockquote.pull-right small:after,
.blockquote-reverse .small:after,
blockquote.pull-right .small:after {
  content: '\00A0 \2014';
}
address {
  margin-bottom: 18px;
  font-style: normal;
  line-height: 1.42857143;
}
code,
kbd,
pre,
samp {
  font-family: monospace;
}
code {
  padding: 2px 4px;
  font-size: 90%;
  color: #c7254e;
  background-color: #f9f2f4;
  border-radius: 2px;
}
kbd {
  padding: 2px 4px;
  font-size: 90%;
  color: #888;
  background-color: transparent;
  border-radius: 1px;
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.25);
}
kbd kbd {
  padding: 0;
  font-size: 100%;
  font-weight: bold;
  box-shadow: none;
}
pre {
  display: block;
  padding: 8.5px;
  margin: 0 0 9px;
  font-size: 12px;
  line-height: 1.42857143;
  word-break: break-all;
  word-wrap: break-word;
  color: #333333;
  background-color: #f5f5f5;
  border: 1px solid #ccc;
  border-radius: 2px;
}
pre code {
  padding: 0;
  font-size: inherit;
  color: inherit;
  white-space: pre-wrap;
  background-color: transparent;
  border-radius: 0;
}
.pre-scrollable {
  max-height: 340px;
  overflow-y: scroll;
}
.container {
  margin-right: auto;
  margin-left: auto;
  padding-left: 0px;
  padding-right: 0px;
}
@media (min-width: 768px) {
  .container {
    width: 768px;
  }
}
@media (min-width: 992px) {
  .container {
    width: 940px;
  }
}
@media (min-width: 1200px) {
  .container {
    width: 1140px;
  }
}
.container-fluid {
  margin-right: auto;
  margin-left: auto;
  padding-left: 0px;
  padding-right: 0px;
}
.row {
  margin-left: 0px;
  margin-right: 0px;
}
.col-xs-1, .col-sm-1, .col-md-1, .col-lg-1, .col-xs-2, .col-sm-2, .col-md-2, .col-lg-2, .col-xs-3, .col-sm-3, .col-md-3, .col-lg-3, .col-xs-4, .col-sm-4, .col-md-4, .col-lg-4, .col-xs-5, .col-sm-5, .col-md-5, .col-lg-5, .col-xs-6, .col-sm-6, .col-md-6, .col-lg-6, .col-xs-7, .col-sm-7, .col-md-7, .col-lg-7, .col-xs-8, .col-sm-8, .col-md-8, .col-lg-8, .col-xs-9, .col-sm-9, .col-md-9, .col-lg-9, .col-xs-10, .col-sm-10, .col-md-10, .col-lg-10, .col-xs-11, .col-sm-11, .col-md-11, .col-lg-11, .col-xs-12, .col-sm-12, .col-md-12, .col-lg-12 {
  position: relative;
  min-height: 1px;
  padding-left: 0px;
  padding-right: 0px;
}
.col-xs-1, .col-xs-2, .col-xs-3, .col-xs-4, .col-xs-5, .col-xs-6, .col-xs-7, .col-xs-8, .col-xs-9, .col-xs-10, .col-xs-11, .col-xs-12 {
  float: left;
}
.col-xs-12 {
  width: 100%;
}
.col-xs-11 {
  width: 91.66666667%;
}
.col-xs-10 {
  width: 83.33333333%;
}
.col-xs-9 {
  width: 75%;
}
.col-xs-8 {
  width: 66.66666667%;
}
.col-xs-7 {
  width: 58.33333333%;
}
.col-xs-6 {
  width: 50%;
}
.col-xs-5 {
  width: 41.66666667%;
}
.col-xs-4 {
  width: 33.33333333%;
}
.col-xs-3 {
  width: 25%;
}
.col-xs-2 {
  width: 16.66666667%;
}
.col-xs-1 {
  width: 8.33333333%;
}
.col-xs-pull-12 {
  right: 100%;
}
.col-xs-pull-11 {
  right: 91.66666667%;
}
.col-xs-pull-10 {
  right: 83.33333333%;
}
.col-xs-pull-9 {
  right: 75%;
}
.col-xs-pull-8 {
  right: 66.66666667%;
}
.col-xs-pull-7 {
  right: 58.33333333%;
}
.col-xs-pull-6 {
  right: 50%;
}
.col-xs-pull-5 {
  right: 41.66666667%;
}
.col-xs-pull-4 {
  right: 33.33333333%;
}
.col-xs-pull-3 {
  right: 25%;
}
.col-xs-pull-2 {
  right: 16.66666667%;
}
.col-xs-pull-1 {
  right: 8.33333333%;
}
.col-xs-pull-0 {
  right: auto;
}
.col-xs-push-12 {
  left: 100%;
}
.col-xs-push-11 {
  left: 91.66666667%;
}
.col-xs-push-10 {
  left: 83.33333333%;
}
.col-xs-push-9 {
  left: 75%;
}
.col-xs-push-8 {
  left: 66.66666667%;
}
.col-xs-push-7 {
  left: 58.33333333%;
}
.col-xs-push-6 {
  left: 50%;
}
.col-xs-push-5 {
  left: 41.66666667%;
}
.col-xs-push-4 {
  left: 33.33333333%;
}
.col-xs-push-3 {
  left: 25%;
}
.col-xs-push-2 {
  left: 16.66666667%;
}
.col-xs-push-1 {
  left: 8.33333333%;
}
.col-xs-push-0 {
  left: auto;
}
.col-xs-offset-12 {
  margin-left: 100%;
}
.col-xs-offset-11 {
  margin-left: 91.66666667%;
}
.col-xs-offset-10 {
  margin-left: 83.33333333%;
}
.col-xs-offset-9 {
  margin-left: 75%;
}
.col-xs-offset-8 {
  margin-left: 66.66666667%;
}
.col-xs-offset-7 {
  margin-left: 58.33333333%;
}
.col-xs-offset-6 {
  margin-left: 50%;
}
.col-xs-offset-5 {
  margin-left: 41.66666667%;
}
.col-xs-offset-4 {
  margin-left: 33.33333333%;
}
.col-xs-offset-3 {
  margin-left: 25%;
}
.col-xs-offset-2 {
  margin-left: 16.66666667%;
}
.col-xs-offset-1 {
  margin-left: 8.33333333%;
}
.col-xs-offset-0 {
  margin-left: 0%;
}
@media (min-width: 768px) {
  .col-sm-1, .col-sm-2, .col-sm-3, .col-sm-4, .col-sm-5, .col-sm-6, .col-sm-7, .col-sm-8, .col-sm-9, .col-sm-10, .col-sm-11, .col-sm-12 {
    float: left;
  }
  .col-sm-12 {
    width: 100%;
  }
  .col-sm-11 {
    width: 91.66666667%;
  }
  .col-sm-10 {
    width: 83.33333333%;
  }
  .col-sm-9 {
    width: 75%;
  }
  .col-sm-8 {
    width: 66.66666667%;
  }
  .col-sm-7 {
    width: 58.33333333%;
  }
  .col-sm-6 {
    width: 50%;
  }
  .col-sm-5 {
    width: 41.66666667%;
  }
  .col-sm-4 {
    width: 33.33333333%;
  }
  .col-sm-3 {
    width: 25%;
  }
  .col-sm-2 {
    width: 16.66666667%;
  }
  .col-sm-1 {
    width: 8.33333333%;
  }
  .col-sm-pull-12 {
    right: 100%;
  }
  .col-sm-pull-11 {
    right: 91.66666667%;
  }
  .col-sm-pull-10 {
    right: 83.33333333%;
  }
  .col-sm-pull-9 {
    right: 75%;
  }
  .col-sm-pull-8 {
    right: 66.66666667%;
  }
  .col-sm-pull-7 {
    right: 58.33333333%;
  }
  .col-sm-pull-6 {
    right: 50%;
  }
  .col-sm-pull-5 {
    right: 41.66666667%;
  }
  .col-sm-pull-4 {
    right: 33.33333333%;
  }
  .col-sm-pull-3 {
    right: 25%;
  }
  .col-sm-pull-2 {
    right: 16.66666667%;
  }
  .col-sm-pull-1 {
    right: 8.33333333%;
  }
  .col-sm-pull-0 {
    right: auto;
  }
  .col-sm-push-12 {
    left: 100%;
  }
  .col-sm-push-11 {
    left: 91.66666667%;
  }
  .col-sm-push-10 {
    left: 83.33333333%;
  }
  .col-sm-push-9 {
    left: 75%;
  }
  .col-sm-push-8 {
    left: 66.66666667%;
  }
  .col-sm-push-7 {
    left: 58.33333333%;
  }
  .col-sm-push-6 {
    left: 50%;
  }
  .col-sm-push-5 {
    left: 41.66666667%;
  }
  .col-sm-push-4 {
    left: 33.33333333%;
  }
  .col-sm-push-3 {
    left: 25%;
  }
  .col-sm-push-2 {
    left: 16.66666667%;
  }
  .col-sm-push-1 {
    left: 8.33333333%;
  }
  .col-sm-push-0 {
    left: auto;
  }
  .col-sm-offset-12 {
    margin-left: 100%;
  }
  .col-sm-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-sm-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-sm-offset-9 {
    margin-left: 75%;
  }
  .col-sm-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-sm-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-sm-offset-6 {
    margin-left: 50%;
  }
  .col-sm-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-sm-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-sm-offset-3 {
    margin-left: 25%;
  }
  .col-sm-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-sm-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-sm-offset-0 {
    margin-left: 0%;
  }
}
@media (min-width: 992px) {
  .col-md-1, .col-md-2, .col-md-3, .col-md-4, .col-md-5, .col-md-6, .col-md-7, .col-md-8, .col-md-9, .col-md-10, .col-md-11, .col-md-12 {
    float: left;
  }
  .col-md-12 {
    width: 100%;
  }
  .col-md-11 {
    width: 91.66666667%;
  }
  .col-md-10 {
    width: 83.33333333%;
  }
  .col-md-9 {
    width: 75%;
  }
  .col-md-8 {
    width: 66.66666667%;
  }
  .col-md-7 {
    width: 58.33333333%;
  }
  .col-md-6 {
    width: 50%;
  }
  .col-md-5 {
    width: 41.66666667%;
  }
  .col-md-4 {
    width: 33.33333333%;
  }
  .col-md-3 {
    width: 25%;
  }
  .col-md-2 {
    width: 16.66666667%;
  }
  .col-md-1 {
    width: 8.33333333%;
  }
  .col-md-pull-12 {
    right: 100%;
  }
  .col-md-pull-11 {
    right: 91.66666667%;
  }
  .col-md-pull-10 {
    right: 83.33333333%;
  }
  .col-md-pull-9 {
    right: 75%;
  }
  .col-md-pull-8 {
    right: 66.66666667%;
  }
  .col-md-pull-7 {
    right: 58.33333333%;
  }
  .col-md-pull-6 {
    right: 50%;
  }
  .col-md-pull-5 {
    right: 41.66666667%;
  }
  .col-md-pull-4 {
    right: 33.33333333%;
  }
  .col-md-pull-3 {
    right: 25%;
  }
  .col-md-pull-2 {
    right: 16.66666667%;
  }
  .col-md-pull-1 {
    right: 8.33333333%;
  }
  .col-md-pull-0 {
    right: auto;
  }
  .col-md-push-12 {
    left: 100%;
  }
  .col-md-push-11 {
    left: 91.66666667%;
  }
  .col-md-push-10 {
    left: 83.33333333%;
  }
  .col-md-push-9 {
    left: 75%;
  }
  .col-md-push-8 {
    left: 66.66666667%;
  }
  .col-md-push-7 {
    left: 58.33333333%;
  }
  .col-md-push-6 {
    left: 50%;
  }
  .col-md-push-5 {
    left: 41.66666667%;
  }
  .col-md-push-4 {
    left: 33.33333333%;
  }
  .col-md-push-3 {
    left: 25%;
  }
  .col-md-push-2 {
    left: 16.66666667%;
  }
  .col-md-push-1 {
    left: 8.33333333%;
  }
  .col-md-push-0 {
    left: auto;
  }
  .col-md-offset-12 {
    margin-left: 100%;
  }
  .col-md-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-md-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-md-offset-9 {
    margin-left: 75%;
  }
  .col-md-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-md-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-md-offset-6 {
    margin-left: 50%;
  }
  .col-md-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-md-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-md-offset-3 {
    margin-left: 25%;
  }
  .col-md-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-md-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-md-offset-0 {
    margin-left: 0%;
  }
}
@media (min-width: 1200px) {
  .col-lg-1, .col-lg-2, .col-lg-3, .col-lg-4, .col-lg-5, .col-lg-6, .col-lg-7, .col-lg-8, .col-lg-9, .col-lg-10, .col-lg-11, .col-lg-12 {
    float: left;
  }
  .col-lg-12 {
    width: 100%;
  }
  .col-lg-11 {
    width: 91.66666667%;
  }
  .col-lg-10 {
    width: 83.33333333%;
  }
  .col-lg-9 {
    width: 75%;
  }
  .col-lg-8 {
    width: 66.66666667%;
  }
  .col-lg-7 {
    width: 58.33333333%;
  }
  .col-lg-6 {
    width: 50%;
  }
  .col-lg-5 {
    width: 41.66666667%;
  }
  .col-lg-4 {
    width: 33.33333333%;
  }
  .col-lg-3 {
    width: 25%;
  }
  .col-lg-2 {
    width: 16.66666667%;
  }
  .col-lg-1 {
    width: 8.33333333%;
  }
  .col-lg-pull-12 {
    right: 100%;
  }
  .col-lg-pull-11 {
    right: 91.66666667%;
  }
  .col-lg-pull-10 {
    right: 83.33333333%;
  }
  .col-lg-pull-9 {
    right: 75%;
  }
  .col-lg-pull-8 {
    right: 66.66666667%;
  }
  .col-lg-pull-7 {
    right: 58.33333333%;
  }
  .col-lg-pull-6 {
    right: 50%;
  }
  .col-lg-pull-5 {
    right: 41.66666667%;
  }
  .col-lg-pull-4 {
    right: 33.33333333%;
  }
  .col-lg-pull-3 {
    right: 25%;
  }
  .col-lg-pull-2 {
    right: 16.66666667%;
  }
  .col-lg-pull-1 {
    right: 8.33333333%;
  }
  .col-lg-pull-0 {
    right: auto;
  }
  .col-lg-push-12 {
    left: 100%;
  }
  .col-lg-push-11 {
    left: 91.66666667%;
  }
  .col-lg-push-10 {
    left: 83.33333333%;
  }
  .col-lg-push-9 {
    left: 75%;
  }
  .col-lg-push-8 {
    left: 66.66666667%;
  }
  .col-lg-push-7 {
    left: 58.33333333%;
  }
  .col-lg-push-6 {
    left: 50%;
  }
  .col-lg-push-5 {
    left: 41.66666667%;
  }
  .col-lg-push-4 {
    left: 33.33333333%;
  }
  .col-lg-push-3 {
    left: 25%;
  }
  .col-lg-push-2 {
    left: 16.66666667%;
  }
  .col-lg-push-1 {
    left: 8.33333333%;
  }
  .col-lg-push-0 {
    left: auto;
  }
  .col-lg-offset-12 {
    margin-left: 100%;
  }
  .col-lg-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-lg-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-lg-offset-9 {
    margin-left: 75%;
  }
  .col-lg-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-lg-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-lg-offset-6 {
    margin-left: 50%;
  }
  .col-lg-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-lg-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-lg-offset-3 {
    margin-left: 25%;
  }
  .col-lg-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-lg-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-lg-offset-0 {
    margin-left: 0%;
  }
}
table {
  background-color: transparent;
}
caption {
  padding-top: 8px;
  padding-bottom: 8px;
  color: #777777;
  text-align: left;
}
th {
  text-align: left;
}
.table {
  width: 100%;
  max-width: 100%;
  margin-bottom: 18px;
}
.table > thead > tr > th,
.table > tbody > tr > th,
.table > tfoot > tr > th,
.table > thead > tr > td,
.table > tbody > tr > td,
.table > tfoot > tr > td {
  padding: 8px;
  line-height: 1.42857143;
  vertical-align: top;
  border-top: 1px solid #ddd;
}
.table > thead > tr > th {
  vertical-align: bottom;
  border-bottom: 2px solid #ddd;
}
.table > caption + thead > tr:first-child > th,
.table > colgroup + thead > tr:first-child > th,
.table > thead:first-child > tr:first-child > th,
.table > caption + thead > tr:first-child > td,
.table > colgroup + thead > tr:first-child > td,
.table > thead:first-child > tr:first-child > td {
  border-top: 0;
}
.table > tbody + tbody {
  border-top: 2px solid #ddd;
}
.table .table {
  background-color: #fff;
}
.table-condensed > thead > tr > th,
.table-condensed > tbody > tr > th,
.table-condensed > tfoot > tr > th,
.table-condensed > thead > tr > td,
.table-condensed > tbody > tr > td,
.table-condensed > tfoot > tr > td {
  padding: 5px;
}
.table-bordered {
  border: 1px solid #ddd;
}
.table-bordered > thead > tr > th,
.table-bordered > tbody > tr > th,
.table-bordered > tfoot > tr > th,
.table-bordered > thead > tr > td,
.table-bordered > tbody > tr > td,
.table-bordered > tfoot > tr > td {
  border: 1px solid #ddd;
}
.table-bordered > thead > tr > th,
.table-bordered > thead > tr > td {
  border-bottom-width: 2px;
}
.table-striped > tbody > tr:nth-of-type(odd) {
  background-color: #f9f9f9;
}
.table-hover > tbody > tr:hover {
  background-color: #f5f5f5;
}
table col[class*="col-"] {
  position: static;
  float: none;
  display: table-column;
}
table td[class*="col-"],
table th[class*="col-"] {
  position: static;
  float: none;
  display: table-cell;
}
.table > thead > tr > td.active,
.table > tbody > tr > td.active,
.table > tfoot > tr > td.active,
.table > thead > tr > th.active,
.table > tbody > tr > th.active,
.table > tfoot > tr > th.active,
.table > thead > tr.active > td,
.table > tbody > tr.active > td,
.table > tfoot > tr.active > td,
.table > thead > tr.active > th,
.table > tbody > tr.active > th,
.table > tfoot > tr.active > th {
  background-color: #f5f5f5;
}
.table-hover > tbody > tr > td.active:hover,
.table-hover > tbody > tr > th.active:hover,
.table-hover > tbody > tr.active:hover > td,
.table-hover > tbody > tr:hover > .active,
.table-hover > tbody > tr.active:hover > th {
  background-color: #e8e8e8;
}
.table > thead > tr > td.success,
.table > tbody > tr > td.success,
.table > tfoot > tr > td.success,
.table > thead > tr > th.success,
.table > tbody > tr > th.success,
.table > tfoot > tr > th.success,
.table > thead > tr.success > td,
.table > tbody > tr.success > td,
.table > tfoot > tr.success > td,
.table > thead > tr.success > th,
.table > tbody > tr.success > th,
.table > tfoot > tr.success > th {
  background-color: #dff0d8;
}
.table-hover > tbody > tr > td.success:hover,
.table-hover > tbody > tr > th.success:hover,
.table-hover > tbody > tr.success:hover > td,
.table-hover > tbody > tr:hover > .success,
.table-hover > tbody > tr.success:hover > th {
  background-color: #d0e9c6;
}
.table > thead > tr > td.info,
.table > tbody > tr > td.info,
.table > tfoot > tr > td.info,
.table > thead > tr > th.info,
.table > tbody > tr > th.info,
.table > tfoot > tr > th.info,
.table > thead > tr.info > td,
.table > tbody > tr.info > td,
.table > tfoot > tr.info > td,
.table > thead > tr.info > th,
.table > tbody > tr.info > th,
.table > tfoot > tr.info > th {
  background-color: #d9edf7;
}
.table-hover > tbody > tr > td.info:hover,
.table-hover > tbody > tr > th.info:hover,
.table-hover > tbody > tr.info:hover > td,
.table-hover > tbody > tr:hover > .info,
.table-hover > tbody > tr.info:hover > th {
  background-color: #c4e3f3;
}
.table > thead > tr > td.warning,
.table > tbody > tr > td.warning,
.table > tfoot > tr > td.warning,
.table > thead > tr > th.warning,
.table > tbody > tr > th.warning,
.table > tfoot > tr > th.warning,
.table > thead > tr.warning > td,
.table > tbody > tr.warning > td,
.table > tfoot > tr.warning > td,
.table > thead > tr.warning > th,
.table > tbody > tr.warning > th,
.table > tfoot > tr.warning > th {
  background-color: #fcf8e3;
}
.table-hover > tbody > tr > td.warning:hover,
.table-hover > tbody > tr > th.warning:hover,
.table-hover > tbody > tr.warning:hover > td,
.table-hover > tbody > tr:hover > .warning,
.table-hover > tbody > tr.warning:hover > th {
  background-color: #faf2cc;
}
.table > thead > tr > td.danger,
.table > tbody > tr > td.danger,
.table > tfoot > tr > td.danger,
.table > thead > tr > th.danger,
.table > tbody > tr > th.danger,
.table > tfoot > tr > th.danger,
.table > thead > tr.danger > td,
.table > tbody > tr.danger > td,
.table > tfoot > tr.danger > td,
.table > thead > tr.danger > th,
.table > tbody > tr.danger > th,
.table > tfoot > tr.danger > th {
  background-color: #f2dede;
}
.table-hover > tbody > tr > td.danger:hover,
.table-hover > tbody > tr > th.danger:hover,
.table-hover > tbody > tr.danger:hover > td,
.table-hover > tbody > tr:hover > .danger,
.table-hover > tbody > tr.danger:hover > th {
  background-color: #ebcccc;
}
.table-responsive {
  overflow-x: auto;
  min-height: 0.01%;
}
@media screen and (max-width: 767px) {
  .table-responsive {
    width: 100%;
    margin-bottom: 13.5px;
    overflow-y: hidden;
    -ms-overflow-style: -ms-autohiding-scrollbar;
    border: 1px solid #ddd;
  }
  .table-responsive > .table {
    margin-bottom: 0;
  }
  .table-responsive > .table > thead > tr > th,
  .table-responsive > .table > tbody > tr > th,
  .table-responsive > .table > tfoot > tr > th,
  .table-responsive > .table > thead > tr > td,
  .table-responsive > .table > tbody > tr > td,
  .table-responsive > .table > tfoot > tr > td {
    white-space: nowrap;
  }
  .table-responsive > .table-bordered {
    border: 0;
  }
  .table-responsive > .table-bordered > thead > tr > th:first-child,
  .table-responsive > .table-bordered > tbody > tr > th:first-child,
  .table-responsive > .table-bordered > tfoot > tr > th:first-child,
  .table-responsive > .table-bordered > thead > tr > td:first-child,
  .table-responsive > .table-bordered > tbody > tr > td:first-child,
  .table-responsive > .table-bordered > tfoot > tr > td:first-child {
    border-left: 0;
  }
  .table-responsive > .table-bordered > thead > tr > th:last-child,
  .table-responsive > .table-bordered > tbody > tr > th:last-child,
  .table-responsive > .table-bordered > tfoot > tr > th:last-child,
  .table-responsive > .table-bordered > thead > tr > td:last-child,
  .table-responsive > .table-bordered > tbody > tr > td:last-child,
  .table-responsive > .table-bordered > tfoot > tr > td:last-child {
    border-right: 0;
  }
  .table-responsive > .table-bordered > tbody > tr:last-child > th,
  .table-responsive > .table-bordered > tfoot > tr:last-child > th,
  .table-responsive > .table-bordered > tbody > tr:last-child > td,
  .table-responsive > .table-bordered > tfoot > tr:last-child > td {
    border-bottom: 0;
  }
}
fieldset {
  padding: 0;
  margin: 0;
  border: 0;
  min-width: 0;
}
legend {
  display: block;
  width: 100%;
  padding: 0;
  margin-bottom: 18px;
  font-size: 19.5px;
  line-height: inherit;
  color: #333333;
  border: 0;
  border-bottom: 1px solid #e5e5e5;
}
label {
  display: inline-block;
  max-width: 100%;
  margin-bottom: 5px;
  font-weight: bold;
}
input[type="search"] {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
input[type="radio"],
input[type="checkbox"] {
  margin: 4px 0 0;
  margin-top: 1px \9;
  line-height: normal;
}
input[type="file"] {
  display: block;
}
input[type="range"] {
  display: block;
  width: 100%;
}
select[multiple],
select[size] {
  height: auto;
}
input[type="file"]:focus,
input[type="radio"]:focus,
input[type="checkbox"]:focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
output {
  display: block;
  padding-top: 7px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
}
.form-control {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
}
.form-control:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.form-control::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.form-control:-ms-input-placeholder {
  color: #999;
}
.form-control::-webkit-input-placeholder {
  color: #999;
}
.form-control::-ms-expand {
  border: 0;
  background-color: transparent;
}
.form-control[disabled],
.form-control[readonly],
fieldset[disabled] .form-control {
  background-color: #eeeeee;
  opacity: 1;
}
.form-control[disabled],
fieldset[disabled] .form-control {
  cursor: not-allowed;
}
textarea.form-control {
  height: auto;
}
input[type="search"] {
  -webkit-appearance: none;
}
@media screen and (-webkit-min-device-pixel-ratio: 0) {
  input[type="date"].form-control,
  input[type="time"].form-control,
  input[type="datetime-local"].form-control,
  input[type="month"].form-control {
    line-height: 32px;
  }
  input[type="date"].input-sm,
  input[type="time"].input-sm,
  input[type="datetime-local"].input-sm,
  input[type="month"].input-sm,
  .input-group-sm input[type="date"],
  .input-group-sm input[type="time"],
  .input-group-sm input[type="datetime-local"],
  .input-group-sm input[type="month"] {
    line-height: 30px;
  }
  input[type="date"].input-lg,
  input[type="time"].input-lg,
  input[type="datetime-local"].input-lg,
  input[type="month"].input-lg,
  .input-group-lg input[type="date"],
  .input-group-lg input[type="time"],
  .input-group-lg input[type="datetime-local"],
  .input-group-lg input[type="month"] {
    line-height: 45px;
  }
}
.form-group {
  margin-bottom: 15px;
}
.radio,
.checkbox {
  position: relative;
  display: block;
  margin-top: 10px;
  margin-bottom: 10px;
}
.radio label,
.checkbox label {
  min-height: 18px;
  padding-left: 20px;
  margin-bottom: 0;
  font-weight: normal;
  cursor: pointer;
}
.radio input[type="radio"],
.radio-inline input[type="radio"],
.checkbox input[type="checkbox"],
.checkbox-inline input[type="checkbox"] {
  position: absolute;
  margin-left: -20px;
  margin-top: 4px \9;
}
.radio + .radio,
.checkbox + .checkbox {
  margin-top: -5px;
}
.radio-inline,
.checkbox-inline {
  position: relative;
  display: inline-block;
  padding-left: 20px;
  margin-bottom: 0;
  vertical-align: middle;
  font-weight: normal;
  cursor: pointer;
}
.radio-inline + .radio-inline,
.checkbox-inline + .checkbox-inline {
  margin-top: 0;
  margin-left: 10px;
}
input[type="radio"][disabled],
input[type="checkbox"][disabled],
input[type="radio"].disabled,
input[type="checkbox"].disabled,
fieldset[disabled] input[type="radio"],
fieldset[disabled] input[type="checkbox"] {
  cursor: not-allowed;
}
.radio-inline.disabled,
.checkbox-inline.disabled,
fieldset[disabled] .radio-inline,
fieldset[disabled] .checkbox-inline {
  cursor: not-allowed;
}
.radio.disabled label,
.checkbox.disabled label,
fieldset[disabled] .radio label,
fieldset[disabled] .checkbox label {
  cursor: not-allowed;
}
.form-control-static {
  padding-top: 7px;
  padding-bottom: 7px;
  margin-bottom: 0;
  min-height: 31px;
}
.form-control-static.input-lg,
.form-control-static.input-sm {
  padding-left: 0;
  padding-right: 0;
}
.input-sm {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
select.input-sm {
  height: 30px;
  line-height: 30px;
}
textarea.input-sm,
select[multiple].input-sm {
  height: auto;
}
.form-group-sm .form-control {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.form-group-sm select.form-control {
  height: 30px;
  line-height: 30px;
}
.form-group-sm textarea.form-control,
.form-group-sm select[multiple].form-control {
  height: auto;
}
.form-group-sm .form-control-static {
  height: 30px;
  min-height: 30px;
  padding: 6px 10px;
  font-size: 12px;
  line-height: 1.5;
}
.input-lg {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
select.input-lg {
  height: 45px;
  line-height: 45px;
}
textarea.input-lg,
select[multiple].input-lg {
  height: auto;
}
.form-group-lg .form-control {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
.form-group-lg select.form-control {
  height: 45px;
  line-height: 45px;
}
.form-group-lg textarea.form-control,
.form-group-lg select[multiple].form-control {
  height: auto;
}
.form-group-lg .form-control-static {
  height: 45px;
  min-height: 35px;
  padding: 11px 16px;
  font-size: 17px;
  line-height: 1.3333333;
}
.has-feedback {
  position: relative;
}
.has-feedback .form-control {
  padding-right: 40px;
}
.form-control-feedback {
  position: absolute;
  top: 0;
  right: 0;
  z-index: 2;
  display: block;
  width: 32px;
  height: 32px;
  line-height: 32px;
  text-align: center;
  pointer-events: none;
}
.input-lg + .form-control-feedback,
.input-group-lg + .form-control-feedback,
.form-group-lg .form-control + .form-control-feedback {
  width: 45px;
  height: 45px;
  line-height: 45px;
}
.input-sm + .form-control-feedback,
.input-group-sm + .form-control-feedback,
.form-group-sm .form-control + .form-control-feedback {
  width: 30px;
  height: 30px;
  line-height: 30px;
}
.has-success .help-block,
.has-success .control-label,
.has-success .radio,
.has-success .checkbox,
.has-success .radio-inline,
.has-success .checkbox-inline,
.has-success.radio label,
.has-success.checkbox label,
.has-success.radio-inline label,
.has-success.checkbox-inline label {
  color: #3c763d;
}
.has-success .form-control {
  border-color: #3c763d;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-success .form-control:focus {
  border-color: #2b542c;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
}
.has-success .input-group-addon {
  color: #3c763d;
  border-color: #3c763d;
  background-color: #dff0d8;
}
.has-success .form-control-feedback {
  color: #3c763d;
}
.has-warning .help-block,
.has-warning .control-label,
.has-warning .radio,
.has-warning .checkbox,
.has-warning .radio-inline,
.has-warning .checkbox-inline,
.has-warning.radio label,
.has-warning.checkbox label,
.has-warning.radio-inline label,
.has-warning.checkbox-inline label {
  color: #8a6d3b;
}
.has-warning .form-control {
  border-color: #8a6d3b;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-warning .form-control:focus {
  border-color: #66512c;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
}
.has-warning .input-group-addon {
  color: #8a6d3b;
  border-color: #8a6d3b;
  background-color: #fcf8e3;
}
.has-warning .form-control-feedback {
  color: #8a6d3b;
}
.has-error .help-block,
.has-error .control-label,
.has-error .radio,
.has-error .checkbox,
.has-error .radio-inline,
.has-error .checkbox-inline,
.has-error.radio label,
.has-error.checkbox label,
.has-error.radio-inline label,
.has-error.checkbox-inline label {
  color: #a94442;
}
.has-error .form-control {
  border-color: #a94442;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-error .form-control:focus {
  border-color: #843534;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
}
.has-error .input-group-addon {
  color: #a94442;
  border-color: #a94442;
  background-color: #f2dede;
}
.has-error .form-control-feedback {
  color: #a94442;
}
.has-feedback label ~ .form-control-feedback {
  top: 23px;
}
.has-feedback label.sr-only ~ .form-control-feedback {
  top: 0;
}
.help-block {
  display: block;
  margin-top: 5px;
  margin-bottom: 10px;
  color: #404040;
}
@media (min-width: 768px) {
  .form-inline .form-group {
    display: inline-block;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .form-control {
    display: inline-block;
    width: auto;
    vertical-align: middle;
  }
  .form-inline .form-control-static {
    display: inline-block;
  }
  .form-inline .input-group {
    display: inline-table;
    vertical-align: middle;
  }
  .form-inline .input-group .input-group-addon,
  .form-inline .input-group .input-group-btn,
  .form-inline .input-group .form-control {
    width: auto;
  }
  .form-inline .input-group > .form-control {
    width: 100%;
  }
  .form-inline .control-label {
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .radio,
  .form-inline .checkbox {
    display: inline-block;
    margin-top: 0;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .radio label,
  .form-inline .checkbox label {
    padding-left: 0;
  }
  .form-inline .radio input[type="radio"],
  .form-inline .checkbox input[type="checkbox"] {
    position: relative;
    margin-left: 0;
  }
  .form-inline .has-feedback .form-control-feedback {
    top: 0;
  }
}
.form-horizontal .radio,
.form-horizontal .checkbox,
.form-horizontal .radio-inline,
.form-horizontal .checkbox-inline {
  margin-top: 0;
  margin-bottom: 0;
  padding-top: 7px;
}
.form-horizontal .radio,
.form-horizontal .checkbox {
  min-height: 25px;
}
.form-horizontal .form-group {
  margin-left: 0px;
  margin-right: 0px;
}
@media (min-width: 768px) {
  .form-horizontal .control-label {
    text-align: right;
    margin-bottom: 0;
    padding-top: 7px;
  }
}
.form-horizontal .has-feedback .form-control-feedback {
  right: 0px;
}
@media (min-width: 768px) {
  .form-horizontal .form-group-lg .control-label {
    padding-top: 11px;
    font-size: 17px;
  }
}
@media (min-width: 768px) {
  .form-horizontal .form-group-sm .control-label {
    padding-top: 6px;
    font-size: 12px;
  }
}
.btn {
  display: inline-block;
  margin-bottom: 0;
  font-weight: normal;
  text-align: center;
  vertical-align: middle;
  touch-action: manipulation;
  cursor: pointer;
  background-image: none;
  border: 1px solid transparent;
  white-space: nowrap;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  border-radius: 2px;
  -webkit-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
}
.btn:focus,
.btn:active:focus,
.btn.active:focus,
.btn.focus,
.btn:active.focus,
.btn.active.focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
.btn:hover,
.btn:focus,
.btn.focus {
  color: #333;
  text-decoration: none;
}
.btn:active,
.btn.active {
  outline: 0;
  background-image: none;
  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
}
.btn.disabled,
.btn[disabled],
fieldset[disabled] .btn {
  cursor: not-allowed;
  opacity: 0.65;
  filter: alpha(opacity=65);
  -webkit-box-shadow: none;
  box-shadow: none;
}
a.btn.disabled,
fieldset[disabled] a.btn {
  pointer-events: none;
}
.btn-default {
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.btn-default:focus,
.btn-default.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.btn-default:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.btn-default:active,
.btn-default.active,
.open > .dropdown-toggle.btn-default {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.btn-default:active:hover,
.btn-default.active:hover,
.open > .dropdown-toggle.btn-default:hover,
.btn-default:active:focus,
.btn-default.active:focus,
.open > .dropdown-toggle.btn-default:focus,
.btn-default:active.focus,
.btn-default.active.focus,
.open > .dropdown-toggle.btn-default.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.btn-default:active,
.btn-default.active,
.open > .dropdown-toggle.btn-default {
  background-image: none;
}
.btn-default.disabled:hover,
.btn-default[disabled]:hover,
fieldset[disabled] .btn-default:hover,
.btn-default.disabled:focus,
.btn-default[disabled]:focus,
fieldset[disabled] .btn-default:focus,
.btn-default.disabled.focus,
.btn-default[disabled].focus,
fieldset[disabled] .btn-default.focus {
  background-color: #fff;
  border-color: #ccc;
}
.btn-default .badge {
  color: #fff;
  background-color: #333;
}
.btn-primary {
  color: #fff;
  background-color: #337ab7;
  border-color: #2e6da4;
}
.btn-primary:focus,
.btn-primary.focus {
  color: #fff;
  background-color: #286090;
  border-color: #122b40;
}
.btn-primary:hover {
  color: #fff;
  background-color: #286090;
  border-color: #204d74;
}
.btn-primary:active,
.btn-primary.active,
.open > .dropdown-toggle.btn-primary {
  color: #fff;
  background-color: #286090;
  border-color: #204d74;
}
.btn-primary:active:hover,
.btn-primary.active:hover,
.open > .dropdown-toggle.btn-primary:hover,
.btn-primary:active:focus,
.btn-primary.active:focus,
.open > .dropdown-toggle.btn-primary:focus,
.btn-primary:active.focus,
.btn-primary.active.focus,
.open > .dropdown-toggle.btn-primary.focus {
  color: #fff;
  background-color: #204d74;
  border-color: #122b40;
}
.btn-primary:active,
.btn-primary.active,
.open > .dropdown-toggle.btn-primary {
  background-image: none;
}
.btn-primary.disabled:hover,
.btn-primary[disabled]:hover,
fieldset[disabled] .btn-primary:hover,
.btn-primary.disabled:focus,
.btn-primary[disabled]:focus,
fieldset[disabled] .btn-primary:focus,
.btn-primary.disabled.focus,
.btn-primary[disabled].focus,
fieldset[disabled] .btn-primary.focus {
  background-color: #337ab7;
  border-color: #2e6da4;
}
.btn-primary .badge {
  color: #337ab7;
  background-color: #fff;
}
.btn-success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.btn-success:focus,
.btn-success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.btn-success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.btn-success:active,
.btn-success.active,
.open > .dropdown-toggle.btn-success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.btn-success:active:hover,
.btn-success.active:hover,
.open > .dropdown-toggle.btn-success:hover,
.btn-success:active:focus,
.btn-success.active:focus,
.open > .dropdown-toggle.btn-success:focus,
.btn-success:active.focus,
.btn-success.active.focus,
.open > .dropdown-toggle.btn-success.focus {
  color: #fff;
  background-color: #398439;
  border-color: #255625;
}
.btn-success:active,
.btn-success.active,
.open > .dropdown-toggle.btn-success {
  background-image: none;
}
.btn-success.disabled:hover,
.btn-success[disabled]:hover,
fieldset[disabled] .btn-success:hover,
.btn-success.disabled:focus,
.btn-success[disabled]:focus,
fieldset[disabled] .btn-success:focus,
.btn-success.disabled.focus,
.btn-success[disabled].focus,
fieldset[disabled] .btn-success.focus {
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.btn-success .badge {
  color: #5cb85c;
  background-color: #fff;
}
.btn-info {
  color: #fff;
  background-color: #5bc0de;
  border-color: #46b8da;
}
.btn-info:focus,
.btn-info.focus {
  color: #fff;
  background-color: #31b0d5;
  border-color: #1b6d85;
}
.btn-info:hover {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.btn-info:active,
.btn-info.active,
.open > .dropdown-toggle.btn-info {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.btn-info:active:hover,
.btn-info.active:hover,
.open > .dropdown-toggle.btn-info:hover,
.btn-info:active:focus,
.btn-info.active:focus,
.open > .dropdown-toggle.btn-info:focus,
.btn-info:active.focus,
.btn-info.active.focus,
.open > .dropdown-toggle.btn-info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
.btn-info:active,
.btn-info.active,
.open > .dropdown-toggle.btn-info {
  background-image: none;
}
.btn-info.disabled:hover,
.btn-info[disabled]:hover,
fieldset[disabled] .btn-info:hover,
.btn-info.disabled:focus,
.btn-info[disabled]:focus,
fieldset[disabled] .btn-info:focus,
.btn-info.disabled.focus,
.btn-info[disabled].focus,
fieldset[disabled] .btn-info.focus {
  background-color: #5bc0de;
  border-color: #46b8da;
}
.btn-info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.btn-warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.btn-warning:focus,
.btn-warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.btn-warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.btn-warning:active,
.btn-warning.active,
.open > .dropdown-toggle.btn-warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.btn-warning:active:hover,
.btn-warning.active:hover,
.open > .dropdown-toggle.btn-warning:hover,
.btn-warning:active:focus,
.btn-warning.active:focus,
.open > .dropdown-toggle.btn-warning:focus,
.btn-warning:active.focus,
.btn-warning.active.focus,
.open > .dropdown-toggle.btn-warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.btn-warning:active,
.btn-warning.active,
.open > .dropdown-toggle.btn-warning {
  background-image: none;
}
.btn-warning.disabled:hover,
.btn-warning[disabled]:hover,
fieldset[disabled] .btn-warning:hover,
.btn-warning.disabled:focus,
.btn-warning[disabled]:focus,
fieldset[disabled] .btn-warning:focus,
.btn-warning.disabled.focus,
.btn-warning[disabled].focus,
fieldset[disabled] .btn-warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.btn-warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.btn-danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
}
.btn-danger:focus,
.btn-danger.focus {
  color: #fff;
  background-color: #c9302c;
  border-color: #761c19;
}
.btn-danger:hover {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.btn-danger:active,
.btn-danger.active,
.open > .dropdown-toggle.btn-danger {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.btn-danger:active:hover,
.btn-danger.active:hover,
.open > .dropdown-toggle.btn-danger:hover,
.btn-danger:active:focus,
.btn-danger.active:focus,
.open > .dropdown-toggle.btn-danger:focus,
.btn-danger:active.focus,
.btn-danger.active.focus,
.open > .dropdown-toggle.btn-danger.focus {
  color: #fff;
  background-color: #ac2925;
  border-color: #761c19;
}
.btn-danger:active,
.btn-danger.active,
.open > .dropdown-toggle.btn-danger {
  background-image: none;
}
.btn-danger.disabled:hover,
.btn-danger[disabled]:hover,
fieldset[disabled] .btn-danger:hover,
.btn-danger.disabled:focus,
.btn-danger[disabled]:focus,
fieldset[disabled] .btn-danger:focus,
.btn-danger.disabled.focus,
.btn-danger[disabled].focus,
fieldset[disabled] .btn-danger.focus {
  background-color: #d9534f;
  border-color: #d43f3a;
}
.btn-danger .badge {
  color: #d9534f;
  background-color: #fff;
}
.btn-link {
  color: #337ab7;
  font-weight: normal;
  border-radius: 0;
}
.btn-link,
.btn-link:active,
.btn-link.active,
.btn-link[disabled],
fieldset[disabled] .btn-link {
  background-color: transparent;
  -webkit-box-shadow: none;
  box-shadow: none;
}
.btn-link,
.btn-link:hover,
.btn-link:focus,
.btn-link:active {
  border-color: transparent;
}
.btn-link:hover,
.btn-link:focus {
  color: #23527c;
  text-decoration: underline;
  background-color: transparent;
}
.btn-link[disabled]:hover,
fieldset[disabled] .btn-link:hover,
.btn-link[disabled]:focus,
fieldset[disabled] .btn-link:focus {
  color: #777777;
  text-decoration: none;
}
.btn-lg,
.btn-group-lg > .btn {
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
.btn-sm,
.btn-group-sm > .btn {
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.btn-xs,
.btn-group-xs > .btn {
  padding: 1px 5px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.btn-block {
  display: block;
  width: 100%;
}
.btn-block + .btn-block {
  margin-top: 5px;
}
input[type="submit"].btn-block,
input[type="reset"].btn-block,
input[type="button"].btn-block {
  width: 100%;
}
.fade {
  opacity: 0;
  -webkit-transition: opacity 0.15s linear;
  -o-transition: opacity 0.15s linear;
  transition: opacity 0.15s linear;
}
.fade.in {
  opacity: 1;
}
.collapse {
  display: none;
}
.collapse.in {
  display: block;
}
tr.collapse.in {
  display: table-row;
}
tbody.collapse.in {
  display: table-row-group;
}
.collapsing {
  position: relative;
  height: 0;
  overflow: hidden;
  -webkit-transition-property: height, visibility;
  transition-property: height, visibility;
  -webkit-transition-duration: 0.35s;
  transition-duration: 0.35s;
  -webkit-transition-timing-function: ease;
  transition-timing-function: ease;
}
.caret {
  display: inline-block;
  width: 0;
  height: 0;
  margin-left: 2px;
  vertical-align: middle;
  border-top: 4px dashed;
  border-top: 4px solid \9;
  border-right: 4px solid transparent;
  border-left: 4px solid transparent;
}
.dropup,
.dropdown {
  position: relative;
}
.dropdown-toggle:focus {
  outline: 0;
}
.dropdown-menu {
  position: absolute;
  top: 100%;
  left: 0;
  z-index: 1000;
  display: none;
  float: left;
  min-width: 160px;
  padding: 5px 0;
  margin: 2px 0 0;
  list-style: none;
  font-size: 13px;
  text-align: left;
  background-color: #fff;
  border: 1px solid #ccc;
  border: 1px solid rgba(0, 0, 0, 0.15);
  border-radius: 2px;
  -webkit-box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
  box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
  background-clip: padding-box;
}
.dropdown-menu.pull-right {
  right: 0;
  left: auto;
}
.dropdown-menu .divider {
  height: 1px;
  margin: 8px 0;
  overflow: hidden;
  background-color: #e5e5e5;
}
.dropdown-menu > li > a {
  display: block;
  padding: 3px 20px;
  clear: both;
  font-weight: normal;
  line-height: 1.42857143;
  color: #333333;
  white-space: nowrap;
}
.dropdown-menu > li > a:hover,
.dropdown-menu > li > a:focus {
  text-decoration: none;
  color: #262626;
  background-color: #f5f5f5;
}
.dropdown-menu > .active > a,
.dropdown-menu > .active > a:hover,
.dropdown-menu > .active > a:focus {
  color: #fff;
  text-decoration: none;
  outline: 0;
  background-color: #337ab7;
}
.dropdown-menu > .disabled > a,
.dropdown-menu > .disabled > a:hover,
.dropdown-menu > .disabled > a:focus {
  color: #777777;
}
.dropdown-menu > .disabled > a:hover,
.dropdown-menu > .disabled > a:focus {
  text-decoration: none;
  background-color: transparent;
  background-image: none;
  filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
  cursor: not-allowed;
}
.open > .dropdown-menu {
  display: block;
}
.open > a {
  outline: 0;
}
.dropdown-menu-right {
  left: auto;
  right: 0;
}
.dropdown-menu-left {
  left: 0;
  right: auto;
}
.dropdown-header {
  display: block;
  padding: 3px 20px;
  font-size: 12px;
  line-height: 1.42857143;
  color: #777777;
  white-space: nowrap;
}
.dropdown-backdrop {
  position: fixed;
  left: 0;
  right: 0;
  bottom: 0;
  top: 0;
  z-index: 990;
}
.pull-right > .dropdown-menu {
  right: 0;
  left: auto;
}
.dropup .caret,
.navbar-fixed-bottom .dropdown .caret {
  border-top: 0;
  border-bottom: 4px dashed;
  border-bottom: 4px solid \9;
  content: "";
}
.dropup .dropdown-menu,
.navbar-fixed-bottom .dropdown .dropdown-menu {
  top: auto;
  bottom: 100%;
  margin-bottom: 2px;
}
@media (min-width: 541px) {
  .navbar-right .dropdown-menu {
    left: auto;
    right: 0;
  }
  .navbar-right .dropdown-menu-left {
    left: 0;
    right: auto;
  }
}
.btn-group,
.btn-group-vertical {
  position: relative;
  display: inline-block;
  vertical-align: middle;
}
.btn-group > .btn,
.btn-group-vertical > .btn {
  position: relative;
  float: left;
}
.btn-group > .btn:hover,
.btn-group-vertical > .btn:hover,
.btn-group > .btn:focus,
.btn-group-vertical > .btn:focus,
.btn-group > .btn:active,
.btn-group-vertical > .btn:active,
.btn-group > .btn.active,
.btn-group-vertical > .btn.active {
  z-index: 2;
}
.btn-group .btn + .btn,
.btn-group .btn + .btn-group,
.btn-group .btn-group + .btn,
.btn-group .btn-group + .btn-group {
  margin-left: -1px;
}
.btn-toolbar {
  margin-left: -5px;
}
.btn-toolbar .btn,
.btn-toolbar .btn-group,
.btn-toolbar .input-group {
  float: left;
}
.btn-toolbar > .btn,
.btn-toolbar > .btn-group,
.btn-toolbar > .input-group {
  margin-left: 5px;
}
.btn-group > .btn:not(:first-child):not(:last-child):not(.dropdown-toggle) {
  border-radius: 0;
}
.btn-group > .btn:first-child {
  margin-left: 0;
}
.btn-group > .btn:first-child:not(:last-child):not(.dropdown-toggle) {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.btn-group > .btn:last-child:not(:first-child),
.btn-group > .dropdown-toggle:not(:first-child) {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.btn-group > .btn-group {
  float: left;
}
.btn-group > .btn-group:not(:first-child):not(:last-child) > .btn {
  border-radius: 0;
}
.btn-group > .btn-group:first-child:not(:last-child) > .btn:last-child,
.btn-group > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.btn-group > .btn-group:last-child:not(:first-child) > .btn:first-child {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.btn-group .dropdown-toggle:active,
.btn-group.open .dropdown-toggle {
  outline: 0;
}
.btn-group > .btn + .dropdown-toggle {
  padding-left: 8px;
  padding-right: 8px;
}
.btn-group > .btn-lg + .dropdown-toggle {
  padding-left: 12px;
  padding-right: 12px;
}
.btn-group.open .dropdown-toggle {
  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
}
.btn-group.open .dropdown-toggle.btn-link {
  -webkit-box-shadow: none;
  box-shadow: none;
}
.btn .caret {
  margin-left: 0;
}
.btn-lg .caret {
  border-width: 5px 5px 0;
  border-bottom-width: 0;
}
.dropup .btn-lg .caret {
  border-width: 0 5px 5px;
}
.btn-group-vertical > .btn,
.btn-group-vertical > .btn-group,
.btn-group-vertical > .btn-group > .btn {
  display: block;
  float: none;
  width: 100%;
  max-width: 100%;
}
.btn-group-vertical > .btn-group > .btn {
  float: none;
}
.btn-group-vertical > .btn + .btn,
.btn-group-vertical > .btn + .btn-group,
.btn-group-vertical > .btn-group + .btn,
.btn-group-vertical > .btn-group + .btn-group {
  margin-top: -1px;
  margin-left: 0;
}
.btn-group-vertical > .btn:not(:first-child):not(:last-child) {
  border-radius: 0;
}
.btn-group-vertical > .btn:first-child:not(:last-child) {
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.btn-group-vertical > .btn:last-child:not(:first-child) {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
  border-bottom-right-radius: 2px;
  border-bottom-left-radius: 2px;
}
.btn-group-vertical > .btn-group:not(:first-child):not(:last-child) > .btn {
  border-radius: 0;
}
.btn-group-vertical > .btn-group:first-child:not(:last-child) > .btn:last-child,
.btn-group-vertical > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.btn-group-vertical > .btn-group:last-child:not(:first-child) > .btn:first-child {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.btn-group-justified {
  display: table;
  width: 100%;
  table-layout: fixed;
  border-collapse: separate;
}
.btn-group-justified > .btn,
.btn-group-justified > .btn-group {
  float: none;
  display: table-cell;
  width: 1%;
}
.btn-group-justified > .btn-group .btn {
  width: 100%;
}
.btn-group-justified > .btn-group .dropdown-menu {
  left: auto;
}
[data-toggle="buttons"] > .btn input[type="radio"],
[data-toggle="buttons"] > .btn-group > .btn input[type="radio"],
[data-toggle="buttons"] > .btn input[type="checkbox"],
[data-toggle="buttons"] > .btn-group > .btn input[type="checkbox"] {
  position: absolute;
  clip: rect(0, 0, 0, 0);
  pointer-events: none;
}
.input-group {
  position: relative;
  display: table;
  border-collapse: separate;
}
.input-group[class*="col-"] {
  float: none;
  padding-left: 0;
  padding-right: 0;
}
.input-group .form-control {
  position: relative;
  z-index: 2;
  float: left;
  width: 100%;
  margin-bottom: 0;
}
.input-group .form-control:focus {
  z-index: 3;
}
.input-group-lg > .form-control,
.input-group-lg > .input-group-addon,
.input-group-lg > .input-group-btn > .btn {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
select.input-group-lg > .form-control,
select.input-group-lg > .input-group-addon,
select.input-group-lg > .input-group-btn > .btn {
  height: 45px;
  line-height: 45px;
}
textarea.input-group-lg > .form-control,
textarea.input-group-lg > .input-group-addon,
textarea.input-group-lg > .input-group-btn > .btn,
select[multiple].input-group-lg > .form-control,
select[multiple].input-group-lg > .input-group-addon,
select[multiple].input-group-lg > .input-group-btn > .btn {
  height: auto;
}
.input-group-sm > .form-control,
.input-group-sm > .input-group-addon,
.input-group-sm > .input-group-btn > .btn {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
select.input-group-sm > .form-control,
select.input-group-sm > .input-group-addon,
select.input-group-sm > .input-group-btn > .btn {
  height: 30px;
  line-height: 30px;
}
textarea.input-group-sm > .form-control,
textarea.input-group-sm > .input-group-addon,
textarea.input-group-sm > .input-group-btn > .btn,
select[multiple].input-group-sm > .form-control,
select[multiple].input-group-sm > .input-group-addon,
select[multiple].input-group-sm > .input-group-btn > .btn {
  height: auto;
}
.input-group-addon,
.input-group-btn,
.input-group .form-control {
  display: table-cell;
}
.input-group-addon:not(:first-child):not(:last-child),
.input-group-btn:not(:first-child):not(:last-child),
.input-group .form-control:not(:first-child):not(:last-child) {
  border-radius: 0;
}
.input-group-addon,
.input-group-btn {
  width: 1%;
  white-space: nowrap;
  vertical-align: middle;
}
.input-group-addon {
  padding: 6px 12px;
  font-size: 13px;
  font-weight: normal;
  line-height: 1;
  color: #555555;
  text-align: center;
  background-color: #eeeeee;
  border: 1px solid #ccc;
  border-radius: 2px;
}
.input-group-addon.input-sm {
  padding: 5px 10px;
  font-size: 12px;
  border-radius: 1px;
}
.input-group-addon.input-lg {
  padding: 10px 16px;
  font-size: 17px;
  border-radius: 3px;
}
.input-group-addon input[type="radio"],
.input-group-addon input[type="checkbox"] {
  margin-top: 0;
}
.input-group .form-control:first-child,
.input-group-addon:first-child,
.input-group-btn:first-child > .btn,
.input-group-btn:first-child > .btn-group > .btn,
.input-group-btn:first-child > .dropdown-toggle,
.input-group-btn:last-child > .btn:not(:last-child):not(.dropdown-toggle),
.input-group-btn:last-child > .btn-group:not(:last-child) > .btn {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.input-group-addon:first-child {
  border-right: 0;
}
.input-group .form-control:last-child,
.input-group-addon:last-child,
.input-group-btn:last-child > .btn,
.input-group-btn:last-child > .btn-group > .btn,
.input-group-btn:last-child > .dropdown-toggle,
.input-group-btn:first-child > .btn:not(:first-child),
.input-group-btn:first-child > .btn-group:not(:first-child) > .btn {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.input-group-addon:last-child {
  border-left: 0;
}
.input-group-btn {
  position: relative;
  font-size: 0;
  white-space: nowrap;
}
.input-group-btn > .btn {
  position: relative;
}
.input-group-btn > .btn + .btn {
  margin-left: -1px;
}
.input-group-btn > .btn:hover,
.input-group-btn > .btn:focus,
.input-group-btn > .btn:active {
  z-index: 2;
}
.input-group-btn:first-child > .btn,
.input-group-btn:first-child > .btn-group {
  margin-right: -1px;
}
.input-group-btn:last-child > .btn,
.input-group-btn:last-child > .btn-group {
  z-index: 2;
  margin-left: -1px;
}
.nav {
  margin-bottom: 0;
  padding-left: 0;
  list-style: none;
}
.nav > li {
  position: relative;
  display: block;
}
.nav > li > a {
  position: relative;
  display: block;
  padding: 10px 15px;
}
.nav > li > a:hover,
.nav > li > a:focus {
  text-decoration: none;
  background-color: #eeeeee;
}
.nav > li.disabled > a {
  color: #777777;
}
.nav > li.disabled > a:hover,
.nav > li.disabled > a:focus {
  color: #777777;
  text-decoration: none;
  background-color: transparent;
  cursor: not-allowed;
}
.nav .open > a,
.nav .open > a:hover,
.nav .open > a:focus {
  background-color: #eeeeee;
  border-color: #337ab7;
}
.nav .nav-divider {
  height: 1px;
  margin: 8px 0;
  overflow: hidden;
  background-color: #e5e5e5;
}
.nav > li > a > img {
  max-width: none;
}
.nav-tabs {
  border-bottom: 1px solid #ddd;
}
.nav-tabs > li {
  float: left;
  margin-bottom: -1px;
}
.nav-tabs > li > a {
  margin-right: 2px;
  line-height: 1.42857143;
  border: 1px solid transparent;
  border-radius: 2px 2px 0 0;
}
.nav-tabs > li > a:hover {
  border-color: #eeeeee #eeeeee #ddd;
}
.nav-tabs > li.active > a,
.nav-tabs > li.active > a:hover,
.nav-tabs > li.active > a:focus {
  color: #555555;
  background-color: #fff;
  border: 1px solid #ddd;
  border-bottom-color: transparent;
  cursor: default;
}
.nav-tabs.nav-justified {
  width: 100%;
  border-bottom: 0;
}
.nav-tabs.nav-justified > li {
  float: none;
}
.nav-tabs.nav-justified > li > a {
  text-align: center;
  margin-bottom: 5px;
}
.nav-tabs.nav-justified > .dropdown .dropdown-menu {
  top: auto;
  left: auto;
}
@media (min-width: 768px) {
  .nav-tabs.nav-justified > li {
    display: table-cell;
    width: 1%;
  }
  .nav-tabs.nav-justified > li > a {
    margin-bottom: 0;
  }
}
.nav-tabs.nav-justified > li > a {
  margin-right: 0;
  border-radius: 2px;
}
.nav-tabs.nav-justified > .active > a,
.nav-tabs.nav-justified > .active > a:hover,
.nav-tabs.nav-justified > .active > a:focus {
  border: 1px solid #ddd;
}
@media (min-width: 768px) {
  .nav-tabs.nav-justified > li > a {
    border-bottom: 1px solid #ddd;
    border-radius: 2px 2px 0 0;
  }
  .nav-tabs.nav-justified > .active > a,
  .nav-tabs.nav-justified > .active > a:hover,
  .nav-tabs.nav-justified > .active > a:focus {
    border-bottom-color: #fff;
  }
}
.nav-pills > li {
  float: left;
}
.nav-pills > li > a {
  border-radius: 2px;
}
.nav-pills > li + li {
  margin-left: 2px;
}
.nav-pills > li.active > a,
.nav-pills > li.active > a:hover,
.nav-pills > li.active > a:focus {
  color: #fff;
  background-color: #337ab7;
}
.nav-stacked > li {
  float: none;
}
.nav-stacked > li + li {
  margin-top: 2px;
  margin-left: 0;
}
.nav-justified {
  width: 100%;
}
.nav-justified > li {
  float: none;
}
.nav-justified > li > a {
  text-align: center;
  margin-bottom: 5px;
}
.nav-justified > .dropdown .dropdown-menu {
  top: auto;
  left: auto;
}
@media (min-width: 768px) {
  .nav-justified > li {
    display: table-cell;
    width: 1%;
  }
  .nav-justified > li > a {
    margin-bottom: 0;
  }
}
.nav-tabs-justified {
  border-bottom: 0;
}
.nav-tabs-justified > li > a {
  margin-right: 0;
  border-radius: 2px;
}
.nav-tabs-justified > .active > a,
.nav-tabs-justified > .active > a:hover,
.nav-tabs-justified > .active > a:focus {
  border: 1px solid #ddd;
}
@media (min-width: 768px) {
  .nav-tabs-justified > li > a {
    border-bottom: 1px solid #ddd;
    border-radius: 2px 2px 0 0;
  }
  .nav-tabs-justified > .active > a,
  .nav-tabs-justified > .active > a:hover,
  .nav-tabs-justified > .active > a:focus {
    border-bottom-color: #fff;
  }
}
.tab-content > .tab-pane {
  display: none;
}
.tab-content > .active {
  display: block;
}
.nav-tabs .dropdown-menu {
  margin-top: -1px;
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.navbar {
  position: relative;
  min-height: 30px;
  margin-bottom: 18px;
  border: 1px solid transparent;
}
@media (min-width: 541px) {
  .navbar {
    border-radius: 2px;
  }
}
@media (min-width: 541px) {
  .navbar-header {
    float: left;
  }
}
.navbar-collapse {
  overflow-x: visible;
  padding-right: 0px;
  padding-left: 0px;
  border-top: 1px solid transparent;
  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1);
  -webkit-overflow-scrolling: touch;
}
.navbar-collapse.in {
  overflow-y: auto;
}
@media (min-width: 541px) {
  .navbar-collapse {
    width: auto;
    border-top: 0;
    box-shadow: none;
  }
  .navbar-collapse.collapse {
    display: block !important;
    height: auto !important;
    padding-bottom: 0;
    overflow: visible !important;
  }
  .navbar-collapse.in {
    overflow-y: visible;
  }
  .navbar-fixed-top .navbar-collapse,
  .navbar-static-top .navbar-collapse,
  .navbar-fixed-bottom .navbar-collapse {
    padding-left: 0;
    padding-right: 0;
  }
}
.navbar-fixed-top .navbar-collapse,
.navbar-fixed-bottom .navbar-collapse {
  max-height: 340px;
}
@media (max-device-width: 540px) and (orientation: landscape) {
  .navbar-fixed-top .navbar-collapse,
  .navbar-fixed-bottom .navbar-collapse {
    max-height: 200px;
  }
}
.container > .navbar-header,
.container-fluid > .navbar-header,
.container > .navbar-collapse,
.container-fluid > .navbar-collapse {
  margin-right: 0px;
  margin-left: 0px;
}
@media (min-width: 541px) {
  .container > .navbar-header,
  .container-fluid > .navbar-header,
  .container > .navbar-collapse,
  .container-fluid > .navbar-collapse {
    margin-right: 0;
    margin-left: 0;
  }
}
.navbar-static-top {
  z-index: 1000;
  border-width: 0 0 1px;
}
@media (min-width: 541px) {
  .navbar-static-top {
    border-radius: 0;
  }
}
.navbar-fixed-top,
.navbar-fixed-bottom {
  position: fixed;
  right: 0;
  left: 0;
  z-index: 1030;
}
@media (min-width: 541px) {
  .navbar-fixed-top,
  .navbar-fixed-bottom {
    border-radius: 0;
  }
}
.navbar-fixed-top {
  top: 0;
  border-width: 0 0 1px;
}
.navbar-fixed-bottom {
  bottom: 0;
  margin-bottom: 0;
  border-width: 1px 0 0;
}
.navbar-brand {
  float: left;
  padding: 6px 0px;
  font-size: 17px;
  line-height: 18px;
  height: 30px;
}
.navbar-brand:hover,
.navbar-brand:focus {
  text-decoration: none;
}
.navbar-brand > img {
  display: block;
}
@media (min-width: 541px) {
  .navbar > .container .navbar-brand,
  .navbar > .container-fluid .navbar-brand {
    margin-left: 0px;
  }
}
.navbar-toggle {
  position: relative;
  float: right;
  margin-right: 0px;
  padding: 9px 10px;
  margin-top: -2px;
  margin-bottom: -2px;
  background-color: transparent;
  background-image: none;
  border: 1px solid transparent;
  border-radius: 2px;
}
.navbar-toggle:focus {
  outline: 0;
}
.navbar-toggle .icon-bar {
  display: block;
  width: 22px;
  height: 2px;
  border-radius: 1px;
}
.navbar-toggle .icon-bar + .icon-bar {
  margin-top: 4px;
}
@media (min-width: 541px) {
  .navbar-toggle {
    display: none;
  }
}
.navbar-nav {
  margin: 3px 0px;
}
.navbar-nav > li > a {
  padding-top: 10px;
  padding-bottom: 10px;
  line-height: 18px;
}
@media (max-width: 540px) {
  .navbar-nav .open .dropdown-menu {
    position: static;
    float: none;
    width: auto;
    margin-top: 0;
    background-color: transparent;
    border: 0;
    box-shadow: none;
  }
  .navbar-nav .open .dropdown-menu > li > a,
  .navbar-nav .open .dropdown-menu .dropdown-header {
    padding: 5px 15px 5px 25px;
  }
  .navbar-nav .open .dropdown-menu > li > a {
    line-height: 18px;
  }
  .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-nav .open .dropdown-menu > li > a:focus {
    background-image: none;
  }
}
@media (min-width: 541px) {
  .navbar-nav {
    float: left;
    margin: 0;
  }
  .navbar-nav > li {
    float: left;
  }
  .navbar-nav > li > a {
    padding-top: 6px;
    padding-bottom: 6px;
  }
}
.navbar-form {
  margin-left: 0px;
  margin-right: 0px;
  padding: 10px 0px;
  border-top: 1px solid transparent;
  border-bottom: 1px solid transparent;
  -webkit-box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
  margin-top: -1px;
  margin-bottom: -1px;
}
@media (min-width: 768px) {
  .navbar-form .form-group {
    display: inline-block;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .form-control {
    display: inline-block;
    width: auto;
    vertical-align: middle;
  }
  .navbar-form .form-control-static {
    display: inline-block;
  }
  .navbar-form .input-group {
    display: inline-table;
    vertical-align: middle;
  }
  .navbar-form .input-group .input-group-addon,
  .navbar-form .input-group .input-group-btn,
  .navbar-form .input-group .form-control {
    width: auto;
  }
  .navbar-form .input-group > .form-control {
    width: 100%;
  }
  .navbar-form .control-label {
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .radio,
  .navbar-form .checkbox {
    display: inline-block;
    margin-top: 0;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .radio label,
  .navbar-form .checkbox label {
    padding-left: 0;
  }
  .navbar-form .radio input[type="radio"],
  .navbar-form .checkbox input[type="checkbox"] {
    position: relative;
    margin-left: 0;
  }
  .navbar-form .has-feedback .form-control-feedback {
    top: 0;
  }
}
@media (max-width: 540px) {
  .navbar-form .form-group {
    margin-bottom: 5px;
  }
  .navbar-form .form-group:last-child {
    margin-bottom: 0;
  }
}
@media (min-width: 541px) {
  .navbar-form {
    width: auto;
    border: 0;
    margin-left: 0;
    margin-right: 0;
    padding-top: 0;
    padding-bottom: 0;
    -webkit-box-shadow: none;
    box-shadow: none;
  }
}
.navbar-nav > li > .dropdown-menu {
  margin-top: 0;
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.navbar-fixed-bottom .navbar-nav > li > .dropdown-menu {
  margin-bottom: 0;
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.navbar-btn {
  margin-top: -1px;
  margin-bottom: -1px;
}
.navbar-btn.btn-sm {
  margin-top: 0px;
  margin-bottom: 0px;
}
.navbar-btn.btn-xs {
  margin-top: 4px;
  margin-bottom: 4px;
}
.navbar-text {
  margin-top: 6px;
  margin-bottom: 6px;
}
@media (min-width: 541px) {
  .navbar-text {
    float: left;
    margin-left: 0px;
    margin-right: 0px;
  }
}
@media (min-width: 541px) {
  .navbar-left {
    float: left !important;
    float: left;
  }
  .navbar-right {
    float: right !important;
    float: right;
    margin-right: 0px;
  }
  .navbar-right ~ .navbar-right {
    margin-right: 0;
  }
}
.navbar-default {
  background-color: #f8f8f8;
  border-color: #e7e7e7;
}
.navbar-default .navbar-brand {
  color: #777;
}
.navbar-default .navbar-brand:hover,
.navbar-default .navbar-brand:focus {
  color: #5e5e5e;
  background-color: transparent;
}
.navbar-default .navbar-text {
  color: #777;
}
.navbar-default .navbar-nav > li > a {
  color: #777;
}
.navbar-default .navbar-nav > li > a:hover,
.navbar-default .navbar-nav > li > a:focus {
  color: #333;
  background-color: transparent;
}
.navbar-default .navbar-nav > .active > a,
.navbar-default .navbar-nav > .active > a:hover,
.navbar-default .navbar-nav > .active > a:focus {
  color: #555;
  background-color: #e7e7e7;
}
.navbar-default .navbar-nav > .disabled > a,
.navbar-default .navbar-nav > .disabled > a:hover,
.navbar-default .navbar-nav > .disabled > a:focus {
  color: #ccc;
  background-color: transparent;
}
.navbar-default .navbar-toggle {
  border-color: #ddd;
}
.navbar-default .navbar-toggle:hover,
.navbar-default .navbar-toggle:focus {
  background-color: #ddd;
}
.navbar-default .navbar-toggle .icon-bar {
  background-color: #888;
}
.navbar-default .navbar-collapse,
.navbar-default .navbar-form {
  border-color: #e7e7e7;
}
.navbar-default .navbar-nav > .open > a,
.navbar-default .navbar-nav > .open > a:hover,
.navbar-default .navbar-nav > .open > a:focus {
  background-color: #e7e7e7;
  color: #555;
}
@media (max-width: 540px) {
  .navbar-default .navbar-nav .open .dropdown-menu > li > a {
    color: #777;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > li > a:focus {
    color: #333;
    background-color: transparent;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a,
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:focus {
    color: #555;
    background-color: #e7e7e7;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a,
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:focus {
    color: #ccc;
    background-color: transparent;
  }
}
.navbar-default .navbar-link {
  color: #777;
}
.navbar-default .navbar-link:hover {
  color: #333;
}
.navbar-default .btn-link {
  color: #777;
}
.navbar-default .btn-link:hover,
.navbar-default .btn-link:focus {
  color: #333;
}
.navbar-default .btn-link[disabled]:hover,
fieldset[disabled] .navbar-default .btn-link:hover,
.navbar-default .btn-link[disabled]:focus,
fieldset[disabled] .navbar-default .btn-link:focus {
  color: #ccc;
}
.navbar-inverse {
  background-color: #222;
  border-color: #080808;
}
.navbar-inverse .navbar-brand {
  color: #9d9d9d;
}
.navbar-inverse .navbar-brand:hover,
.navbar-inverse .navbar-brand:focus {
  color: #fff;
  background-color: transparent;
}
.navbar-inverse .navbar-text {
  color: #9d9d9d;
}
.navbar-inverse .navbar-nav > li > a {
  color: #9d9d9d;
}
.navbar-inverse .navbar-nav > li > a:hover,
.navbar-inverse .navbar-nav > li > a:focus {
  color: #fff;
  background-color: transparent;
}
.navbar-inverse .navbar-nav > .active > a,
.navbar-inverse .navbar-nav > .active > a:hover,
.navbar-inverse .navbar-nav > .active > a:focus {
  color: #fff;
  background-color: #080808;
}
.navbar-inverse .navbar-nav > .disabled > a,
.navbar-inverse .navbar-nav > .disabled > a:hover,
.navbar-inverse .navbar-nav > .disabled > a:focus {
  color: #444;
  background-color: transparent;
}
.navbar-inverse .navbar-toggle {
  border-color: #333;
}
.navbar-inverse .navbar-toggle:hover,
.navbar-inverse .navbar-toggle:focus {
  background-color: #333;
}
.navbar-inverse .navbar-toggle .icon-bar {
  background-color: #fff;
}
.navbar-inverse .navbar-collapse,
.navbar-inverse .navbar-form {
  border-color: #101010;
}
.navbar-inverse .navbar-nav > .open > a,
.navbar-inverse .navbar-nav > .open > a:hover,
.navbar-inverse .navbar-nav > .open > a:focus {
  background-color: #080808;
  color: #fff;
}
@media (max-width: 540px) {
  .navbar-inverse .navbar-nav .open .dropdown-menu > .dropdown-header {
    border-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu .divider {
    background-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a {
    color: #9d9d9d;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:focus {
    color: #fff;
    background-color: transparent;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:focus {
    color: #fff;
    background-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:focus {
    color: #444;
    background-color: transparent;
  }
}
.navbar-inverse .navbar-link {
  color: #9d9d9d;
}
.navbar-inverse .navbar-link:hover {
  color: #fff;
}
.navbar-inverse .btn-link {
  color: #9d9d9d;
}
.navbar-inverse .btn-link:hover,
.navbar-inverse .btn-link:focus {
  color: #fff;
}
.navbar-inverse .btn-link[disabled]:hover,
fieldset[disabled] .navbar-inverse .btn-link:hover,
.navbar-inverse .btn-link[disabled]:focus,
fieldset[disabled] .navbar-inverse .btn-link:focus {
  color: #444;
}
.breadcrumb {
  padding: 8px 15px;
  margin-bottom: 18px;
  list-style: none;
  background-color: #f5f5f5;
  border-radius: 2px;
}
.breadcrumb > li {
  display: inline-block;
}
.breadcrumb > li + li:before {
  content: "/\00a0";
  padding: 0 5px;
  color: #5e5e5e;
}
.breadcrumb > .active {
  color: #777777;
}
.pagination {
  display: inline-block;
  padding-left: 0;
  margin: 18px 0;
  border-radius: 2px;
}
.pagination > li {
  display: inline;
}
.pagination > li > a,
.pagination > li > span {
  position: relative;
  float: left;
  padding: 6px 12px;
  line-height: 1.42857143;
  text-decoration: none;
  color: #337ab7;
  background-color: #fff;
  border: 1px solid #ddd;
  margin-left: -1px;
}
.pagination > li:first-child > a,
.pagination > li:first-child > span {
  margin-left: 0;
  border-bottom-left-radius: 2px;
  border-top-left-radius: 2px;
}
.pagination > li:last-child > a,
.pagination > li:last-child > span {
  border-bottom-right-radius: 2px;
  border-top-right-radius: 2px;
}
.pagination > li > a:hover,
.pagination > li > span:hover,
.pagination > li > a:focus,
.pagination > li > span:focus {
  z-index: 2;
  color: #23527c;
  background-color: #eeeeee;
  border-color: #ddd;
}
.pagination > .active > a,
.pagination > .active > span,
.pagination > .active > a:hover,
.pagination > .active > span:hover,
.pagination > .active > a:focus,
.pagination > .active > span:focus {
  z-index: 3;
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
  cursor: default;
}
.pagination > .disabled > span,
.pagination > .disabled > span:hover,
.pagination > .disabled > span:focus,
.pagination > .disabled > a,
.pagination > .disabled > a:hover,
.pagination > .disabled > a:focus {
  color: #777777;
  background-color: #fff;
  border-color: #ddd;
  cursor: not-allowed;
}
.pagination-lg > li > a,
.pagination-lg > li > span {
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
}
.pagination-lg > li:first-child > a,
.pagination-lg > li:first-child > span {
  border-bottom-left-radius: 3px;
  border-top-left-radius: 3px;
}
.pagination-lg > li:last-child > a,
.pagination-lg > li:last-child > span {
  border-bottom-right-radius: 3px;
  border-top-right-radius: 3px;
}
.pagination-sm > li > a,
.pagination-sm > li > span {
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
}
.pagination-sm > li:first-child > a,
.pagination-sm > li:first-child > span {
  border-bottom-left-radius: 1px;
  border-top-left-radius: 1px;
}
.pagination-sm > li:last-child > a,
.pagination-sm > li:last-child > span {
  border-bottom-right-radius: 1px;
  border-top-right-radius: 1px;
}
.pager {
  padding-left: 0;
  margin: 18px 0;
  list-style: none;
  text-align: center;
}
.pager li {
  display: inline;
}
.pager li > a,
.pager li > span {
  display: inline-block;
  padding: 5px 14px;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 15px;
}
.pager li > a:hover,
.pager li > a:focus {
  text-decoration: none;
  background-color: #eeeeee;
}
.pager .next > a,
.pager .next > span {
  float: right;
}
.pager .previous > a,
.pager .previous > span {
  float: left;
}
.pager .disabled > a,
.pager .disabled > a:hover,
.pager .disabled > a:focus,
.pager .disabled > span {
  color: #777777;
  background-color: #fff;
  cursor: not-allowed;
}
.label {
  display: inline;
  padding: .2em .6em .3em;
  font-size: 75%;
  font-weight: bold;
  line-height: 1;
  color: #fff;
  text-align: center;
  white-space: nowrap;
  vertical-align: baseline;
  border-radius: .25em;
}
a.label:hover,
a.label:focus {
  color: #fff;
  text-decoration: none;
  cursor: pointer;
}
.label:empty {
  display: none;
}
.btn .label {
  position: relative;
  top: -1px;
}
.label-default {
  background-color: #777777;
}
.label-default[href]:hover,
.label-default[href]:focus {
  background-color: #5e5e5e;
}
.label-primary {
  background-color: #337ab7;
}
.label-primary[href]:hover,
.label-primary[href]:focus {
  background-color: #286090;
}
.label-success {
  background-color: #5cb85c;
}
.label-success[href]:hover,
.label-success[href]:focus {
  background-color: #449d44;
}
.label-info {
  background-color: #5bc0de;
}
.label-info[href]:hover,
.label-info[href]:focus {
  background-color: #31b0d5;
}
.label-warning {
  background-color: #f0ad4e;
}
.label-warning[href]:hover,
.label-warning[href]:focus {
  background-color: #ec971f;
}
.label-danger {
  background-color: #d9534f;
}
.label-danger[href]:hover,
.label-danger[href]:focus {
  background-color: #c9302c;
}
.badge {
  display: inline-block;
  min-width: 10px;
  padding: 3px 7px;
  font-size: 12px;
  font-weight: bold;
  color: #fff;
  line-height: 1;
  vertical-align: middle;
  white-space: nowrap;
  text-align: center;
  background-color: #777777;
  border-radius: 10px;
}
.badge:empty {
  display: none;
}
.btn .badge {
  position: relative;
  top: -1px;
}
.btn-xs .badge,
.btn-group-xs > .btn .badge {
  top: 0;
  padding: 1px 5px;
}
a.badge:hover,
a.badge:focus {
  color: #fff;
  text-decoration: none;
  cursor: pointer;
}
.list-group-item.active > .badge,
.nav-pills > .active > a > .badge {
  color: #337ab7;
  background-color: #fff;
}
.list-group-item > .badge {
  float: right;
}
.list-group-item > .badge + .badge {
  margin-right: 5px;
}
.nav-pills > li > a > .badge {
  margin-left: 3px;
}
.jumbotron {
  padding-top: 30px;
  padding-bottom: 30px;
  margin-bottom: 30px;
  color: inherit;
  background-color: #eeeeee;
}
.jumbotron h1,
.jumbotron .h1 {
  color: inherit;
}
.jumbotron p {
  margin-bottom: 15px;
  font-size: 20px;
  font-weight: 200;
}
.jumbotron > hr {
  border-top-color: #d5d5d5;
}
.container .jumbotron,
.container-fluid .jumbotron {
  border-radius: 3px;
  padding-left: 0px;
  padding-right: 0px;
}
.jumbotron .container {
  max-width: 100%;
}
@media screen and (min-width: 768px) {
  .jumbotron {
    padding-top: 48px;
    padding-bottom: 48px;
  }
  .container .jumbotron,
  .container-fluid .jumbotron {
    padding-left: 60px;
    padding-right: 60px;
  }
  .jumbotron h1,
  .jumbotron .h1 {
    font-size: 59px;
  }
}
.thumbnail {
  display: block;
  padding: 4px;
  margin-bottom: 18px;
  line-height: 1.42857143;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 2px;
  -webkit-transition: border 0.2s ease-in-out;
  -o-transition: border 0.2s ease-in-out;
  transition: border 0.2s ease-in-out;
}
.thumbnail > img,
.thumbnail a > img {
  margin-left: auto;
  margin-right: auto;
}
a.thumbnail:hover,
a.thumbnail:focus,
a.thumbnail.active {
  border-color: #337ab7;
}
.thumbnail .caption {
  padding: 9px;
  color: #000;
}
.alert {
  padding: 15px;
  margin-bottom: 18px;
  border: 1px solid transparent;
  border-radius: 2px;
}
.alert h4 {
  margin-top: 0;
  color: inherit;
}
.alert .alert-link {
  font-weight: bold;
}
.alert > p,
.alert > ul {
  margin-bottom: 0;
}
.alert > p + p {
  margin-top: 5px;
}
.alert-dismissable,
.alert-dismissible {
  padding-right: 35px;
}
.alert-dismissable .close,
.alert-dismissible .close {
  position: relative;
  top: -2px;
  right: -21px;
  color: inherit;
}
.alert-success {
  background-color: #dff0d8;
  border-color: #d6e9c6;
  color: #3c763d;
}
.alert-success hr {
  border-top-color: #c9e2b3;
}
.alert-success .alert-link {
  color: #2b542c;
}
.alert-info {
  background-color: #d9edf7;
  border-color: #bce8f1;
  color: #31708f;
}
.alert-info hr {
  border-top-color: #a6e1ec;
}
.alert-info .alert-link {
  color: #245269;
}
.alert-warning {
  background-color: #fcf8e3;
  border-color: #faebcc;
  color: #8a6d3b;
}
.alert-warning hr {
  border-top-color: #f7e1b5;
}
.alert-warning .alert-link {
  color: #66512c;
}
.alert-danger {
  background-color: #f2dede;
  border-color: #ebccd1;
  color: #a94442;
}
.alert-danger hr {
  border-top-color: #e4b9c0;
}
.alert-danger .alert-link {
  color: #843534;
}
@-webkit-keyframes progress-bar-stripes {
  from {
    background-position: 40px 0;
  }
  to {
    background-position: 0 0;
  }
}
@keyframes progress-bar-stripes {
  from {
    background-position: 40px 0;
  }
  to {
    background-position: 0 0;
  }
}
.progress {
  overflow: hidden;
  height: 18px;
  margin-bottom: 18px;
  background-color: #f5f5f5;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
  box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
}
.progress-bar {
  float: left;
  width: 0%;
  height: 100%;
  font-size: 12px;
  line-height: 18px;
  color: #fff;
  text-align: center;
  background-color: #337ab7;
  -webkit-box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
  -webkit-transition: width 0.6s ease;
  -o-transition: width 0.6s ease;
  transition: width 0.6s ease;
}
.progress-striped .progress-bar,
.progress-bar-striped {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-size: 40px 40px;
}
.progress.active .progress-bar,
.progress-bar.active {
  -webkit-animation: progress-bar-stripes 2s linear infinite;
  -o-animation: progress-bar-stripes 2s linear infinite;
  animation: progress-bar-stripes 2s linear infinite;
}
.progress-bar-success {
  background-color: #5cb85c;
}
.progress-striped .progress-bar-success {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-info {
  background-color: #5bc0de;
}
.progress-striped .progress-bar-info {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-warning {
  background-color: #f0ad4e;
}
.progress-striped .progress-bar-warning {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-danger {
  background-color: #d9534f;
}
.progress-striped .progress-bar-danger {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.media {
  margin-top: 15px;
}
.media:first-child {
  margin-top: 0;
}
.media,
.media-body {
  zoom: 1;
  overflow: hidden;
}
.media-body {
  width: 10000px;
}
.media-object {
  display: block;
}
.media-object.img-thumbnail {
  max-width: none;
}
.media-right,
.media > .pull-right {
  padding-left: 10px;
}
.media-left,
.media > .pull-left {
  padding-right: 10px;
}
.media-left,
.media-right,
.media-body {
  display: table-cell;
  vertical-align: top;
}
.media-middle {
  vertical-align: middle;
}
.media-bottom {
  vertical-align: bottom;
}
.media-heading {
  margin-top: 0;
  margin-bottom: 5px;
}
.media-list {
  padding-left: 0;
  list-style: none;
}
.list-group {
  margin-bottom: 20px;
  padding-left: 0;
}
.list-group-item {
  position: relative;
  display: block;
  padding: 10px 15px;
  margin-bottom: -1px;
  background-color: #fff;
  border: 1px solid #ddd;
}
.list-group-item:first-child {
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
}
.list-group-item:last-child {
  margin-bottom: 0;
  border-bottom-right-radius: 2px;
  border-bottom-left-radius: 2px;
}
a.list-group-item,
button.list-group-item {
  color: #555;
}
a.list-group-item .list-group-item-heading,
button.list-group-item .list-group-item-heading {
  color: #333;
}
a.list-group-item:hover,
button.list-group-item:hover,
a.list-group-item:focus,
button.list-group-item:focus {
  text-decoration: none;
  color: #555;
  background-color: #f5f5f5;
}
button.list-group-item {
  width: 100%;
  text-align: left;
}
.list-group-item.disabled,
.list-group-item.disabled:hover,
.list-group-item.disabled:focus {
  background-color: #eeeeee;
  color: #777777;
  cursor: not-allowed;
}
.list-group-item.disabled .list-group-item-heading,
.list-group-item.disabled:hover .list-group-item-heading,
.list-group-item.disabled:focus .list-group-item-heading {
  color: inherit;
}
.list-group-item.disabled .list-group-item-text,
.list-group-item.disabled:hover .list-group-item-text,
.list-group-item.disabled:focus .list-group-item-text {
  color: #777777;
}
.list-group-item.active,
.list-group-item.active:hover,
.list-group-item.active:focus {
  z-index: 2;
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
}
.list-group-item.active .list-group-item-heading,
.list-group-item.active:hover .list-group-item-heading,
.list-group-item.active:focus .list-group-item-heading,
.list-group-item.active .list-group-item-heading > small,
.list-group-item.active:hover .list-group-item-heading > small,
.list-group-item.active:focus .list-group-item-heading > small,
.list-group-item.active .list-group-item-heading > .small,
.list-group-item.active:hover .list-group-item-heading > .small,
.list-group-item.active:focus .list-group-item-heading > .small {
  color: inherit;
}
.list-group-item.active .list-group-item-text,
.list-group-item.active:hover .list-group-item-text,
.list-group-item.active:focus .list-group-item-text {
  color: #c7ddef;
}
.list-group-item-success {
  color: #3c763d;
  background-color: #dff0d8;
}
a.list-group-item-success,
button.list-group-item-success {
  color: #3c763d;
}
a.list-group-item-success .list-group-item-heading,
button.list-group-item-success .list-group-item-heading {
  color: inherit;
}
a.list-group-item-success:hover,
button.list-group-item-success:hover,
a.list-group-item-success:focus,
button.list-group-item-success:focus {
  color: #3c763d;
  background-color: #d0e9c6;
}
a.list-group-item-success.active,
button.list-group-item-success.active,
a.list-group-item-success.active:hover,
button.list-group-item-success.active:hover,
a.list-group-item-success.active:focus,
button.list-group-item-success.active:focus {
  color: #fff;
  background-color: #3c763d;
  border-color: #3c763d;
}
.list-group-item-info {
  color: #31708f;
  background-color: #d9edf7;
}
a.list-group-item-info,
button.list-group-item-info {
  color: #31708f;
}
a.list-group-item-info .list-group-item-heading,
button.list-group-item-info .list-group-item-heading {
  color: inherit;
}
a.list-group-item-info:hover,
button.list-group-item-info:hover,
a.list-group-item-info:focus,
button.list-group-item-info:focus {
  color: #31708f;
  background-color: #c4e3f3;
}
a.list-group-item-info.active,
button.list-group-item-info.active,
a.list-group-item-info.active:hover,
button.list-group-item-info.active:hover,
a.list-group-item-info.active:focus,
button.list-group-item-info.active:focus {
  color: #fff;
  background-color: #31708f;
  border-color: #31708f;
}
.list-group-item-warning {
  color: #8a6d3b;
  background-color: #fcf8e3;
}
a.list-group-item-warning,
button.list-group-item-warning {
  color: #8a6d3b;
}
a.list-group-item-warning .list-group-item-heading,
button.list-group-item-warning .list-group-item-heading {
  color: inherit;
}
a.list-group-item-warning:hover,
button.list-group-item-warning:hover,
a.list-group-item-warning:focus,
button.list-group-item-warning:focus {
  color: #8a6d3b;
  background-color: #faf2cc;
}
a.list-group-item-warning.active,
button.list-group-item-warning.active,
a.list-group-item-warning.active:hover,
button.list-group-item-warning.active:hover,
a.list-group-item-warning.active:focus,
button.list-group-item-warning.active:focus {
  color: #fff;
  background-color: #8a6d3b;
  border-color: #8a6d3b;
}
.list-group-item-danger {
  color: #a94442;
  background-color: #f2dede;
}
a.list-group-item-danger,
button.list-group-item-danger {
  color: #a94442;
}
a.list-group-item-danger .list-group-item-heading,
button.list-group-item-danger .list-group-item-heading {
  color: inherit;
}
a.list-group-item-danger:hover,
button.list-group-item-danger:hover,
a.list-group-item-danger:focus,
button.list-group-item-danger:focus {
  color: #a94442;
  background-color: #ebcccc;
}
a.list-group-item-danger.active,
button.list-group-item-danger.active,
a.list-group-item-danger.active:hover,
button.list-group-item-danger.active:hover,
a.list-group-item-danger.active:focus,
button.list-group-item-danger.active:focus {
  color: #fff;
  background-color: #a94442;
  border-color: #a94442;
}
.list-group-item-heading {
  margin-top: 0;
  margin-bottom: 5px;
}
.list-group-item-text {
  margin-bottom: 0;
  line-height: 1.3;
}
.panel {
  margin-bottom: 18px;
  background-color: #fff;
  border: 1px solid transparent;
  border-radius: 2px;
  -webkit-box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
  box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
}
.panel-body {
  padding: 15px;
}
.panel-heading {
  padding: 10px 15px;
  border-bottom: 1px solid transparent;
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel-heading > .dropdown .dropdown-toggle {
  color: inherit;
}
.panel-title {
  margin-top: 0;
  margin-bottom: 0;
  font-size: 15px;
  color: inherit;
}
.panel-title > a,
.panel-title > small,
.panel-title > .small,
.panel-title > small > a,
.panel-title > .small > a {
  color: inherit;
}
.panel-footer {
  padding: 10px 15px;
  background-color: #f5f5f5;
  border-top: 1px solid #ddd;
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .list-group,
.panel > .panel-collapse > .list-group {
  margin-bottom: 0;
}
.panel > .list-group .list-group-item,
.panel > .panel-collapse > .list-group .list-group-item {
  border-width: 1px 0;
  border-radius: 0;
}
.panel > .list-group:first-child .list-group-item:first-child,
.panel > .panel-collapse > .list-group:first-child .list-group-item:first-child {
  border-top: 0;
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel > .list-group:last-child .list-group-item:last-child,
.panel > .panel-collapse > .list-group:last-child .list-group-item:last-child {
  border-bottom: 0;
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .panel-heading + .panel-collapse > .list-group .list-group-item:first-child {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.panel-heading + .list-group .list-group-item:first-child {
  border-top-width: 0;
}
.list-group + .panel-footer {
  border-top-width: 0;
}
.panel > .table,
.panel > .table-responsive > .table,
.panel > .panel-collapse > .table {
  margin-bottom: 0;
}
.panel > .table caption,
.panel > .table-responsive > .table caption,
.panel > .panel-collapse > .table caption {
  padding-left: 15px;
  padding-right: 15px;
}
.panel > .table:first-child,
.panel > .table-responsive:first-child > .table:first-child {
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child {
  border-top-left-radius: 1px;
  border-top-right-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child td:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child td:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:first-child,
.panel > .table:first-child > thead:first-child > tr:first-child th:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child th:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:first-child {
  border-top-left-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child td:last-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:last-child,
.panel > .table:first-child > tbody:first-child > tr:first-child td:last-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:last-child,
.panel > .table:first-child > thead:first-child > tr:first-child th:last-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:last-child,
.panel > .table:first-child > tbody:first-child > tr:first-child th:last-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:last-child {
  border-top-right-radius: 1px;
}
.panel > .table:last-child,
.panel > .table-responsive:last-child > .table:last-child {
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child {
  border-bottom-left-radius: 1px;
  border-bottom-right-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child td:first-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:first-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
.panel > .table:last-child > tbody:last-child > tr:last-child th:first-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:first-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child th:first-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:first-child {
  border-bottom-left-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child td:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
.panel > .table:last-child > tbody:last-child > tr:last-child th:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child th:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:last-child {
  border-bottom-right-radius: 1px;
}
.panel > .panel-body + .table,
.panel > .panel-body + .table-responsive,
.panel > .table + .panel-body,
.panel > .table-responsive + .panel-body {
  border-top: 1px solid #ddd;
}
.panel > .table > tbody:first-child > tr:first-child th,
.panel > .table > tbody:first-child > tr:first-child td {
  border-top: 0;
}
.panel > .table-bordered,
.panel > .table-responsive > .table-bordered {
  border: 0;
}
.panel > .table-bordered > thead > tr > th:first-child,
.panel > .table-responsive > .table-bordered > thead > tr > th:first-child,
.panel > .table-bordered > tbody > tr > th:first-child,
.panel > .table-responsive > .table-bordered > tbody > tr > th:first-child,
.panel > .table-bordered > tfoot > tr > th:first-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > th:first-child,
.panel > .table-bordered > thead > tr > td:first-child,
.panel > .table-responsive > .table-bordered > thead > tr > td:first-child,
.panel > .table-bordered > tbody > tr > td:first-child,
.panel > .table-responsive > .table-bordered > tbody > tr > td:first-child,
.panel > .table-bordered > tfoot > tr > td:first-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > td:first-child {
  border-left: 0;
}
.panel > .table-bordered > thead > tr > th:last-child,
.panel > .table-responsive > .table-bordered > thead > tr > th:last-child,
.panel > .table-bordered > tbody > tr > th:last-child,
.panel > .table-responsive > .table-bordered > tbody > tr > th:last-child,
.panel > .table-bordered > tfoot > tr > th:last-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > th:last-child,
.panel > .table-bordered > thead > tr > td:last-child,
.panel > .table-responsive > .table-bordered > thead > tr > td:last-child,
.panel > .table-bordered > tbody > tr > td:last-child,
.panel > .table-responsive > .table-bordered > tbody > tr > td:last-child,
.panel > .table-bordered > tfoot > tr > td:last-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > td:last-child {
  border-right: 0;
}
.panel > .table-bordered > thead > tr:first-child > td,
.panel > .table-responsive > .table-bordered > thead > tr:first-child > td,
.panel > .table-bordered > tbody > tr:first-child > td,
.panel > .table-responsive > .table-bordered > tbody > tr:first-child > td,
.panel > .table-bordered > thead > tr:first-child > th,
.panel > .table-responsive > .table-bordered > thead > tr:first-child > th,
.panel > .table-bordered > tbody > tr:first-child > th,
.panel > .table-responsive > .table-bordered > tbody > tr:first-child > th {
  border-bottom: 0;
}
.panel > .table-bordered > tbody > tr:last-child > td,
.panel > .table-responsive > .table-bordered > tbody > tr:last-child > td,
.panel > .table-bordered > tfoot > tr:last-child > td,
.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > td,
.panel > .table-bordered > tbody > tr:last-child > th,
.panel > .table-responsive > .table-bordered > tbody > tr:last-child > th,
.panel > .table-bordered > tfoot > tr:last-child > th,
.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > th {
  border-bottom: 0;
}
.panel > .table-responsive {
  border: 0;
  margin-bottom: 0;
}
.panel-group {
  margin-bottom: 18px;
}
.panel-group .panel {
  margin-bottom: 0;
  border-radius: 2px;
}
.panel-group .panel + .panel {
  margin-top: 5px;
}
.panel-group .panel-heading {
  border-bottom: 0;
}
.panel-group .panel-heading + .panel-collapse > .panel-body,
.panel-group .panel-heading + .panel-collapse > .list-group {
  border-top: 1px solid #ddd;
}
.panel-group .panel-footer {
  border-top: 0;
}
.panel-group .panel-footer + .panel-collapse .panel-body {
  border-bottom: 1px solid #ddd;
}
.panel-default {
  border-color: #ddd;
}
.panel-default > .panel-heading {
  color: #333333;
  background-color: #f5f5f5;
  border-color: #ddd;
}
.panel-default > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #ddd;
}
.panel-default > .panel-heading .badge {
  color: #f5f5f5;
  background-color: #333333;
}
.panel-default > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #ddd;
}
.panel-primary {
  border-color: #337ab7;
}
.panel-primary > .panel-heading {
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
}
.panel-primary > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #337ab7;
}
.panel-primary > .panel-heading .badge {
  color: #337ab7;
  background-color: #fff;
}
.panel-primary > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #337ab7;
}
.panel-success {
  border-color: #d6e9c6;
}
.panel-success > .panel-heading {
  color: #3c763d;
  background-color: #dff0d8;
  border-color: #d6e9c6;
}
.panel-success > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #d6e9c6;
}
.panel-success > .panel-heading .badge {
  color: #dff0d8;
  background-color: #3c763d;
}
.panel-success > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #d6e9c6;
}
.panel-info {
  border-color: #bce8f1;
}
.panel-info > .panel-heading {
  color: #31708f;
  background-color: #d9edf7;
  border-color: #bce8f1;
}
.panel-info > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #bce8f1;
}
.panel-info > .panel-heading .badge {
  color: #d9edf7;
  background-color: #31708f;
}
.panel-info > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #bce8f1;
}
.panel-warning {
  border-color: #faebcc;
}
.panel-warning > .panel-heading {
  color: #8a6d3b;
  background-color: #fcf8e3;
  border-color: #faebcc;
}
.panel-warning > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #faebcc;
}
.panel-warning > .panel-heading .badge {
  color: #fcf8e3;
  background-color: #8a6d3b;
}
.panel-warning > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #faebcc;
}
.panel-danger {
  border-color: #ebccd1;
}
.panel-danger > .panel-heading {
  color: #a94442;
  background-color: #f2dede;
  border-color: #ebccd1;
}
.panel-danger > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #ebccd1;
}
.panel-danger > .panel-heading .badge {
  color: #f2dede;
  background-color: #a94442;
}
.panel-danger > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #ebccd1;
}
.embed-responsive {
  position: relative;
  display: block;
  height: 0;
  padding: 0;
  overflow: hidden;
}
.embed-responsive .embed-responsive-item,
.embed-responsive iframe,
.embed-responsive embed,
.embed-responsive object,
.embed-responsive video {
  position: absolute;
  top: 0;
  left: 0;
  bottom: 0;
  height: 100%;
  width: 100%;
  border: 0;
}
.embed-responsive-16by9 {
  padding-bottom: 56.25%;
}
.embed-responsive-4by3 {
  padding-bottom: 75%;
}
.well {
  min-height: 20px;
  padding: 19px;
  margin-bottom: 20px;
  background-color: #f5f5f5;
  border: 1px solid #e3e3e3;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
}
.well blockquote {
  border-color: #ddd;
  border-color: rgba(0, 0, 0, 0.15);
}
.well-lg {
  padding: 24px;
  border-radius: 3px;
}
.well-sm {
  padding: 9px;
  border-radius: 1px;
}
.close {
  float: right;
  font-size: 19.5px;
  font-weight: bold;
  line-height: 1;
  color: #000;
  text-shadow: 0 1px 0 #fff;
  opacity: 0.2;
  filter: alpha(opacity=20);
}
.close:hover,
.close:focus {
  color: #000;
  text-decoration: none;
  cursor: pointer;
  opacity: 0.5;
  filter: alpha(opacity=50);
}
button.close {
  padding: 0;
  cursor: pointer;
  background: transparent;
  border: 0;
  -webkit-appearance: none;
}
.modal-open {
  overflow: hidden;
}
.modal {
  display: none;
  overflow: hidden;
  position: fixed;
  top: 0;
  right: 0;
  bottom: 0;
  left: 0;
  z-index: 1050;
  -webkit-overflow-scrolling: touch;
  outline: 0;
}
.modal.fade .modal-dialog {
  -webkit-transform: translate(0, -25%);
  -ms-transform: translate(0, -25%);
  -o-transform: translate(0, -25%);
  transform: translate(0, -25%);
  -webkit-transition: -webkit-transform 0.3s ease-out;
  -moz-transition: -moz-transform 0.3s ease-out;
  -o-transition: -o-transform 0.3s ease-out;
  transition: transform 0.3s ease-out;
}
.modal.in .modal-dialog {
  -webkit-transform: translate(0, 0);
  -ms-transform: translate(0, 0);
  -o-transform: translate(0, 0);
  transform: translate(0, 0);
}
.modal-open .modal {
  overflow-x: hidden;
  overflow-y: auto;
}
.modal-dialog {
  position: relative;
  width: auto;
  margin: 10px;
}
.modal-content {
  position: relative;
  background-color: #fff;
  border: 1px solid #999;
  border: 1px solid rgba(0, 0, 0, 0.2);
  border-radius: 3px;
  -webkit-box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
  box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
  background-clip: padding-box;
  outline: 0;
}
.modal-backdrop {
  position: fixed;
  top: 0;
  right: 0;
  bottom: 0;
  left: 0;
  z-index: 1040;
  background-color: #000;
}
.modal-backdrop.fade {
  opacity: 0;
  filter: alpha(opacity=0);
}
.modal-backdrop.in {
  opacity: 0.5;
  filter: alpha(opacity=50);
}
.modal-header {
  padding: 15px;
  border-bottom: 1px solid #e5e5e5;
}
.modal-header .close {
  margin-top: -2px;
}
.modal-title {
  margin: 0;
  line-height: 1.42857143;
}
.modal-body {
  position: relative;
  padding: 15px;
}
.modal-footer {
  padding: 15px;
  text-align: right;
  border-top: 1px solid #e5e5e5;
}
.modal-footer .btn + .btn {
  margin-left: 5px;
  margin-bottom: 0;
}
.modal-footer .btn-group .btn + .btn {
  margin-left: -1px;
}
.modal-footer .btn-block + .btn-block {
  margin-left: 0;
}
.modal-scrollbar-measure {
  position: absolute;
  top: -9999px;
  width: 50px;
  height: 50px;
  overflow: scroll;
}
@media (min-width: 768px) {
  .modal-dialog {
    width: 600px;
    margin: 30px auto;
  }
  .modal-content {
    -webkit-box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
    box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
  }
  .modal-sm {
    width: 300px;
  }
}
@media (min-width: 992px) {
  .modal-lg {
    width: 900px;
  }
}
.tooltip {
  position: absolute;
  z-index: 1070;
  display: block;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-style: normal;
  font-weight: normal;
  letter-spacing: normal;
  line-break: auto;
  line-height: 1.42857143;
  text-align: left;
  text-align: start;
  text-decoration: none;
  text-shadow: none;
  text-transform: none;
  white-space: normal;
  word-break: normal;
  word-spacing: normal;
  word-wrap: normal;
  font-size: 12px;
  opacity: 0;
  filter: alpha(opacity=0);
}
.tooltip.in {
  opacity: 0.9;
  filter: alpha(opacity=90);
}
.tooltip.top {
  margin-top: -3px;
  padding: 5px 0;
}
.tooltip.right {
  margin-left: 3px;
  padding: 0 5px;
}
.tooltip.bottom {
  margin-top: 3px;
  padding: 5px 0;
}
.tooltip.left {
  margin-left: -3px;
  padding: 0 5px;
}
.tooltip-inner {
  max-width: 200px;
  padding: 3px 8px;
  color: #fff;
  text-align: center;
  background-color: #000;
  border-radius: 2px;
}
.tooltip-arrow {
  position: absolute;
  width: 0;
  height: 0;
  border-color: transparent;
  border-style: solid;
}
.tooltip.top .tooltip-arrow {
  bottom: 0;
  left: 50%;
  margin-left: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.top-left .tooltip-arrow {
  bottom: 0;
  right: 5px;
  margin-bottom: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.top-right .tooltip-arrow {
  bottom: 0;
  left: 5px;
  margin-bottom: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.right .tooltip-arrow {
  top: 50%;
  left: 0;
  margin-top: -5px;
  border-width: 5px 5px 5px 0;
  border-right-color: #000;
}
.tooltip.left .tooltip-arrow {
  top: 50%;
  right: 0;
  margin-top: -5px;
  border-width: 5px 0 5px 5px;
  border-left-color: #000;
}
.tooltip.bottom .tooltip-arrow {
  top: 0;
  left: 50%;
  margin-left: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.tooltip.bottom-left .tooltip-arrow {
  top: 0;
  right: 5px;
  margin-top: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.tooltip.bottom-right .tooltip-arrow {
  top: 0;
  left: 5px;
  margin-top: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.popover {
  position: absolute;
  top: 0;
  left: 0;
  z-index: 1060;
  display: none;
  max-width: 276px;
  padding: 1px;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-style: normal;
  font-weight: normal;
  letter-spacing: normal;
  line-break: auto;
  line-height: 1.42857143;
  text-align: left;
  text-align: start;
  text-decoration: none;
  text-shadow: none;
  text-transform: none;
  white-space: normal;
  word-break: normal;
  word-spacing: normal;
  word-wrap: normal;
  font-size: 13px;
  background-color: #fff;
  background-clip: padding-box;
  border: 1px solid #ccc;
  border: 1px solid rgba(0, 0, 0, 0.2);
  border-radius: 3px;
  -webkit-box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
  box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
}
.popover.top {
  margin-top: -10px;
}
.popover.right {
  margin-left: 10px;
}
.popover.bottom {
  margin-top: 10px;
}
.popover.left {
  margin-left: -10px;
}
.popover-title {
  margin: 0;
  padding: 8px 14px;
  font-size: 13px;
  background-color: #f7f7f7;
  border-bottom: 1px solid #ebebeb;
  border-radius: 2px 2px 0 0;
}
.popover-content {
  padding: 9px 14px;
}
.popover > .arrow,
.popover > .arrow:after {
  position: absolute;
  display: block;
  width: 0;
  height: 0;
  border-color: transparent;
  border-style: solid;
}
.popover > .arrow {
  border-width: 11px;
}
.popover > .arrow:after {
  border-width: 10px;
  content: "";
}
.popover.top > .arrow {
  left: 50%;
  margin-left: -11px;
  border-bottom-width: 0;
  border-top-color: #999999;
  border-top-color: rgba(0, 0, 0, 0.25);
  bottom: -11px;
}
.popover.top > .arrow:after {
  content: " ";
  bottom: 1px;
  margin-left: -10px;
  border-bottom-width: 0;
  border-top-color: #fff;
}
.popover.right > .arrow {
  top: 50%;
  left: -11px;
  margin-top: -11px;
  border-left-width: 0;
  border-right-color: #999999;
  border-right-color: rgba(0, 0, 0, 0.25);
}
.popover.right > .arrow:after {
  content: " ";
  left: 1px;
  bottom: -10px;
  border-left-width: 0;
  border-right-color: #fff;
}
.popover.bottom > .arrow {
  left: 50%;
  margin-left: -11px;
  border-top-width: 0;
  border-bottom-color: #999999;
  border-bottom-color: rgba(0, 0, 0, 0.25);
  top: -11px;
}
.popover.bottom > .arrow:after {
  content: " ";
  top: 1px;
  margin-left: -10px;
  border-top-width: 0;
  border-bottom-color: #fff;
}
.popover.left > .arrow {
  top: 50%;
  right: -11px;
  margin-top: -11px;
  border-right-width: 0;
  border-left-color: #999999;
  border-left-color: rgba(0, 0, 0, 0.25);
}
.popover.left > .arrow:after {
  content: " ";
  right: 1px;
  border-right-width: 0;
  border-left-color: #fff;
  bottom: -10px;
}
.carousel {
  position: relative;
}
.carousel-inner {
  position: relative;
  overflow: hidden;
  width: 100%;
}
.carousel-inner > .item {
  display: none;
  position: relative;
  -webkit-transition: 0.6s ease-in-out left;
  -o-transition: 0.6s ease-in-out left;
  transition: 0.6s ease-in-out left;
}
.carousel-inner > .item > img,
.carousel-inner > .item > a > img {
  line-height: 1;
}
@media all and (transform-3d), (-webkit-transform-3d) {
  .carousel-inner > .item {
    -webkit-transition: -webkit-transform 0.6s ease-in-out;
    -moz-transition: -moz-transform 0.6s ease-in-out;
    -o-transition: -o-transform 0.6s ease-in-out;
    transition: transform 0.6s ease-in-out;
    -webkit-backface-visibility: hidden;
    -moz-backface-visibility: hidden;
    backface-visibility: hidden;
    -webkit-perspective: 1000px;
    -moz-perspective: 1000px;
    perspective: 1000px;
  }
  .carousel-inner > .item.next,
  .carousel-inner > .item.active.right {
    -webkit-transform: translate3d(100%, 0, 0);
    transform: translate3d(100%, 0, 0);
    left: 0;
  }
  .carousel-inner > .item.prev,
  .carousel-inner > .item.active.left {
    -webkit-transform: translate3d(-100%, 0, 0);
    transform: translate3d(-100%, 0, 0);
    left: 0;
  }
  .carousel-inner > .item.next.left,
  .carousel-inner > .item.prev.right,
  .carousel-inner > .item.active {
    -webkit-transform: translate3d(0, 0, 0);
    transform: translate3d(0, 0, 0);
    left: 0;
  }
}
.carousel-inner > .active,
.carousel-inner > .next,
.carousel-inner > .prev {
  display: block;
}
.carousel-inner > .active {
  left: 0;
}
.carousel-inner > .next,
.carousel-inner > .prev {
  position: absolute;
  top: 0;
  width: 100%;
}
.carousel-inner > .next {
  left: 100%;
}
.carousel-inner > .prev {
  left: -100%;
}
.carousel-inner > .next.left,
.carousel-inner > .prev.right {
  left: 0;
}
.carousel-inner > .active.left {
  left: -100%;
}
.carousel-inner > .active.right {
  left: 100%;
}
.carousel-control {
  position: absolute;
  top: 0;
  left: 0;
  bottom: 0;
  width: 15%;
  opacity: 0.5;
  filter: alpha(opacity=50);
  font-size: 20px;
  color: #fff;
  text-align: center;
  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
  background-color: rgba(0, 0, 0, 0);
}
.carousel-control.left {
  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-repeat: repeat-x;
  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#80000000', endColorstr='#00000000', GradientType=1);
}
.carousel-control.right {
  left: auto;
  right: 0;
  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-repeat: repeat-x;
  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#00000000', endColorstr='#80000000', GradientType=1);
}
.carousel-control:hover,
.carousel-control:focus {
  outline: 0;
  color: #fff;
  text-decoration: none;
  opacity: 0.9;
  filter: alpha(opacity=90);
}
.carousel-control .icon-prev,
.carousel-control .icon-next,
.carousel-control .glyphicon-chevron-left,
.carousel-control .glyphicon-chevron-right {
  position: absolute;
  top: 50%;
  margin-top: -10px;
  z-index: 5;
  display: inline-block;
}
.carousel-control .icon-prev,
.carousel-control .glyphicon-chevron-left {
  left: 50%;
  margin-left: -10px;
}
.carousel-control .icon-next,
.carousel-control .glyphicon-chevron-right {
  right: 50%;
  margin-right: -10px;
}
.carousel-control .icon-prev,
.carousel-control .icon-next {
  width: 20px;
  height: 20px;
  line-height: 1;
  font-family: serif;
}
.carousel-control .icon-prev:before {
  content: '\2039';
}
.carousel-control .icon-next:before {
  content: '\203a';
}
.carousel-indicators {
  position: absolute;
  bottom: 10px;
  left: 50%;
  z-index: 15;
  width: 60%;
  margin-left: -30%;
  padding-left: 0;
  list-style: none;
  text-align: center;
}
.carousel-indicators li {
  display: inline-block;
  width: 10px;
  height: 10px;
  margin: 1px;
  text-indent: -999px;
  border: 1px solid #fff;
  border-radius: 10px;
  cursor: pointer;
  background-color: #000 \9;
  background-color: rgba(0, 0, 0, 0);
}
.carousel-indicators .active {
  margin: 0;
  width: 12px;
  height: 12px;
  background-color: #fff;
}
.carousel-caption {
  position: absolute;
  left: 15%;
  right: 15%;
  bottom: 20px;
  z-index: 10;
  padding-top: 20px;
  padding-bottom: 20px;
  color: #fff;
  text-align: center;
  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
}
.carousel-caption .btn {
  text-shadow: none;
}
@media screen and (min-width: 768px) {
  .carousel-control .glyphicon-chevron-left,
  .carousel-control .glyphicon-chevron-right,
  .carousel-control .icon-prev,
  .carousel-control .icon-next {
    width: 30px;
    height: 30px;
    margin-top: -10px;
    font-size: 30px;
  }
  .carousel-control .glyphicon-chevron-left,
  .carousel-control .icon-prev {
    margin-left: -10px;
  }
  .carousel-control .glyphicon-chevron-right,
  .carousel-control .icon-next {
    margin-right: -10px;
  }
  .carousel-caption {
    left: 20%;
    right: 20%;
    padding-bottom: 30px;
  }
  .carousel-indicators {
    bottom: 20px;
  }
}
.clearfix:before,
.clearfix:after,
.dl-horizontal dd:before,
.dl-horizontal dd:after,
.container:before,
.container:after,
.container-fluid:before,
.container-fluid:after,
.row:before,
.row:after,
.form-horizontal .form-group:before,
.form-horizontal .form-group:after,
.btn-toolbar:before,
.btn-toolbar:after,
.btn-group-vertical > .btn-group:before,
.btn-group-vertical > .btn-group:after,
.nav:before,
.nav:after,
.navbar:before,
.navbar:after,
.navbar-header:before,
.navbar-header:after,
.navbar-collapse:before,
.navbar-collapse:after,
.pager:before,
.pager:after,
.panel-body:before,
.panel-body:after,
.modal-header:before,
.modal-header:after,
.modal-footer:before,
.modal-footer:after,
.item_buttons:before,
.item_buttons:after {
  content: " ";
  display: table;
}
.clearfix:after,
.dl-horizontal dd:after,
.container:after,
.container-fluid:after,
.row:after,
.form-horizontal .form-group:after,
.btn-toolbar:after,
.btn-group-vertical > .btn-group:after,
.nav:after,
.navbar:after,
.navbar-header:after,
.navbar-collapse:after,
.pager:after,
.panel-body:after,
.modal-header:after,
.modal-footer:after,
.item_buttons:after {
  clear: both;
}
.center-block {
  display: block;
  margin-left: auto;
  margin-right: auto;
}
.pull-right {
  float: right !important;
}
.pull-left {
  float: left !important;
}
.hide {
  display: none !important;
}
.show {
  display: block !important;
}
.invisible {
  visibility: hidden;
}
.text-hide {
  font: 0/0 a;
  color: transparent;
  text-shadow: none;
  background-color: transparent;
  border: 0;
}
.hidden {
  display: none !important;
}
.affix {
  position: fixed;
}
@-ms-viewport {
  width: device-width;
}
.visible-xs,
.visible-sm,
.visible-md,
.visible-lg {
  display: none !important;
}
.visible-xs-block,
.visible-xs-inline,
.visible-xs-inline-block,
.visible-sm-block,
.visible-sm-inline,
.visible-sm-inline-block,
.visible-md-block,
.visible-md-inline,
.visible-md-inline-block,
.visible-lg-block,
.visible-lg-inline,
.visible-lg-inline-block {
  display: none !important;
}
@media (max-width: 767px) {
  .visible-xs {
    display: block !important;
  }
  table.visible-xs {
    display: table !important;
  }
  tr.visible-xs {
    display: table-row !important;
  }
  th.visible-xs,
  td.visible-xs {
    display: table-cell !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-block {
    display: block !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-inline {
    display: inline !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm {
    display: block !important;
  }
  table.visible-sm {
    display: table !important;
  }
  tr.visible-sm {
    display: table-row !important;
  }
  th.visible-sm,
  td.visible-sm {
    display: table-cell !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-block {
    display: block !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-inline {
    display: inline !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md {
    display: block !important;
  }
  table.visible-md {
    display: table !important;
  }
  tr.visible-md {
    display: table-row !important;
  }
  th.visible-md,
  td.visible-md {
    display: table-cell !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-block {
    display: block !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-inline {
    display: inline !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg {
    display: block !important;
  }
  table.visible-lg {
    display: table !important;
  }
  tr.visible-lg {
    display: table-row !important;
  }
  th.visible-lg,
  td.visible-lg {
    display: table-cell !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-block {
    display: block !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-inline {
    display: inline !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-inline-block {
    display: inline-block !important;
  }
}
@media (max-width: 767px) {
  .hidden-xs {
    display: none !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .hidden-sm {
    display: none !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .hidden-md {
    display: none !important;
  }
}
@media (min-width: 1200px) {
  .hidden-lg {
    display: none !important;
  }
}
.visible-print {
  display: none !important;
}
@media print {
  .visible-print {
    display: block !important;
  }
  table.visible-print {
    display: table !important;
  }
  tr.visible-print {
    display: table-row !important;
  }
  th.visible-print,
  td.visible-print {
    display: table-cell !important;
  }
}
.visible-print-block {
  display: none !important;
}
@media print {
  .visible-print-block {
    display: block !important;
  }
}
.visible-print-inline {
  display: none !important;
}
@media print {
  .visible-print-inline {
    display: inline !important;
  }
}
.visible-print-inline-block {
  display: none !important;
}
@media print {
  .visible-print-inline-block {
    display: inline-block !important;
  }
}
@media print {
  .hidden-print {
    display: none !important;
  }
}
/*!
*
* Font Awesome
*
*/
/*!
 *  Font Awesome 4.2.0 by @davegandy - http://fontawesome.io - @fontawesome
 *  License - http://fontawesome.io/license (Font: SIL OFL 1.1, CSS: MIT License)
 */
/* FONT PATH
 * -------------------------- */
@font-face {
  font-family: 'FontAwesome';
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?v=4.2.0');
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?#iefix&v=4.2.0') format('embedded-opentype'), url('../components/font-awesome/fonts/fontawesome-webfont.woff?v=4.2.0') format('woff'), url('../components/font-awesome/fonts/fontawesome-webfont.ttf?v=4.2.0') format('truetype'), url('../components/font-awesome/fonts/fontawesome-webfont.svg?v=4.2.0#fontawesomeregular') format('svg');
  font-weight: normal;
  font-style: normal;
}
.fa {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
}
/* makes the font 33% larger relative to the icon container */
.fa-lg {
  font-size: 1.33333333em;
  line-height: 0.75em;
  vertical-align: -15%;
}
.fa-2x {
  font-size: 2em;
}
.fa-3x {
  font-size: 3em;
}
.fa-4x {
  font-size: 4em;
}
.fa-5x {
  font-size: 5em;
}
.fa-fw {
  width: 1.28571429em;
  text-align: center;
}
.fa-ul {
  padding-left: 0;
  margin-left: 2.14285714em;
  list-style-type: none;
}
.fa-ul > li {
  position: relative;
}
.fa-li {
  position: absolute;
  left: -2.14285714em;
  width: 2.14285714em;
  top: 0.14285714em;
  text-align: center;
}
.fa-li.fa-lg {
  left: -1.85714286em;
}
.fa-border {
  padding: .2em .25em .15em;
  border: solid 0.08em #eee;
  border-radius: .1em;
}
.pull-right {
  float: right;
}
.pull-left {
  float: left;
}
.fa.pull-left {
  margin-right: .3em;
}
.fa.pull-right {
  margin-left: .3em;
}
.fa-spin {
  -webkit-animation: fa-spin 2s infinite linear;
  animation: fa-spin 2s infinite linear;
}
@-webkit-keyframes fa-spin {
  0% {
    -webkit-transform: rotate(0deg);
    transform: rotate(0deg);
  }
  100% {
    -webkit-transform: rotate(359deg);
    transform: rotate(359deg);
  }
}
@keyframes fa-spin {
  0% {
    -webkit-transform: rotate(0deg);
    transform: rotate(0deg);
  }
  100% {
    -webkit-transform: rotate(359deg);
    transform: rotate(359deg);
  }
}
.fa-rotate-90 {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=1);
  -webkit-transform: rotate(90deg);
  -ms-transform: rotate(90deg);
  transform: rotate(90deg);
}
.fa-rotate-180 {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=2);
  -webkit-transform: rotate(180deg);
  -ms-transform: rotate(180deg);
  transform: rotate(180deg);
}
.fa-rotate-270 {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=3);
  -webkit-transform: rotate(270deg);
  -ms-transform: rotate(270deg);
  transform: rotate(270deg);
}
.fa-flip-horizontal {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=0, mirror=1);
  -webkit-transform: scale(-1, 1);
  -ms-transform: scale(-1, 1);
  transform: scale(-1, 1);
}
.fa-flip-vertical {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=2, mirror=1);
  -webkit-transform: scale(1, -1);
  -ms-transform: scale(1, -1);
  transform: scale(1, -1);
}
:root .fa-rotate-90,
:root .fa-rotate-180,
:root .fa-rotate-270,
:root .fa-flip-horizontal,
:root .fa-flip-vertical {
  filter: none;
}
.fa-stack {
  position: relative;
  display: inline-block;
  width: 2em;
  height: 2em;
  line-height: 2em;
  vertical-align: middle;
}
.fa-stack-1x,
.fa-stack-2x {
  position: absolute;
  left: 0;
  width: 100%;
  text-align: center;
}
.fa-stack-1x {
  line-height: inherit;
}
.fa-stack-2x {
  font-size: 2em;
}
.fa-inverse {
  color: #fff;
}
/* Font Awesome uses the Unicode Private Use Area (PUA) to ensure screen
   readers do not read off random characters that represent icons */
.fa-glass:before {
  content: "\f000";
}
.fa-music:before {
  content: "\f001";
}
.fa-search:before {
  content: "\f002";
}
.fa-envelope-o:before {
  content: "\f003";
}
.fa-heart:before {
  content: "\f004";
}
.fa-star:before {
  content: "\f005";
}
.fa-star-o:before {
  content: "\f006";
}
.fa-user:before {
  content: "\f007";
}
.fa-film:before {
  content: "\f008";
}
.fa-th-large:before {
  content: "\f009";
}
.fa-th:before {
  content: "\f00a";
}
.fa-th-list:before {
  content: "\f00b";
}
.fa-check:before {
  content: "\f00c";
}
.fa-remove:before,
.fa-close:before,
.fa-times:before {
  content: "\f00d";
}
.fa-search-plus:before {
  content: "\f00e";
}
.fa-search-minus:before {
  content: "\f010";
}
.fa-power-off:before {
  content: "\f011";
}
.fa-signal:before {
  content: "\f012";
}
.fa-gear:before,
.fa-cog:before {
  content: "\f013";
}
.fa-trash-o:before {
  content: "\f014";
}
.fa-home:before {
  content: "\f015";
}
.fa-file-o:before {
  content: "\f016";
}
.fa-clock-o:before {
  content: "\f017";
}
.fa-road:before {
  content: "\f018";
}
.fa-download:before {
  content: "\f019";
}
.fa-arrow-circle-o-down:before {
  content: "\f01a";
}
.fa-arrow-circle-o-up:before {
  content: "\f01b";
}
.fa-inbox:before {
  content: "\f01c";
}
.fa-play-circle-o:before {
  content: "\f01d";
}
.fa-rotate-right:before,
.fa-repeat:before {
  content: "\f01e";
}
.fa-refresh:before {
  content: "\f021";
}
.fa-list-alt:before {
  content: "\f022";
}
.fa-lock:before {
  content: "\f023";
}
.fa-flag:before {
  content: "\f024";
}
.fa-headphones:before {
  content: "\f025";
}
.fa-volume-off:before {
  content: "\f026";
}
.fa-volume-down:before {
  content: "\f027";
}
.fa-volume-up:before {
  content: "\f028";
}
.fa-qrcode:before {
  content: "\f029";
}
.fa-barcode:before {
  content: "\f02a";
}
.fa-tag:before {
  content: "\f02b";
}
.fa-tags:before {
  content: "\f02c";
}
.fa-book:before {
  content: "\f02d";
}
.fa-bookmark:before {
  content: "\f02e";
}
.fa-print:before {
  content: "\f02f";
}
.fa-camera:before {
  content: "\f030";
}
.fa-font:before {
  content: "\f031";
}
.fa-bold:before {
  content: "\f032";
}
.fa-italic:before {
  content: "\f033";
}
.fa-text-height:before {
  content: "\f034";
}
.fa-text-width:before {
  content: "\f035";
}
.fa-align-left:before {
  content: "\f036";
}
.fa-align-center:before {
  content: "\f037";
}
.fa-align-right:before {
  content: "\f038";
}
.fa-align-justify:before {
  content: "\f039";
}
.fa-list:before {
  content: "\f03a";
}
.fa-dedent:before,
.fa-outdent:before {
  content: "\f03b";
}
.fa-indent:before {
  content: "\f03c";
}
.fa-video-camera:before {
  content: "\f03d";
}
.fa-photo:before,
.fa-image:before,
.fa-picture-o:before {
  content: "\f03e";
}
.fa-pencil:before {
  content: "\f040";
}
.fa-map-marker:before {
  content: "\f041";
}
.fa-adjust:before {
  content: "\f042";
}
.fa-tint:before {
  content: "\f043";
}
.fa-edit:before,
.fa-pencil-square-o:before {
  content: "\f044";
}
.fa-share-square-o:before {
  content: "\f045";
}
.fa-check-square-o:before {
  content: "\f046";
}
.fa-arrows:before {
  content: "\f047";
}
.fa-step-backward:before {
  content: "\f048";
}
.fa-fast-backward:before {
  content: "\f049";
}
.fa-backward:before {
  content: "\f04a";
}
.fa-play:before {
  content: "\f04b";
}
.fa-pause:before {
  content: "\f04c";
}
.fa-stop:before {
  content: "\f04d";
}
.fa-forward:before {
  content: "\f04e";
}
.fa-fast-forward:before {
  content: "\f050";
}
.fa-step-forward:before {
  content: "\f051";
}
.fa-eject:before {
  content: "\f052";
}
.fa-chevron-left:before {
  content: "\f053";
}
.fa-chevron-right:before {
  content: "\f054";
}
.fa-plus-circle:before {
  content: "\f055";
}
.fa-minus-circle:before {
  content: "\f056";
}
.fa-times-circle:before {
  content: "\f057";
}
.fa-check-circle:before {
  content: "\f058";
}
.fa-question-circle:before {
  content: "\f059";
}
.fa-info-circle:before {
  content: "\f05a";
}
.fa-crosshairs:before {
  content: "\f05b";
}
.fa-times-circle-o:before {
  content: "\f05c";
}
.fa-check-circle-o:before {
  content: "\f05d";
}
.fa-ban:before {
  content: "\f05e";
}
.fa-arrow-left:before {
  content: "\f060";
}
.fa-arrow-right:before {
  content: "\f061";
}
.fa-arrow-up:before {
  content: "\f062";
}
.fa-arrow-down:before {
  content: "\f063";
}
.fa-mail-forward:before,
.fa-share:before {
  content: "\f064";
}
.fa-expand:before {
  content: "\f065";
}
.fa-compress:before {
  content: "\f066";
}
.fa-plus:before {
  content: "\f067";
}
.fa-minus:before {
  content: "\f068";
}
.fa-asterisk:before {
  content: "\f069";
}
.fa-exclamation-circle:before {
  content: "\f06a";
}
.fa-gift:before {
  content: "\f06b";
}
.fa-leaf:before {
  content: "\f06c";
}
.fa-fire:before {
  content: "\f06d";
}
.fa-eye:before {
  content: "\f06e";
}
.fa-eye-slash:before {
  content: "\f070";
}
.fa-warning:before,
.fa-exclamation-triangle:before {
  content: "\f071";
}
.fa-plane:before {
  content: "\f072";
}
.fa-calendar:before {
  content: "\f073";
}
.fa-random:before {
  content: "\f074";
}
.fa-comment:before {
  content: "\f075";
}
.fa-magnet:before {
  content: "\f076";
}
.fa-chevron-up:before {
  content: "\f077";
}
.fa-chevron-down:before {
  content: "\f078";
}
.fa-retweet:before {
  content: "\f079";
}
.fa-shopping-cart:before {
  content: "\f07a";
}
.fa-folder:before {
  content: "\f07b";
}
.fa-folder-open:before {
  content: "\f07c";
}
.fa-arrows-v:before {
  content: "\f07d";
}
.fa-arrows-h:before {
  content: "\f07e";
}
.fa-bar-chart-o:before,
.fa-bar-chart:before {
  content: "\f080";
}
.fa-twitter-square:before {
  content: "\f081";
}
.fa-facebook-square:before {
  content: "\f082";
}
.fa-camera-retro:before {
  content: "\f083";
}
.fa-key:before {
  content: "\f084";
}
.fa-gears:before,
.fa-cogs:before {
  content: "\f085";
}
.fa-comments:before {
  content: "\f086";
}
.fa-thumbs-o-up:before {
  content: "\f087";
}
.fa-thumbs-o-down:before {
  content: "\f088";
}
.fa-star-half:before {
  content: "\f089";
}
.fa-heart-o:before {
  content: "\f08a";
}
.fa-sign-out:before {
  content: "\f08b";
}
.fa-linkedin-square:before {
  content: "\f08c";
}
.fa-thumb-tack:before {
  content: "\f08d";
}
.fa-external-link:before {
  content: "\f08e";
}
.fa-sign-in:before {
  content: "\f090";
}
.fa-trophy:before {
  content: "\f091";
}
.fa-github-square:before {
  content: "\f092";
}
.fa-upload:before {
  content: "\f093";
}
.fa-lemon-o:before {
  content: "\f094";
}
.fa-phone:before {
  content: "\f095";
}
.fa-square-o:before {
  content: "\f096";
}
.fa-bookmark-o:before {
  content: "\f097";
}
.fa-phone-square:before {
  content: "\f098";
}
.fa-twitter:before {
  content: "\f099";
}
.fa-facebook:before {
  content: "\f09a";
}
.fa-github:before {
  content: "\f09b";
}
.fa-unlock:before {
  content: "\f09c";
}
.fa-credit-card:before {
  content: "\f09d";
}
.fa-rss:before {
  content: "\f09e";
}
.fa-hdd-o:before {
  content: "\f0a0";
}
.fa-bullhorn:before {
  content: "\f0a1";
}
.fa-bell:before {
  content: "\f0f3";
}
.fa-certificate:before {
  content: "\f0a3";
}
.fa-hand-o-right:before {
  content: "\f0a4";
}
.fa-hand-o-left:before {
  content: "\f0a5";
}
.fa-hand-o-up:before {
  content: "\f0a6";
}
.fa-hand-o-down:before {
  content: "\f0a7";
}
.fa-arrow-circle-left:before {
  content: "\f0a8";
}
.fa-arrow-circle-right:before {
  content: "\f0a9";
}
.fa-arrow-circle-up:before {
  content: "\f0aa";
}
.fa-arrow-circle-down:before {
  content: "\f0ab";
}
.fa-globe:before {
  content: "\f0ac";
}
.fa-wrench:before {
  content: "\f0ad";
}
.fa-tasks:before {
  content: "\f0ae";
}
.fa-filter:before {
  content: "\f0b0";
}
.fa-briefcase:before {
  content: "\f0b1";
}
.fa-arrows-alt:before {
  content: "\f0b2";
}
.fa-group:before,
.fa-users:before {
  content: "\f0c0";
}
.fa-chain:before,
.fa-link:before {
  content: "\f0c1";
}
.fa-cloud:before {
  content: "\f0c2";
}
.fa-flask:before {
  content: "\f0c3";
}
.fa-cut:before,
.fa-scissors:before {
  content: "\f0c4";
}
.fa-copy:before,
.fa-files-o:before {
  content: "\f0c5";
}
.fa-paperclip:before {
  content: "\f0c6";
}
.fa-save:before,
.fa-floppy-o:before {
  content: "\f0c7";
}
.fa-square:before {
  content: "\f0c8";
}
.fa-navicon:before,
.fa-reorder:before,
.fa-bars:before {
  content: "\f0c9";
}
.fa-list-ul:before {
  content: "\f0ca";
}
.fa-list-ol:before {
  content: "\f0cb";
}
.fa-strikethrough:before {
  content: "\f0cc";
}
.fa-underline:before {
  content: "\f0cd";
}
.fa-table:before {
  content: "\f0ce";
}
.fa-magic:before {
  content: "\f0d0";
}
.fa-truck:before {
  content: "\f0d1";
}
.fa-pinterest:before {
  content: "\f0d2";
}
.fa-pinterest-square:before {
  content: "\f0d3";
}
.fa-google-plus-square:before {
  content: "\f0d4";
}
.fa-google-plus:before {
  content: "\f0d5";
}
.fa-money:before {
  content: "\f0d6";
}
.fa-caret-down:before {
  content: "\f0d7";
}
.fa-caret-up:before {
  content: "\f0d8";
}
.fa-caret-left:before {
  content: "\f0d9";
}
.fa-caret-right:before {
  content: "\f0da";
}
.fa-columns:before {
  content: "\f0db";
}
.fa-unsorted:before,
.fa-sort:before {
  content: "\f0dc";
}
.fa-sort-down:before,
.fa-sort-desc:before {
  content: "\f0dd";
}
.fa-sort-up:before,
.fa-sort-asc:before {
  content: "\f0de";
}
.fa-envelope:before {
  content: "\f0e0";
}
.fa-linkedin:before {
  content: "\f0e1";
}
.fa-rotate-left:before,
.fa-undo:before {
  content: "\f0e2";
}
.fa-legal:before,
.fa-gavel:before {
  content: "\f0e3";
}
.fa-dashboard:before,
.fa-tachometer:before {
  content: "\f0e4";
}
.fa-comment-o:before {
  content: "\f0e5";
}
.fa-comments-o:before {
  content: "\f0e6";
}
.fa-flash:before,
.fa-bolt:before {
  content: "\f0e7";
}
.fa-sitemap:before {
  content: "\f0e8";
}
.fa-umbrella:before {
  content: "\f0e9";
}
.fa-paste:before,
.fa-clipboard:before {
  content: "\f0ea";
}
.fa-lightbulb-o:before {
  content: "\f0eb";
}
.fa-exchange:before {
  content: "\f0ec";
}
.fa-cloud-download:before {
  content: "\f0ed";
}
.fa-cloud-upload:before {
  content: "\f0ee";
}
.fa-user-md:before {
  content: "\f0f0";
}
.fa-stethoscope:before {
  content: "\f0f1";
}
.fa-suitcase:before {
  content: "\f0f2";
}
.fa-bell-o:before {
  content: "\f0a2";
}
.fa-coffee:before {
  content: "\f0f4";
}
.fa-cutlery:before {
  content: "\f0f5";
}
.fa-file-text-o:before {
  content: "\f0f6";
}
.fa-building-o:before {
  content: "\f0f7";
}
.fa-hospital-o:before {
  content: "\f0f8";
}
.fa-ambulance:before {
  content: "\f0f9";
}
.fa-medkit:before {
  content: "\f0fa";
}
.fa-fighter-jet:before {
  content: "\f0fb";
}
.fa-beer:before {
  content: "\f0fc";
}
.fa-h-square:before {
  content: "\f0fd";
}
.fa-plus-square:before {
  content: "\f0fe";
}
.fa-angle-double-left:before {
  content: "\f100";
}
.fa-angle-double-right:before {
  content: "\f101";
}
.fa-angle-double-up:before {
  content: "\f102";
}
.fa-angle-double-down:before {
  content: "\f103";
}
.fa-angle-left:before {
  content: "\f104";
}
.fa-angle-right:before {
  content: "\f105";
}
.fa-angle-up:before {
  content: "\f106";
}
.fa-angle-down:before {
  content: "\f107";
}
.fa-desktop:before {
  content: "\f108";
}
.fa-laptop:before {
  content: "\f109";
}
.fa-tablet:before {
  content: "\f10a";
}
.fa-mobile-phone:before,
.fa-mobile:before {
  content: "\f10b";
}
.fa-circle-o:before {
  content: "\f10c";
}
.fa-quote-left:before {
  content: "\f10d";
}
.fa-quote-right:before {
  content: "\f10e";
}
.fa-spinner:before {
  content: "\f110";
}
.fa-circle:before {
  content: "\f111";
}
.fa-mail-reply:before,
.fa-reply:before {
  content: "\f112";
}
.fa-github-alt:before {
  content: "\f113";
}
.fa-folder-o:before {
  content: "\f114";
}
.fa-folder-open-o:before {
  content: "\f115";
}
.fa-smile-o:before {
  content: "\f118";
}
.fa-frown-o:before {
  content: "\f119";
}
.fa-meh-o:before {
  content: "\f11a";
}
.fa-gamepad:before {
  content: "\f11b";
}
.fa-keyboard-o:before {
  content: "\f11c";
}
.fa-flag-o:before {
  content: "\f11d";
}
.fa-flag-checkered:before {
  content: "\f11e";
}
.fa-terminal:before {
  content: "\f120";
}
.fa-code:before {
  content: "\f121";
}
.fa-mail-reply-all:before,
.fa-reply-all:before {
  content: "\f122";
}
.fa-star-half-empty:before,
.fa-star-half-full:before,
.fa-star-half-o:before {
  content: "\f123";
}
.fa-location-arrow:before {
  content: "\f124";
}
.fa-crop:before {
  content: "\f125";
}
.fa-code-fork:before {
  content: "\f126";
}
.fa-unlink:before,
.fa-chain-broken:before {
  content: "\f127";
}
.fa-question:before {
  content: "\f128";
}
.fa-info:before {
  content: "\f129";
}
.fa-exclamation:before {
  content: "\f12a";
}
.fa-superscript:before {
  content: "\f12b";
}
.fa-subscript:before {
  content: "\f12c";
}
.fa-eraser:before {
  content: "\f12d";
}
.fa-puzzle-piece:before {
  content: "\f12e";
}
.fa-microphone:before {
  content: "\f130";
}
.fa-microphone-slash:before {
  content: "\f131";
}
.fa-shield:before {
  content: "\f132";
}
.fa-calendar-o:before {
  content: "\f133";
}
.fa-fire-extinguisher:before {
  content: "\f134";
}
.fa-rocket:before {
  content: "\f135";
}
.fa-maxcdn:before {
  content: "\f136";
}
.fa-chevron-circle-left:before {
  content: "\f137";
}
.fa-chevron-circle-right:before {
  content: "\f138";
}
.fa-chevron-circle-up:before {
  content: "\f139";
}
.fa-chevron-circle-down:before {
  content: "\f13a";
}
.fa-html5:before {
  content: "\f13b";
}
.fa-css3:before {
  content: "\f13c";
}
.fa-anchor:before {
  content: "\f13d";
}
.fa-unlock-alt:before {
  content: "\f13e";
}
.fa-bullseye:before {
  content: "\f140";
}
.fa-ellipsis-h:before {
  content: "\f141";
}
.fa-ellipsis-v:before {
  content: "\f142";
}
.fa-rss-square:before {
  content: "\f143";
}
.fa-play-circle:before {
  content: "\f144";
}
.fa-ticket:before {
  content: "\f145";
}
.fa-minus-square:before {
  content: "\f146";
}
.fa-minus-square-o:before {
  content: "\f147";
}
.fa-level-up:before {
  content: "\f148";
}
.fa-level-down:before {
  content: "\f149";
}
.fa-check-square:before {
  content: "\f14a";
}
.fa-pencil-square:before {
  content: "\f14b";
}
.fa-external-link-square:before {
  content: "\f14c";
}
.fa-share-square:before {
  content: "\f14d";
}
.fa-compass:before {
  content: "\f14e";
}
.fa-toggle-down:before,
.fa-caret-square-o-down:before {
  content: "\f150";
}
.fa-toggle-up:before,
.fa-caret-square-o-up:before {
  content: "\f151";
}
.fa-toggle-right:before,
.fa-caret-square-o-right:before {
  content: "\f152";
}
.fa-euro:before,
.fa-eur:before {
  content: "\f153";
}
.fa-gbp:before {
  content: "\f154";
}
.fa-dollar:before,
.fa-usd:before {
  content: "\f155";
}
.fa-rupee:before,
.fa-inr:before {
  content: "\f156";
}
.fa-cny:before,
.fa-rmb:before,
.fa-yen:before,
.fa-jpy:before {
  content: "\f157";
}
.fa-ruble:before,
.fa-rouble:before,
.fa-rub:before {
  content: "\f158";
}
.fa-won:before,
.fa-krw:before {
  content: "\f159";
}
.fa-bitcoin:before,
.fa-btc:before {
  content: "\f15a";
}
.fa-file:before {
  content: "\f15b";
}
.fa-file-text:before {
  content: "\f15c";
}
.fa-sort-alpha-asc:before {
  content: "\f15d";
}
.fa-sort-alpha-desc:before {
  content: "\f15e";
}
.fa-sort-amount-asc:before {
  content: "\f160";
}
.fa-sort-amount-desc:before {
  content: "\f161";
}
.fa-sort-numeric-asc:before {
  content: "\f162";
}
.fa-sort-numeric-desc:before {
  content: "\f163";
}
.fa-thumbs-up:before {
  content: "\f164";
}
.fa-thumbs-down:before {
  content: "\f165";
}
.fa-youtube-square:before {
  content: "\f166";
}
.fa-youtube:before {
  content: "\f167";
}
.fa-xing:before {
  content: "\f168";
}
.fa-xing-square:before {
  content: "\f169";
}
.fa-youtube-play:before {
  content: "\f16a";
}
.fa-dropbox:before {
  content: "\f16b";
}
.fa-stack-overflow:before {
  content: "\f16c";
}
.fa-instagram:before {
  content: "\f16d";
}
.fa-flickr:before {
  content: "\f16e";
}
.fa-adn:before {
  content: "\f170";
}
.fa-bitbucket:before {
  content: "\f171";
}
.fa-bitbucket-square:before {
  content: "\f172";
}
.fa-tumblr:before {
  content: "\f173";
}
.fa-tumblr-square:before {
  content: "\f174";
}
.fa-long-arrow-down:before {
  content: "\f175";
}
.fa-long-arrow-up:before {
  content: "\f176";
}
.fa-long-arrow-left:before {
  content: "\f177";
}
.fa-long-arrow-right:before {
  content: "\f178";
}
.fa-apple:before {
  content: "\f179";
}
.fa-windows:before {
  content: "\f17a";
}
.fa-android:before {
  content: "\f17b";
}
.fa-linux:before {
  content: "\f17c";
}
.fa-dribbble:before {
  content: "\f17d";
}
.fa-skype:before {
  content: "\f17e";
}
.fa-foursquare:before {
  content: "\f180";
}
.fa-trello:before {
  content: "\f181";
}
.fa-female:before {
  content: "\f182";
}
.fa-male:before {
  content: "\f183";
}
.fa-gittip:before {
  content: "\f184";
}
.fa-sun-o:before {
  content: "\f185";
}
.fa-moon-o:before {
  content: "\f186";
}
.fa-archive:before {
  content: "\f187";
}
.fa-bug:before {
  content: "\f188";
}
.fa-vk:before {
  content: "\f189";
}
.fa-weibo:before {
  content: "\f18a";
}
.fa-renren:before {
  content: "\f18b";
}
.fa-pagelines:before {
  content: "\f18c";
}
.fa-stack-exchange:before {
  content: "\f18d";
}
.fa-arrow-circle-o-right:before {
  content: "\f18e";
}
.fa-arrow-circle-o-left:before {
  content: "\f190";
}
.fa-toggle-left:before,
.fa-caret-square-o-left:before {
  content: "\f191";
}
.fa-dot-circle-o:before {
  content: "\f192";
}
.fa-wheelchair:before {
  content: "\f193";
}
.fa-vimeo-square:before {
  content: "\f194";
}
.fa-turkish-lira:before,
.fa-try:before {
  content: "\f195";
}
.fa-plus-square-o:before {
  content: "\f196";
}
.fa-space-shuttle:before {
  content: "\f197";
}
.fa-slack:before {
  content: "\f198";
}
.fa-envelope-square:before {
  content: "\f199";
}
.fa-wordpress:before {
  content: "\f19a";
}
.fa-openid:before {
  content: "\f19b";
}
.fa-institution:before,
.fa-bank:before,
.fa-university:before {
  content: "\f19c";
}
.fa-mortar-board:before,
.fa-graduation-cap:before {
  content: "\f19d";
}
.fa-yahoo:before {
  content: "\f19e";
}
.fa-google:before {
  content: "\f1a0";
}
.fa-reddit:before {
  content: "\f1a1";
}
.fa-reddit-square:before {
  content: "\f1a2";
}
.fa-stumbleupon-circle:before {
  content: "\f1a3";
}
.fa-stumbleupon:before {
  content: "\f1a4";
}
.fa-delicious:before {
  content: "\f1a5";
}
.fa-digg:before {
  content: "\f1a6";
}
.fa-pied-piper:before {
  content: "\f1a7";
}
.fa-pied-piper-alt:before {
  content: "\f1a8";
}
.fa-drupal:before {
  content: "\f1a9";
}
.fa-joomla:before {
  content: "\f1aa";
}
.fa-language:before {
  content: "\f1ab";
}
.fa-fax:before {
  content: "\f1ac";
}
.fa-building:before {
  content: "\f1ad";
}
.fa-child:before {
  content: "\f1ae";
}
.fa-paw:before {
  content: "\f1b0";
}
.fa-spoon:before {
  content: "\f1b1";
}
.fa-cube:before {
  content: "\f1b2";
}
.fa-cubes:before {
  content: "\f1b3";
}
.fa-behance:before {
  content: "\f1b4";
}
.fa-behance-square:before {
  content: "\f1b5";
}
.fa-steam:before {
  content: "\f1b6";
}
.fa-steam-square:before {
  content: "\f1b7";
}
.fa-recycle:before {
  content: "\f1b8";
}
.fa-automobile:before,
.fa-car:before {
  content: "\f1b9";
}
.fa-cab:before,
.fa-taxi:before {
  content: "\f1ba";
}
.fa-tree:before {
  content: "\f1bb";
}
.fa-spotify:before {
  content: "\f1bc";
}
.fa-deviantart:before {
  content: "\f1bd";
}
.fa-soundcloud:before {
  content: "\f1be";
}
.fa-database:before {
  content: "\f1c0";
}
.fa-file-pdf-o:before {
  content: "\f1c1";
}
.fa-file-word-o:before {
  content: "\f1c2";
}
.fa-file-excel-o:before {
  content: "\f1c3";
}
.fa-file-powerpoint-o:before {
  content: "\f1c4";
}
.fa-file-photo-o:before,
.fa-file-picture-o:before,
.fa-file-image-o:before {
  content: "\f1c5";
}
.fa-file-zip-o:before,
.fa-file-archive-o:before {
  content: "\f1c6";
}
.fa-file-sound-o:before,
.fa-file-audio-o:before {
  content: "\f1c7";
}
.fa-file-movie-o:before,
.fa-file-video-o:before {
  content: "\f1c8";
}
.fa-file-code-o:before {
  content: "\f1c9";
}
.fa-vine:before {
  content: "\f1ca";
}
.fa-codepen:before {
  content: "\f1cb";
}
.fa-jsfiddle:before {
  content: "\f1cc";
}
.fa-life-bouy:before,
.fa-life-buoy:before,
.fa-life-saver:before,
.fa-support:before,
.fa-life-ring:before {
  content: "\f1cd";
}
.fa-circle-o-notch:before {
  content: "\f1ce";
}
.fa-ra:before,
.fa-rebel:before {
  content: "\f1d0";
}
.fa-ge:before,
.fa-empire:before {
  content: "\f1d1";
}
.fa-git-square:before {
  content: "\f1d2";
}
.fa-git:before {
  content: "\f1d3";
}
.fa-hacker-news:before {
  content: "\f1d4";
}
.fa-tencent-weibo:before {
  content: "\f1d5";
}
.fa-qq:before {
  content: "\f1d6";
}
.fa-wechat:before,
.fa-weixin:before {
  content: "\f1d7";
}
.fa-send:before,
.fa-paper-plane:before {
  content: "\f1d8";
}
.fa-send-o:before,
.fa-paper-plane-o:before {
  content: "\f1d9";
}
.fa-history:before {
  content: "\f1da";
}
.fa-circle-thin:before {
  content: "\f1db";
}
.fa-header:before {
  content: "\f1dc";
}
.fa-paragraph:before {
  content: "\f1dd";
}
.fa-sliders:before {
  content: "\f1de";
}
.fa-share-alt:before {
  content: "\f1e0";
}
.fa-share-alt-square:before {
  content: "\f1e1";
}
.fa-bomb:before {
  content: "\f1e2";
}
.fa-soccer-ball-o:before,
.fa-futbol-o:before {
  content: "\f1e3";
}
.fa-tty:before {
  content: "\f1e4";
}
.fa-binoculars:before {
  content: "\f1e5";
}
.fa-plug:before {
  content: "\f1e6";
}
.fa-slideshare:before {
  content: "\f1e7";
}
.fa-twitch:before {
  content: "\f1e8";
}
.fa-yelp:before {
  content: "\f1e9";
}
.fa-newspaper-o:before {
  content: "\f1ea";
}
.fa-wifi:before {
  content: "\f1eb";
}
.fa-calculator:before {
  content: "\f1ec";
}
.fa-paypal:before {
  content: "\f1ed";
}
.fa-google-wallet:before {
  content: "\f1ee";
}
.fa-cc-visa:before {
  content: "\f1f0";
}
.fa-cc-mastercard:before {
  content: "\f1f1";
}
.fa-cc-discover:before {
  content: "\f1f2";
}
.fa-cc-amex:before {
  content: "\f1f3";
}
.fa-cc-paypal:before {
  content: "\f1f4";
}
.fa-cc-stripe:before {
  content: "\f1f5";
}
.fa-bell-slash:before {
  content: "\f1f6";
}
.fa-bell-slash-o:before {
  content: "\f1f7";
}
.fa-trash:before {
  content: "\f1f8";
}
.fa-copyright:before {
  content: "\f1f9";
}
.fa-at:before {
  content: "\f1fa";
}
.fa-eyedropper:before {
  content: "\f1fb";
}
.fa-paint-brush:before {
  content: "\f1fc";
}
.fa-birthday-cake:before {
  content: "\f1fd";
}
.fa-area-chart:before {
  content: "\f1fe";
}
.fa-pie-chart:before {
  content: "\f200";
}
.fa-line-chart:before {
  content: "\f201";
}
.fa-lastfm:before {
  content: "\f202";
}
.fa-lastfm-square:before {
  content: "\f203";
}
.fa-toggle-off:before {
  content: "\f204";
}
.fa-toggle-on:before {
  content: "\f205";
}
.fa-bicycle:before {
  content: "\f206";
}
.fa-bus:before {
  content: "\f207";
}
.fa-ioxhost:before {
  content: "\f208";
}
.fa-angellist:before {
  content: "\f209";
}
.fa-cc:before {
  content: "\f20a";
}
.fa-shekel:before,
.fa-sheqel:before,
.fa-ils:before {
  content: "\f20b";
}
.fa-meanpath:before {
  content: "\f20c";
}
/*!
*
* IPython base
*
*/
.modal.fade .modal-dialog {
  -webkit-transform: translate(0, 0);
  -ms-transform: translate(0, 0);
  -o-transform: translate(0, 0);
  transform: translate(0, 0);
}
code {
  color: #000;
}
pre {
  font-size: inherit;
  line-height: inherit;
}
label {
  font-weight: normal;
}
/* Make the page background atleast 100% the height of the view port */
/* Make the page itself atleast 70% the height of the view port */
.border-box-sizing {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.corner-all {
  border-radius: 2px;
}
.no-padding {
  padding: 0px;
}
/* Flexible box model classes */
/* Taken from Alex Russell http://infrequently.org/2009/08/css-3-progress/ */
/* This file is a compatability layer.  It allows the usage of flexible box 
model layouts accross multiple browsers, including older browsers.  The newest,
universal implementation of the flexible box model is used when available (see
`Modern browsers` comments below).  Browsers that are known to implement this 
new spec completely include:

    Firefox 28.0+
    Chrome 29.0+
    Internet Explorer 11+ 
    Opera 17.0+

Browsers not listed, including Safari, are supported via the styling under the
`Old browsers` comments below.
*/
.hbox {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
.hbox > * {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
}
.vbox {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
.vbox > * {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
}
.hbox.reverse,
.vbox.reverse,
.reverse {
  /* Old browsers */
  -webkit-box-direction: reverse;
  -moz-box-direction: reverse;
  box-direction: reverse;
  /* Modern browsers */
  flex-direction: row-reverse;
}
.hbox.box-flex0,
.vbox.box-flex0,
.box-flex0 {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
  width: auto;
}
.hbox.box-flex1,
.vbox.box-flex1,
.box-flex1 {
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
.hbox.box-flex,
.vbox.box-flex,
.box-flex {
  /* Old browsers */
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
.hbox.box-flex2,
.vbox.box-flex2,
.box-flex2 {
  /* Old browsers */
  -webkit-box-flex: 2;
  -moz-box-flex: 2;
  box-flex: 2;
  /* Modern browsers */
  flex: 2;
}
.box-group1 {
  /*  Deprecated */
  -webkit-box-flex-group: 1;
  -moz-box-flex-group: 1;
  box-flex-group: 1;
}
.box-group2 {
  /* Deprecated */
  -webkit-box-flex-group: 2;
  -moz-box-flex-group: 2;
  box-flex-group: 2;
}
.hbox.start,
.vbox.start,
.start {
  /* Old browsers */
  -webkit-box-pack: start;
  -moz-box-pack: start;
  box-pack: start;
  /* Modern browsers */
  justify-content: flex-start;
}
.hbox.end,
.vbox.end,
.end {
  /* Old browsers */
  -webkit-box-pack: end;
  -moz-box-pack: end;
  box-pack: end;
  /* Modern browsers */
  justify-content: flex-end;
}
.hbox.center,
.vbox.center,
.center {
  /* Old browsers */
  -webkit-box-pack: center;
  -moz-box-pack: center;
  box-pack: center;
  /* Modern browsers */
  justify-content: center;
}
.hbox.baseline,
.vbox.baseline,
.baseline {
  /* Old browsers */
  -webkit-box-pack: baseline;
  -moz-box-pack: baseline;
  box-pack: baseline;
  /* Modern browsers */
  justify-content: baseline;
}
.hbox.stretch,
.vbox.stretch,
.stretch {
  /* Old browsers */
  -webkit-box-pack: stretch;
  -moz-box-pack: stretch;
  box-pack: stretch;
  /* Modern browsers */
  justify-content: stretch;
}
.hbox.align-start,
.vbox.align-start,
.align-start {
  /* Old browsers */
  -webkit-box-align: start;
  -moz-box-align: start;
  box-align: start;
  /* Modern browsers */
  align-items: flex-start;
}
.hbox.align-end,
.vbox.align-end,
.align-end {
  /* Old browsers */
  -webkit-box-align: end;
  -moz-box-align: end;
  box-align: end;
  /* Modern browsers */
  align-items: flex-end;
}
.hbox.align-center,
.vbox.align-center,
.align-center {
  /* Old browsers */
  -webkit-box-align: center;
  -moz-box-align: center;
  box-align: center;
  /* Modern browsers */
  align-items: center;
}
.hbox.align-baseline,
.vbox.align-baseline,
.align-baseline {
  /* Old browsers */
  -webkit-box-align: baseline;
  -moz-box-align: baseline;
  box-align: baseline;
  /* Modern browsers */
  align-items: baseline;
}
.hbox.align-stretch,
.vbox.align-stretch,
.align-stretch {
  /* Old browsers */
  -webkit-box-align: stretch;
  -moz-box-align: stretch;
  box-align: stretch;
  /* Modern browsers */
  align-items: stretch;
}
div.error {
  margin: 2em;
  text-align: center;
}
div.error > h1 {
  font-size: 500%;
  line-height: normal;
}
div.error > p {
  font-size: 200%;
  line-height: normal;
}
div.traceback-wrapper {
  text-align: left;
  max-width: 800px;
  margin: auto;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
body {
  background-color: #fff;
  /* This makes sure that the body covers the entire window and needs to
       be in a different element than the display: box in wrapper below */
  position: absolute;
  left: 0px;
  right: 0px;
  top: 0px;
  bottom: 0px;
  overflow: visible;
}
body > #header {
  /* Initially hidden to prevent FLOUC */
  display: none;
  background-color: #fff;
  /* Display over codemirror */
  position: relative;
  z-index: 100;
}
body > #header #header-container {
  padding-bottom: 5px;
  padding-top: 5px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
body > #header .header-bar {
  width: 100%;
  height: 1px;
  background: #e7e7e7;
  margin-bottom: -1px;
}
@media print {
  body > #header {
    display: none !important;
  }
}
#header-spacer {
  width: 100%;
  visibility: hidden;
}
@media print {
  #header-spacer {
    display: none;
  }
}
#ipython_notebook {
  padding-left: 0px;
  padding-top: 1px;
  padding-bottom: 1px;
}
@media (max-width: 991px) {
  #ipython_notebook {
    margin-left: 10px;
  }
}
[dir="rtl"] #ipython_notebook {
  float: right !important;
}
#noscript {
  width: auto;
  padding-top: 16px;
  padding-bottom: 16px;
  text-align: center;
  font-size: 22px;
  color: red;
  font-weight: bold;
}
#ipython_notebook img {
  height: 28px;
}
#site {
  width: 100%;
  display: none;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  overflow: auto;
}
@media print {
  #site {
    height: auto !important;
  }
}
/* Smaller buttons */
.ui-button .ui-button-text {
  padding: 0.2em 0.8em;
  font-size: 77%;
}
input.ui-button {
  padding: 0.3em 0.9em;
}
span#login_widget {
  float: right;
}
span#login_widget > .button,
#logout {
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
span#login_widget > .button:focus,
#logout:focus,
span#login_widget > .button.focus,
#logout.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
span#login_widget > .button:hover,
#logout:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
span#login_widget > .button:active,
#logout:active,
span#login_widget > .button.active,
#logout.active,
.open > .dropdown-togglespan#login_widget > .button,
.open > .dropdown-toggle#logout {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
span#login_widget > .button:active:hover,
#logout:active:hover,
span#login_widget > .button.active:hover,
#logout.active:hover,
.open > .dropdown-togglespan#login_widget > .button:hover,
.open > .dropdown-toggle#logout:hover,
span#login_widget > .button:active:focus,
#logout:active:focus,
span#login_widget > .button.active:focus,
#logout.active:focus,
.open > .dropdown-togglespan#login_widget > .button:focus,
.open > .dropdown-toggle#logout:focus,
span#login_widget > .button:active.focus,
#logout:active.focus,
span#login_widget > .button.active.focus,
#logout.active.focus,
.open > .dropdown-togglespan#login_widget > .button.focus,
.open > .dropdown-toggle#logout.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
span#login_widget > .button:active,
#logout:active,
span#login_widget > .button.active,
#logout.active,
.open > .dropdown-togglespan#login_widget > .button,
.open > .dropdown-toggle#logout {
  background-image: none;
}
span#login_widget > .button.disabled:hover,
#logout.disabled:hover,
span#login_widget > .button[disabled]:hover,
#logout[disabled]:hover,
fieldset[disabled] span#login_widget > .button:hover,
fieldset[disabled] #logout:hover,
span#login_widget > .button.disabled:focus,
#logout.disabled:focus,
span#login_widget > .button[disabled]:focus,
#logout[disabled]:focus,
fieldset[disabled] span#login_widget > .button:focus,
fieldset[disabled] #logout:focus,
span#login_widget > .button.disabled.focus,
#logout.disabled.focus,
span#login_widget > .button[disabled].focus,
#logout[disabled].focus,
fieldset[disabled] span#login_widget > .button.focus,
fieldset[disabled] #logout.focus {
  background-color: #fff;
  border-color: #ccc;
}
span#login_widget > .button .badge,
#logout .badge {
  color: #fff;
  background-color: #333;
}
.nav-header {
  text-transform: none;
}
#header > span {
  margin-top: 10px;
}
.modal_stretch .modal-dialog {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  min-height: 80vh;
}
.modal_stretch .modal-dialog .modal-body {
  max-height: calc(100vh - 200px);
  overflow: auto;
  flex: 1;
}
@media (min-width: 768px) {
  .modal .modal-dialog {
    width: 700px;
  }
}
@media (min-width: 768px) {
  select.form-control {
    margin-left: 12px;
    margin-right: 12px;
  }
}
/*!
*
* IPython auth
*
*/
.center-nav {
  display: inline-block;
  margin-bottom: -4px;
}
/*!
*
* IPython tree view
*
*/
/* We need an invisible input field on top of the sentense*/
/* "Drag file onto the list ..." */
.alternate_upload {
  background-color: none;
  display: inline;
}
.alternate_upload.form {
  padding: 0;
  margin: 0;
}
.alternate_upload input.fileinput {
  text-align: center;
  vertical-align: middle;
  display: inline;
  opacity: 0;
  z-index: 2;
  width: 12ex;
  margin-right: -12ex;
}
.alternate_upload .btn-upload {
  height: 22px;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
[dir="rtl"] #tabs li {
  float: right;
}
ul#tabs {
  margin-bottom: 4px;
}
[dir="rtl"] ul#tabs {
  margin-right: 0px;
}
ul#tabs a {
  padding-top: 6px;
  padding-bottom: 4px;
}
ul.breadcrumb a:focus,
ul.breadcrumb a:hover {
  text-decoration: none;
}
ul.breadcrumb i.icon-home {
  font-size: 16px;
  margin-right: 4px;
}
ul.breadcrumb span {
  color: #5e5e5e;
}
.list_toolbar {
  padding: 4px 0 4px 0;
  vertical-align: middle;
}
.list_toolbar .tree-buttons {
  padding-top: 1px;
}
[dir="rtl"] .list_toolbar .tree-buttons {
  float: left !important;
}
[dir="rtl"] .list_toolbar .pull-right {
  padding-top: 1px;
  float: left !important;
}
[dir="rtl"] .list_toolbar .pull-left {
  float: right !important;
}
.dynamic-buttons {
  padding-top: 3px;
  display: inline-block;
}
.list_toolbar [class*="span"] {
  min-height: 24px;
}
.list_header {
  font-weight: bold;
  background-color: #EEE;
}
.list_placeholder {
  font-weight: bold;
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
}
.list_container {
  margin-top: 4px;
  margin-bottom: 20px;
  border: 1px solid #ddd;
  border-radius: 2px;
}
.list_container > div {
  border-bottom: 1px solid #ddd;
}
.list_container > div:hover .list-item {
  background-color: red;
}
.list_container > div:last-child {
  border: none;
}
.list_item:hover .list_item {
  background-color: #ddd;
}
.list_item a {
  text-decoration: none;
}
.list_item:hover {
  background-color: #fafafa;
}
.list_header > div,
.list_item > div {
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
  line-height: 22px;
}
.list_header > div input,
.list_item > div input {
  margin-right: 7px;
  margin-left: 14px;
  vertical-align: baseline;
  line-height: 22px;
  position: relative;
  top: -1px;
}
.list_header > div .item_link,
.list_item > div .item_link {
  margin-left: -1px;
  vertical-align: baseline;
  line-height: 22px;
}
.new-file input[type=checkbox] {
  visibility: hidden;
}
.item_name {
  line-height: 22px;
  height: 24px;
}
.item_icon {
  font-size: 14px;
  color: #5e5e5e;
  margin-right: 7px;
  margin-left: 7px;
  line-height: 22px;
  vertical-align: baseline;
}
.item_buttons {
  line-height: 1em;
  margin-left: -5px;
}
.item_buttons .btn,
.item_buttons .btn-group,
.item_buttons .input-group {
  float: left;
}
.item_buttons > .btn,
.item_buttons > .btn-group,
.item_buttons > .input-group {
  margin-left: 5px;
}
.item_buttons .btn {
  min-width: 13ex;
}
.item_buttons .running-indicator {
  padding-top: 4px;
  color: #5cb85c;
}
.item_buttons .kernel-name {
  padding-top: 4px;
  color: #5bc0de;
  margin-right: 7px;
  float: left;
}
.toolbar_info {
  height: 24px;
  line-height: 24px;
}
.list_item input:not([type=checkbox]) {
  padding-top: 3px;
  padding-bottom: 3px;
  height: 22px;
  line-height: 14px;
  margin: 0px;
}
.highlight_text {
  color: blue;
}
#project_name {
  display: inline-block;
  padding-left: 7px;
  margin-left: -2px;
}
#project_name > .breadcrumb {
  padding: 0px;
  margin-bottom: 0px;
  background-color: transparent;
  font-weight: bold;
}
#tree-selector {
  padding-right: 0px;
}
[dir="rtl"] #tree-selector a {
  float: right;
}
#button-select-all {
  min-width: 50px;
}
#select-all {
  margin-left: 7px;
  margin-right: 2px;
}
.menu_icon {
  margin-right: 2px;
}
.tab-content .row {
  margin-left: 0px;
  margin-right: 0px;
}
.folder_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f114";
}
.folder_icon:before.pull-left {
  margin-right: .3em;
}
.folder_icon:before.pull-right {
  margin-left: .3em;
}
.notebook_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f02d";
  position: relative;
  top: -1px;
}
.notebook_icon:before.pull-left {
  margin-right: .3em;
}
.notebook_icon:before.pull-right {
  margin-left: .3em;
}
.running_notebook_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f02d";
  position: relative;
  top: -1px;
  color: #5cb85c;
}
.running_notebook_icon:before.pull-left {
  margin-right: .3em;
}
.running_notebook_icon:before.pull-right {
  margin-left: .3em;
}
.file_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f016";
  position: relative;
  top: -2px;
}
.file_icon:before.pull-left {
  margin-right: .3em;
}
.file_icon:before.pull-right {
  margin-left: .3em;
}
#notebook_toolbar .pull-right {
  padding-top: 0px;
  margin-right: -1px;
}
ul#new-menu {
  left: auto;
  right: 0;
}
[dir="rtl"] #new-menu {
  text-align: right;
}
.kernel-menu-icon {
  padding-right: 12px;
  width: 24px;
  content: "\f096";
}
.kernel-menu-icon:before {
  content: "\f096";
}
.kernel-menu-icon-current:before {
  content: "\f00c";
}
#tab_content {
  padding-top: 20px;
}
#running .panel-group .panel {
  margin-top: 3px;
  margin-bottom: 1em;
}
#running .panel-group .panel .panel-heading {
  background-color: #EEE;
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
  line-height: 22px;
}
#running .panel-group .panel .panel-heading a:focus,
#running .panel-group .panel .panel-heading a:hover {
  text-decoration: none;
}
#running .panel-group .panel .panel-body {
  padding: 0px;
}
#running .panel-group .panel .panel-body .list_container {
  margin-top: 0px;
  margin-bottom: 0px;
  border: 0px;
  border-radius: 0px;
}
#running .panel-group .panel .panel-body .list_container .list_item {
  border-bottom: 1px solid #ddd;
}
#running .panel-group .panel .panel-body .list_container .list_item:last-child {
  border-bottom: 0px;
}
[dir="rtl"] #running .col-sm-8 {
  float: right !important;
}
.delete-button {
  display: none;
}
.duplicate-button {
  display: none;
}
.rename-button {
  display: none;
}
.shutdown-button {
  display: none;
}
.dynamic-instructions {
  display: inline-block;
  padding-top: 4px;
}
/*!
*
* IPython text editor webapp
*
*/
.selected-keymap i.fa {
  padding: 0px 5px;
}
.selected-keymap i.fa:before {
  content: "\f00c";
}
#mode-menu {
  overflow: auto;
  max-height: 20em;
}
.edit_app #header {
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
.edit_app #menubar .navbar {
  /* Use a negative 1 bottom margin, so the border overlaps the border of the
    header */
  margin-bottom: -1px;
}
.dirty-indicator {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator.pull-left {
  margin-right: .3em;
}
.dirty-indicator.pull-right {
  margin-left: .3em;
}
.dirty-indicator-dirty {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator-dirty.pull-left {
  margin-right: .3em;
}
.dirty-indicator-dirty.pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator-clean.pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean.pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f00c";
}
.dirty-indicator-clean:before.pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean:before.pull-right {
  margin-left: .3em;
}
#filename {
  font-size: 16pt;
  display: table;
  padding: 0px 5px;
}
#current-mode {
  padding-left: 5px;
  padding-right: 5px;
}
#texteditor-backdrop {
  padding-top: 20px;
  padding-bottom: 20px;
}
@media not print {
  #texteditor-backdrop {
    background-color: #EEE;
  }
}
@media print {
  #texteditor-backdrop #texteditor-container .CodeMirror-gutter,
  #texteditor-backdrop #texteditor-container .CodeMirror-gutters {
    background-color: #fff;
  }
}
@media not print {
  #texteditor-backdrop #texteditor-container .CodeMirror-gutter,
  #texteditor-backdrop #texteditor-container .CodeMirror-gutters {
    background-color: #fff;
  }
}
@media not print {
  #texteditor-backdrop #texteditor-container {
    padding: 0px;
    background-color: #fff;
    -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
    box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  }
}
/*!
*
* IPython notebook
*
*/
/* CSS font colors for translated ANSI colors. */
.ansibold {
  font-weight: bold;
}
/* use dark versions for foreground, to improve visibility */
.ansiblack {
  color: black;
}
.ansired {
  color: darkred;
}
.ansigreen {
  color: darkgreen;
}
.ansiyellow {
  color: #c4a000;
}
.ansiblue {
  color: darkblue;
}
.ansipurple {
  color: darkviolet;
}
.ansicyan {
  color: steelblue;
}
.ansigray {
  color: gray;
}
/* and light for background, for the same reason */
.ansibgblack {
  background-color: black;
}
.ansibgred {
  background-color: red;
}
.ansibggreen {
  background-color: green;
}
.ansibgyellow {
  background-color: yellow;
}
.ansibgblue {
  background-color: blue;
}
.ansibgpurple {
  background-color: magenta;
}
.ansibgcyan {
  background-color: cyan;
}
.ansibggray {
  background-color: gray;
}
div.cell {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  border-radius: 2px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  border-width: 1px;
  border-style: solid;
  border-color: transparent;
  width: 100%;
  padding: 5px;
  /* This acts as a spacer between cells, that is outside the border */
  margin: 0px;
  outline: none;
  border-left-width: 1px;
  padding-left: 5px;
  background: linear-gradient(to right, transparent -40px, transparent 1px, transparent 1px, transparent 100%);
}
div.cell.jupyter-soft-selected {
  border-left-color: #90CAF9;
  border-left-color: #E3F2FD;
  border-left-width: 1px;
  padding-left: 5px;
  border-right-color: #E3F2FD;
  border-right-width: 1px;
  background: #E3F2FD;
}
@media print {
  div.cell.jupyter-soft-selected {
    border-color: transparent;
  }
}
div.cell.selected {
  border-color: #ababab;
  border-left-width: 0px;
  padding-left: 6px;
  background: linear-gradient(to right, #42A5F5 -40px, #42A5F5 5px, transparent 5px, transparent 100%);
}
@media print {
  div.cell.selected {
    border-color: transparent;
  }
}
div.cell.selected.jupyter-soft-selected {
  border-left-width: 0;
  padding-left: 6px;
  background: linear-gradient(to right, #42A5F5 -40px, #42A5F5 7px, #E3F2FD 7px, #E3F2FD 100%);
}
.edit_mode div.cell.selected {
  border-color: #66BB6A;
  border-left-width: 0px;
  padding-left: 6px;
  background: linear-gradient(to right, #66BB6A -40px, #66BB6A 5px, transparent 5px, transparent 100%);
}
@media print {
  .edit_mode div.cell.selected {
    border-color: transparent;
  }
}
.prompt {
  /* This needs to be wide enough for 3 digit prompt numbers: In[100]: */
  min-width: 14ex;
  /* This padding is tuned to match the padding on the CodeMirror editor. */
  padding: 0.4em;
  margin: 0px;
  font-family: monospace;
  text-align: right;
  /* This has to match that of the the CodeMirror class line-height below */
  line-height: 1.21429em;
  /* Don't highlight prompt number selection */
  -webkit-touch-callout: none;
  -webkit-user-select: none;
  -khtml-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
  /* Use default cursor */
  cursor: default;
}
@media (max-width: 540px) {
  .prompt {
    text-align: left;
  }
}
div.inner_cell {
  min-width: 0;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
/* input_area and input_prompt must match in top border and margin for alignment */
div.input_area {
  border: 1px solid #cfcfcf;
  border-radius: 2px;
  background: #f7f7f7;
  line-height: 1.21429em;
}
/* This is needed so that empty prompt areas can collapse to zero height when there
   is no content in the output_subarea and the prompt. The main purpose of this is
   to make sure that empty JavaScript output_subareas have no height. */
div.prompt:empty {
  padding-top: 0;
  padding-bottom: 0;
}
div.unrecognized_cell {
  padding: 5px 5px 5px 0px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
div.unrecognized_cell .inner_cell {
  border-radius: 2px;
  padding: 5px;
  font-weight: bold;
  color: red;
  border: 1px solid #cfcfcf;
  background: #eaeaea;
}
div.unrecognized_cell .inner_cell a {
  color: inherit;
  text-decoration: none;
}
div.unrecognized_cell .inner_cell a:hover {
  color: inherit;
  text-decoration: none;
}
@media (max-width: 540px) {
  div.unrecognized_cell > div.prompt {
    display: none;
  }
}
div.code_cell {
  /* avoid page breaking on code cells when printing */
}
@media print {
  div.code_cell {
    page-break-inside: avoid;
  }
}
/* any special styling for code cells that are currently running goes here */
div.input {
  page-break-inside: avoid;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.input {
    /* Old browsers */
    display: -webkit-box;
    -webkit-box-orient: vertical;
    -webkit-box-align: stretch;
    display: -moz-box;
    -moz-box-orient: vertical;
    -moz-box-align: stretch;
    display: box;
    box-orient: vertical;
    box-align: stretch;
    /* Modern browsers */
    display: flex;
    flex-direction: column;
    align-items: stretch;
  }
}
/* input_area and input_prompt must match in top border and margin for alignment */
div.input_prompt {
  color: #303F9F;
  border-top: 1px solid transparent;
}
div.input_area > div.highlight {
  margin: 0.4em;
  border: none;
  padding: 0px;
  background-color: transparent;
}
div.input_area > div.highlight > pre {
  margin: 0px;
  border: none;
  padding: 0px;
  background-color: transparent;
}
/* The following gets added to the <head> if it is detected that the user has a
 * monospace font with inconsistent normal/bold/italic height.  See
 * notebookmain.js.  Such fonts will have keywords vertically offset with
 * respect to the rest of the text.  The user should select a better font.
 * See: https://github.com/ipython/ipython/issues/1503
 *
 * .CodeMirror span {
 *      vertical-align: bottom;
 * }
 */
.CodeMirror {
  line-height: 1.21429em;
  /* Changed from 1em to our global default */
  font-size: 14px;
  height: auto;
  /* Changed to auto to autogrow */
  background: none;
  /* Changed from white to allow our bg to show through */
}
.CodeMirror-scroll {
  /*  The CodeMirror docs are a bit fuzzy on if overflow-y should be hidden or visible.*/
  /*  We have found that if it is visible, vertical scrollbars appear with font size changes.*/
  overflow-y: hidden;
  overflow-x: auto;
}
.CodeMirror-lines {
  /* In CM2, this used to be 0.4em, but in CM3 it went to 4px. We need the em value because */
  /* we have set a different line-height and want this to scale with that. */
  padding: 0.4em;
}
.CodeMirror-linenumber {
  padding: 0 8px 0 4px;
}
.CodeMirror-gutters {
  border-bottom-left-radius: 2px;
  border-top-left-radius: 2px;
}
.CodeMirror pre {
  /* In CM3 this went to 4px from 0 in CM2. We need the 0 value because of how we size */
  /* .CodeMirror-lines */
  padding: 0;
  border: 0;
  border-radius: 0;
}
/*

Original style from softwaremaniacs.org (c) Ivan Sagalaev <Maniac@SoftwareManiacs.Org>
Adapted from GitHub theme

*/
.highlight-base {
  color: #000;
}
.highlight-variable {
  color: #000;
}
.highlight-variable-2 {
  color: #1a1a1a;
}
.highlight-variable-3 {
  color: #333333;
}
.highlight-string {
  color: #BA2121;
}
.highlight-comment {
  color: #408080;
  font-style: italic;
}
.highlight-number {
  color: #080;
}
.highlight-atom {
  color: #88F;
}
.highlight-keyword {
  color: #008000;
  font-weight: bold;
}
.highlight-builtin {
  color: #008000;
}
.highlight-error {
  color: #f00;
}
.highlight-operator {
  color: #AA22FF;
  font-weight: bold;
}
.highlight-meta {
  color: #AA22FF;
}
/* previously not defined, copying from default codemirror */
.highlight-def {
  color: #00f;
}
.highlight-string-2 {
  color: #f50;
}
.highlight-qualifier {
  color: #555;
}
.highlight-bracket {
  color: #997;
}
.highlight-tag {
  color: #170;
}
.highlight-attribute {
  color: #00c;
}
.highlight-header {
  color: blue;
}
.highlight-quote {
  color: #090;
}
.highlight-link {
  color: #00c;
}
/* apply the same style to codemirror */
.cm-s-ipython span.cm-keyword {
  color: #008000;
  font-weight: bold;
}
.cm-s-ipython span.cm-atom {
  color: #88F;
}
.cm-s-ipython span.cm-number {
  color: #080;
}
.cm-s-ipython span.cm-def {
  color: #00f;
}
.cm-s-ipython span.cm-variable {
  color: #000;
}
.cm-s-ipython span.cm-operator {
  color: #AA22FF;
  font-weight: bold;
}
.cm-s-ipython span.cm-variable-2 {
  color: #1a1a1a;
}
.cm-s-ipython span.cm-variable-3 {
  color: #333333;
}
.cm-s-ipython span.cm-comment {
  color: #408080;
  font-style: italic;
}
.cm-s-ipython span.cm-string {
  color: #BA2121;
}
.cm-s-ipython span.cm-string-2 {
  color: #f50;
}
.cm-s-ipython span.cm-meta {
  color: #AA22FF;
}
.cm-s-ipython span.cm-qualifier {
  color: #555;
}
.cm-s-ipython span.cm-builtin {
  color: #008000;
}
.cm-s-ipython span.cm-bracket {
  color: #997;
}
.cm-s-ipython span.cm-tag {
  color: #170;
}
.cm-s-ipython span.cm-attribute {
  color: #00c;
}
.cm-s-ipython span.cm-header {
  color: blue;
}
.cm-s-ipython span.cm-quote {
  color: #090;
}
.cm-s-ipython span.cm-link {
  color: #00c;
}
.cm-s-ipython span.cm-error {
  color: #f00;
}
.cm-s-ipython span.cm-tab {
  background: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAADAAAAAMCAYAAAAkuj5RAAAAAXNSR0IArs4c6QAAAGFJREFUSMft1LsRQFAQheHPowAKoACx3IgEKtaEHujDjORSgWTH/ZOdnZOcM/sgk/kFFWY0qV8foQwS4MKBCS3qR6ixBJvElOobYAtivseIE120FaowJPN75GMu8j/LfMwNjh4HUpwg4LUAAAAASUVORK5CYII=);
  background-position: right;
  background-repeat: no-repeat;
}
div.output_wrapper {
  /* this position must be relative to enable descendents to be absolute within it */
  position: relative;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  z-index: 1;
}
/* class for the output area when it should be height-limited */
div.output_scroll {
  /* ideally, this would be max-height, but FF barfs all over that */
  height: 24em;
  /* FF needs this *and the wrapper* to specify full width, or it will shrinkwrap */
  width: 100%;
  overflow: auto;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
  box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
  display: block;
}
/* output div while it is collapsed */
div.output_collapsed {
  margin: 0px;
  padding: 0px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
div.out_prompt_overlay {
  height: 100%;
  padding: 0px 0.4em;
  position: absolute;
  border-radius: 2px;
}
div.out_prompt_overlay:hover {
  /* use inner shadow to get border that is computed the same on WebKit/FF */
  -webkit-box-shadow: inset 0 0 1px #000;
  box-shadow: inset 0 0 1px #000;
  background: rgba(240, 240, 240, 0.5);
}
div.output_prompt {
  color: #D84315;
}
/* This class is the outer container of all output sections. */
div.output_area {
  padding: 0px;
  page-break-inside: avoid;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
div.output_area .MathJax_Display {
  text-align: left !important;
}
div.output_area .rendered_html table {
  margin-left: 0;
  margin-right: 0;
}
div.output_area .rendered_html img {
  margin-left: 0;
  margin-right: 0;
}
div.output_area img,
div.output_area svg {
  max-width: 100%;
  height: auto;
}
div.output_area img.unconfined,
div.output_area svg.unconfined {
  max-width: none;
}
/* This is needed to protect the pre formating from global settings such
   as that of bootstrap */
.output {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.output_area {
    /* Old browsers */
    display: -webkit-box;
    -webkit-box-orient: vertical;
    -webkit-box-align: stretch;
    display: -moz-box;
    -moz-box-orient: vertical;
    -moz-box-align: stretch;
    display: box;
    box-orient: vertical;
    box-align: stretch;
    /* Modern browsers */
    display: flex;
    flex-direction: column;
    align-items: stretch;
  }
}
div.output_area pre {
  margin: 0;
  padding: 0;
  border: 0;
  vertical-align: baseline;
  color: black;
  background-color: transparent;
  border-radius: 0;
}
/* This class is for the output subarea inside the output_area and after
   the prompt div. */
div.output_subarea {
  overflow-x: auto;
  padding: 0.4em;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
  max-width: calc(100% - 14ex);
}
div.output_scroll div.output_subarea {
  overflow-x: visible;
}
/* The rest of the output_* classes are for special styling of the different
   output types */
/* all text output has this class: */
div.output_text {
  text-align: left;
  color: #000;
  /* This has to match that of the the CodeMirror class line-height below */
  line-height: 1.21429em;
}
/* stdout/stderr are 'text' as well as 'stream', but execute_result/error are *not* streams */
div.output_stderr {
  background: #fdd;
  /* very light red background for stderr */
}
div.output_latex {
  text-align: left;
}
/* Empty output_javascript divs should have no height */
div.output_javascript:empty {
  padding: 0;
}
.js-error {
  color: darkred;
}
/* raw_input styles */
div.raw_input_container {
  line-height: 1.21429em;
  padding-top: 5px;
}
pre.raw_input_prompt {
  /* nothing needed here. */
}
input.raw_input {
  font-family: monospace;
  font-size: inherit;
  color: inherit;
  width: auto;
  /* make sure input baseline aligns with prompt */
  vertical-align: baseline;
  /* padding + margin = 0.5em between prompt and cursor */
  padding: 0em 0.25em;
  margin: 0em 0.25em;
}
input.raw_input:focus {
  box-shadow: none;
}
p.p-space {
  margin-bottom: 10px;
}
div.output_unrecognized {
  padding: 5px;
  font-weight: bold;
  color: red;
}
div.output_unrecognized a {
  color: inherit;
  text-decoration: none;
}
div.output_unrecognized a:hover {
  color: inherit;
  text-decoration: none;
}
.rendered_html {
  color: #000;
  /* any extras will just be numbers: */
}
.rendered_html em {
  font-style: italic;
}
.rendered_html strong {
  font-weight: bold;
}
.rendered_html u {
  text-decoration: underline;
}
.rendered_html :link {
  text-decoration: underline;
}
.rendered_html :visited {
  text-decoration: underline;
}
.rendered_html h1 {
  font-size: 185.7%;
  margin: 1.08em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h2 {
  font-size: 157.1%;
  margin: 1.27em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h3 {
  font-size: 128.6%;
  margin: 1.55em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h4 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h5 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
  font-style: italic;
}
.rendered_html h6 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
  font-style: italic;
}
.rendered_html h1:first-child {
  margin-top: 0.538em;
}
.rendered_html h2:first-child {
  margin-top: 0.636em;
}
.rendered_html h3:first-child {
  margin-top: 0.777em;
}
.rendered_html h4:first-child {
  margin-top: 1em;
}
.rendered_html h5:first-child {
  margin-top: 1em;
}
.rendered_html h6:first-child {
  margin-top: 1em;
}
.rendered_html ul {
  list-style: disc;
  margin: 0em 2em;
  padding-left: 0px;
}
.rendered_html ul ul {
  list-style: square;
  margin: 0em 2em;
}
.rendered_html ul ul ul {
  list-style: circle;
  margin: 0em 2em;
}
.rendered_html ol {
  list-style: decimal;
  margin: 0em 2em;
  padding-left: 0px;
}
.rendered_html ol ol {
  list-style: upper-alpha;
  margin: 0em 2em;
}
.rendered_html ol ol ol {
  list-style: lower-alpha;
  margin: 0em 2em;
}
.rendered_html ol ol ol ol {
  list-style: lower-roman;
  margin: 0em 2em;
}
.rendered_html ol ol ol ol ol {
  list-style: decimal;
  margin: 0em 2em;
}
.rendered_html * + ul {
  margin-top: 1em;
}
.rendered_html * + ol {
  margin-top: 1em;
}
.rendered_html hr {
  color: black;
  background-color: black;
}
.rendered_html pre {
  margin: 1em 2em;
}
.rendered_html pre,
.rendered_html code {
  border: 0;
  background-color: #fff;
  color: #000;
  font-size: 100%;
  padding: 0px;
}
.rendered_html blockquote {
  margin: 1em 2em;
}
.rendered_html table {
  margin-left: auto;
  margin-right: auto;
  border: 1px solid black;
  border-collapse: collapse;
}
.rendered_html tr,
.rendered_html th,
.rendered_html td {
  border: 1px solid black;
  border-collapse: collapse;
  margin: 1em 2em;
}
.rendered_html td,
.rendered_html th {
  text-align: left;
  vertical-align: middle;
  padding: 4px;
}
.rendered_html th {
  font-weight: bold;
}
.rendered_html * + table {
  margin-top: 1em;
}
.rendered_html p {
  text-align: left;
}
.rendered_html * + p {
  margin-top: 1em;
}
.rendered_html img {
  display: block;
  margin-left: auto;
  margin-right: auto;
}
.rendered_html * + img {
  margin-top: 1em;
}
.rendered_html img,
.rendered_html svg {
  max-width: 100%;
  height: auto;
}
.rendered_html img.unconfined,
.rendered_html svg.unconfined {
  max-width: none;
}
div.text_cell {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.text_cell > div.prompt {
    display: none;
  }
}
div.text_cell_render {
  /*font-family: "Helvetica Neue", Arial, Helvetica, Geneva, sans-serif;*/
  outline: none;
  resize: none;
  width: inherit;
  border-style: none;
  padding: 0.5em 0.5em 0.5em 0.4em;
  color: #000;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
a.anchor-link:link {
  text-decoration: none;
  padding: 0px 20px;
  visibility: hidden;
}
h1:hover .anchor-link,
h2:hover .anchor-link,
h3:hover .anchor-link,
h4:hover .anchor-link,
h5:hover .anchor-link,
h6:hover .anchor-link {
  visibility: visible;
}
.text_cell.rendered .input_area {
  display: none;
}
.text_cell.rendered .rendered_html {
  overflow-x: auto;
  overflow-y: hidden;
}
.text_cell.unrendered .text_cell_render {
  display: none;
}
.cm-header-1,
.cm-header-2,
.cm-header-3,
.cm-header-4,
.cm-header-5,
.cm-header-6 {
  font-weight: bold;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
}
.cm-header-1 {
  font-size: 185.7%;
}
.cm-header-2 {
  font-size: 157.1%;
}
.cm-header-3 {
  font-size: 128.6%;
}
.cm-header-4 {
  font-size: 110%;
}
.cm-header-5 {
  font-size: 100%;
  font-style: italic;
}
.cm-header-6 {
  font-size: 100%;
  font-style: italic;
}
/*!
*
* IPython notebook webapp
*
*/
@media (max-width: 767px) {
  .notebook_app {
    padding-left: 0px;
    padding-right: 0px;
  }
}
#ipython-main-app {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  height: 100%;
}
div#notebook_panel {
  margin: 0px;
  padding: 0px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  height: 100%;
}
div#notebook {
  font-size: 14px;
  line-height: 20px;
  overflow-y: hidden;
  overflow-x: auto;
  width: 100%;
  /* This spaces the page away from the edge of the notebook area */
  padding-top: 20px;
  margin: 0px;
  outline: none;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  min-height: 100%;
}
@media not print {
  #notebook-container {
    padding: 15px;
    background-color: #fff;
    min-height: 0;
    -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
    box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  }
}
@media print {
  #notebook-container {
    width: 100%;
  }
}
div.ui-widget-content {
  border: 1px solid #ababab;
  outline: none;
}
pre.dialog {
  background-color: #f7f7f7;
  border: 1px solid #ddd;
  border-radius: 2px;
  padding: 0.4em;
  padding-left: 2em;
}
p.dialog {
  padding: 0.2em;
}
/* Word-wrap output correctly.  This is the CSS3 spelling, though Firefox seems
   to not honor it correctly.  Webkit browsers (Chrome, rekonq, Safari) do.
 */
pre,
code,
kbd,
samp {
  white-space: pre-wrap;
}
#fonttest {
  font-family: monospace;
}
p {
  margin-bottom: 0;
}
.end_space {
  min-height: 100px;
  transition: height .2s ease;
}
.notebook_app > #header {
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
@media not print {
  .notebook_app {
    background-color: #EEE;
  }
}
kbd {
  border-style: solid;
  border-width: 1px;
  box-shadow: none;
  margin: 2px;
  padding-left: 2px;
  padding-right: 2px;
  padding-top: 1px;
  padding-bottom: 1px;
}
/* CSS for the cell toolbar */
.celltoolbar {
  border: thin solid #CFCFCF;
  border-bottom: none;
  background: #EEE;
  border-radius: 2px 2px 0px 0px;
  width: 100%;
  height: 29px;
  padding-right: 4px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  /* Old browsers */
  -webkit-box-pack: end;
  -moz-box-pack: end;
  box-pack: end;
  /* Modern browsers */
  justify-content: flex-end;
  display: -webkit-flex;
}
@media print {
  .celltoolbar {
    display: none;
  }
}
.ctb_hideshow {
  display: none;
  vertical-align: bottom;
}
/* ctb_show is added to the ctb_hideshow div to show the cell toolbar.
   Cell toolbars are only shown when the ctb_global_show class is also set.
*/
.ctb_global_show .ctb_show.ctb_hideshow {
  display: block;
}
.ctb_global_show .ctb_show + .input_area,
.ctb_global_show .ctb_show + div.text_cell_input,
.ctb_global_show .ctb_show ~ div.text_cell_render {
  border-top-right-radius: 0px;
  border-top-left-radius: 0px;
}
.ctb_global_show .ctb_show ~ div.text_cell_render {
  border: 1px solid #cfcfcf;
}
.celltoolbar {
  font-size: 87%;
  padding-top: 3px;
}
.celltoolbar select {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
  width: inherit;
  font-size: inherit;
  height: 22px;
  padding: 0px;
  display: inline-block;
}
.celltoolbar select:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.celltoolbar select::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.celltoolbar select:-ms-input-placeholder {
  color: #999;
}
.celltoolbar select::-webkit-input-placeholder {
  color: #999;
}
.celltoolbar select::-ms-expand {
  border: 0;
  background-color: transparent;
}
.celltoolbar select[disabled],
.celltoolbar select[readonly],
fieldset[disabled] .celltoolbar select {
  background-color: #eeeeee;
  opacity: 1;
}
.celltoolbar select[disabled],
fieldset[disabled] .celltoolbar select {
  cursor: not-allowed;
}
textarea.celltoolbar select {
  height: auto;
}
select.celltoolbar select {
  height: 30px;
  line-height: 30px;
}
textarea.celltoolbar select,
select[multiple].celltoolbar select {
  height: auto;
}
.celltoolbar label {
  margin-left: 5px;
  margin-right: 5px;
}
.completions {
  position: absolute;
  z-index: 110;
  overflow: hidden;
  border: 1px solid #ababab;
  border-radius: 2px;
  -webkit-box-shadow: 0px 6px 10px -1px #adadad;
  box-shadow: 0px 6px 10px -1px #adadad;
  line-height: 1;
}
.completions select {
  background: white;
  outline: none;
  border: none;
  padding: 0px;
  margin: 0px;
  overflow: auto;
  font-family: monospace;
  font-size: 110%;
  color: #000;
  width: auto;
}
.completions select option.context {
  color: #286090;
}
#kernel_logo_widget {
  float: right !important;
  float: right;
}
#kernel_logo_widget .current_kernel_logo {
  display: none;
  margin-top: -1px;
  margin-bottom: -1px;
  width: 32px;
  height: 32px;
}
#menubar {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  margin-top: 1px;
}
#menubar .navbar {
  border-top: 1px;
  border-radius: 0px 0px 2px 2px;
  margin-bottom: 0px;
}
#menubar .navbar-toggle {
  float: left;
  padding-top: 7px;
  padding-bottom: 7px;
  border: none;
}
#menubar .navbar-collapse {
  clear: left;
}
.nav-wrapper {
  border-bottom: 1px solid #e7e7e7;
}
i.menu-icon {
  padding-top: 4px;
}
ul#help_menu li a {
  overflow: hidden;
  padding-right: 2.2em;
}
ul#help_menu li a i {
  margin-right: -1.2em;
}
.dropdown-submenu {
  position: relative;
}
.dropdown-submenu > .dropdown-menu {
  top: 0;
  left: 100%;
  margin-top: -6px;
  margin-left: -1px;
}
.dropdown-submenu:hover > .dropdown-menu {
  display: block;
}
.dropdown-submenu > a:after {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  display: block;
  content: "\f0da";
  float: right;
  color: #333333;
  margin-top: 2px;
  margin-right: -10px;
}
.dropdown-submenu > a:after.pull-left {
  margin-right: .3em;
}
.dropdown-submenu > a:after.pull-right {
  margin-left: .3em;
}
.dropdown-submenu:hover > a:after {
  color: #262626;
}
.dropdown-submenu.pull-left {
  float: none;
}
.dropdown-submenu.pull-left > .dropdown-menu {
  left: -100%;
  margin-left: 10px;
}
#notification_area {
  float: right !important;
  float: right;
  z-index: 10;
}
.indicator_area {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
}
#kernel_indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
  border-left: 1px solid;
}
#kernel_indicator .kernel_indicator_name {
  padding-left: 5px;
  padding-right: 5px;
}
#modal_indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
}
#readonly-indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
  margin-top: 2px;
  margin-bottom: 0px;
  margin-left: 0px;
  margin-right: 0px;
  display: none;
}
.modal_indicator:before {
  width: 1.28571429em;
  text-align: center;
}
.edit_mode .modal_indicator:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f040";
}
.edit_mode .modal_indicator:before.pull-left {
  margin-right: .3em;
}
.edit_mode .modal_indicator:before.pull-right {
  margin-left: .3em;
}
.command_mode .modal_indicator:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: ' ';
}
.command_mode .modal_indicator:before.pull-left {
  margin-right: .3em;
}
.command_mode .modal_indicator:before.pull-right {
  margin-left: .3em;
}
.kernel_idle_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f10c";
}
.kernel_idle_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_idle_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_busy_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f111";
}
.kernel_busy_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_busy_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_dead_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f1e2";
}
.kernel_dead_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_dead_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_disconnected_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f127";
}
.kernel_disconnected_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_disconnected_icon:before.pull-right {
  margin-left: .3em;
}
.notification_widget {
  color: #777;
  z-index: 10;
  background: rgba(240, 240, 240, 0.5);
  margin-right: 4px;
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget:focus,
.notification_widget.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.notification_widget:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active:hover,
.notification_widget.active:hover,
.open > .dropdown-toggle.notification_widget:hover,
.notification_widget:active:focus,
.notification_widget.active:focus,
.open > .dropdown-toggle.notification_widget:focus,
.notification_widget:active.focus,
.notification_widget.active.focus,
.open > .dropdown-toggle.notification_widget.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  background-image: none;
}
.notification_widget.disabled:hover,
.notification_widget[disabled]:hover,
fieldset[disabled] .notification_widget:hover,
.notification_widget.disabled:focus,
.notification_widget[disabled]:focus,
fieldset[disabled] .notification_widget:focus,
.notification_widget.disabled.focus,
.notification_widget[disabled].focus,
fieldset[disabled] .notification_widget.focus {
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget .badge {
  color: #fff;
  background-color: #333;
}
.notification_widget.warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning:focus,
.notification_widget.warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.notification_widget.warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active:hover,
.notification_widget.warning.active:hover,
.open > .dropdown-toggle.notification_widget.warning:hover,
.notification_widget.warning:active:focus,
.notification_widget.warning.active:focus,
.open > .dropdown-toggle.notification_widget.warning:focus,
.notification_widget.warning:active.focus,
.notification_widget.warning.active.focus,
.open > .dropdown-toggle.notification_widget.warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  background-image: none;
}
.notification_widget.warning.disabled:hover,
.notification_widget.warning[disabled]:hover,
fieldset[disabled] .notification_widget.warning:hover,
.notification_widget.warning.disabled:focus,
.notification_widget.warning[disabled]:focus,
fieldset[disabled] .notification_widget.warning:focus,
.notification_widget.warning.disabled.focus,
.notification_widget.warning[disabled].focus,
fieldset[disabled] .notification_widget.warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.notification_widget.success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success:focus,
.notification_widget.success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.notification_widget.success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active:hover,
.notification_widget.success.active:hover,
.open > .dropdown-toggle.notification_widget.success:hover,
.notification_widget.success:active:focus,
.notification_widget.success.active:focus,
.open > .dropdown-toggle.notification_widget.success:focus,
.notification_widget.success:active.focus,
.notification_widget.success.active.focus,
.open > .dropdown-toggle.notification_widget.success.focus {
  color: #fff;
  background-color: #398439;
  border-color: #255625;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  background-image: none;
}
.notification_widget.success.disabled:hover,
.notification_widget.success[disabled]:hover,
fieldset[disabled] .notification_widget.success:hover,
.notification_widget.success.disabled:focus,
.notification_widget.success[disabled]:focus,
fieldset[disabled] .notification_widget.success:focus,
.notification_widget.success.disabled.focus,
.notification_widget.success[disabled].focus,
fieldset[disabled] .notification_widget.success.focus {
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success .badge {
  color: #5cb85c;
  background-color: #fff;
}
.notification_widget.info {
  color: #fff;
  background-color: #5bc0de;
  border-color: #46b8da;
}
.notification_widget.info:focus,
.notification_widget.info.focus {
  color: #fff;
  background-color: #31b0d5;
  border-color: #1b6d85;
}
.notification_widget.info:hover {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.notification_widget.info:active,
.notification_widget.info.active,
.open > .dropdown-toggle.notification_widget.info {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.notification_widget.info:active:hover,
.notification_widget.info.active:hover,
.open > .dropdown-toggle.notification_widget.info:hover,
.notification_widget.info:active:focus,
.notification_widget.info.active:focus,
.open > .dropdown-toggle.notification_widget.info:focus,
.notification_widget.info:active.focus,
.notification_widget.info.active.focus,
.open > .dropdown-toggle.notification_widget.info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
.notification_widget.info:active,
.notification_widget.info.active,
.open > .dropdown-toggle.notification_widget.info {
  background-image: none;
}
.notification_widget.info.disabled:hover,
.notification_widget.info[disabled]:hover,
fieldset[disabled] .notification_widget.info:hover,
.notification_widget.info.disabled:focus,
.notification_widget.info[disabled]:focus,
fieldset[disabled] .notification_widget.info:focus,
.notification_widget.info.disabled.focus,
.notification_widget.info[disabled].focus,
fieldset[disabled] .notification_widget.info.focus {
  background-color: #5bc0de;
  border-color: #46b8da;
}
.notification_widget.info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.notification_widget.danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
}
.notification_widget.danger:focus,
.notification_widget.danger.focus {
  color: #fff;
  background-color: #c9302c;
  border-color: #761c19;
}
.notification_widget.danger:hover {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.notification_widget.danger:active,
.notification_widget.danger.active,
.open > .dropdown-toggle.notification_widget.danger {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.notification_widget.danger:active:hover,
.notification_widget.danger.active:hover,
.open > .dropdown-toggle.notification_widget.danger:hover,
.notification_widget.danger:active:focus,
.notification_widget.danger.active:focus,
.open > .dropdown-toggle.notification_widget.danger:focus,
.notification_widget.danger:active.focus,
.notification_widget.danger.active.focus,
.open > .dropdown-toggle.notification_widget.danger.focus {
  color: #fff;
  background-color: #ac2925;
  border-color: #761c19;
}
.notification_widget.danger:active,
.notification_widget.danger.active,
.open > .dropdown-toggle.notification_widget.danger {
  background-image: none;
}
.notification_widget.danger.disabled:hover,
.notification_widget.danger[disabled]:hover,
fieldset[disabled] .notification_widget.danger:hover,
.notification_widget.danger.disabled:focus,
.notification_widget.danger[disabled]:focus,
fieldset[disabled] .notification_widget.danger:focus,
.notification_widget.danger.disabled.focus,
.notification_widget.danger[disabled].focus,
fieldset[disabled] .notification_widget.danger.focus {
  background-color: #d9534f;
  border-color: #d43f3a;
}
.notification_widget.danger .badge {
  color: #d9534f;
  background-color: #fff;
}
div#pager {
  background-color: #fff;
  font-size: 14px;
  line-height: 20px;
  overflow: hidden;
  display: none;
  position: fixed;
  bottom: 0px;
  width: 100%;
  max-height: 50%;
  padding-top: 8px;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  /* Display over codemirror */
  z-index: 100;
  /* Hack which prevents jquery ui resizable from changing top. */
  top: auto !important;
}
div#pager pre {
  line-height: 1.21429em;
  color: #000;
  background-color: #f7f7f7;
  padding: 0.4em;
}
div#pager #pager-button-area {
  position: absolute;
  top: 8px;
  right: 20px;
}
div#pager #pager-contents {
  position: relative;
  overflow: auto;
  width: 100%;
  height: 100%;
}
div#pager #pager-contents #pager-container {
  position: relative;
  padding: 15px 0px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
div#pager .ui-resizable-handle {
  top: 0px;
  height: 8px;
  background: #f7f7f7;
  border-top: 1px solid #cfcfcf;
  border-bottom: 1px solid #cfcfcf;
  /* This injects handle bars (a short, wide = symbol) for 
        the resize handle. */
}
div#pager .ui-resizable-handle::after {
  content: '';
  top: 2px;
  left: 50%;
  height: 3px;
  width: 30px;
  margin-left: -15px;
  position: absolute;
  border-top: 1px solid #cfcfcf;
}
.quickhelp {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  line-height: 1.8em;
}
.shortcut_key {
  display: inline-block;
  width: 21ex;
  text-align: right;
  font-family: monospace;
}
.shortcut_descr {
  display: inline-block;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
span.save_widget {
  margin-top: 6px;
}
span.save_widget span.filename {
  height: 1em;
  line-height: 1em;
  padding: 3px;
  margin-left: 16px;
  border: none;
  font-size: 146.5%;
  border-radius: 2px;
}
span.save_widget span.filename:hover {
  background-color: #e6e6e6;
}
span.checkpoint_status,
span.autosave_status {
  font-size: small;
}
@media (max-width: 767px) {
  span.save_widget {
    font-size: small;
  }
  span.checkpoint_status,
  span.autosave_status {
    display: none;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  span.checkpoint_status {
    display: none;
  }
  span.autosave_status {
    font-size: x-small;
  }
}
.toolbar {
  padding: 0px;
  margin-left: -5px;
  margin-top: 2px;
  margin-bottom: 5px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.toolbar select,
.toolbar label {
  width: auto;
  vertical-align: middle;
  margin-right: 2px;
  margin-bottom: 0px;
  display: inline;
  font-size: 92%;
  margin-left: 0.3em;
  margin-right: 0.3em;
  padding: 0px;
  padding-top: 3px;
}
.toolbar .btn {
  padding: 2px 8px;
}
.toolbar .btn-group {
  margin-top: 0px;
  margin-left: 5px;
}
#maintoolbar {
  margin-bottom: -3px;
  margin-top: -8px;
  border: 0px;
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<h1 id="Modelling-Guide-for-Predictive-Maintenance">Modelling Guide for Predictive Maintenance<a class="anchor-link" href="#Modelling-Guide-for-Predictive-Maintenance">&#182;</a></h1><p>This notebook provides the steps of implementing a predictive maintenance model found in the <a href="https://gallery.cortanaintelligence.com/Collection/Predictive-Maintenance-Implementation-Guide-1">Predictive Maintenance Modelling Guide</a> collection in the <a href="https://gallery.cortanaintelligence.com/">Cortana Intelligence Gallery</a>.</p>
<p>This is a Python adaptation of a <a href="https://gallery.cortanaintelligence.com/Notebook/Predictive-Maintenance-Modelling-Guide-R-Notebook-1">notebook</a> originally created by <a href="https://gallery.cortanaintelligence.com/Home/Author?authorId=C2475BBD3EA55681F67FD54C8799EDDC8C6288409304605B235E39491B4E31CE">Fidan Boylu Uz</a> (a Microsoft employee) for distribution on the <a href="https://gallery.cortanaintelligence.com/">Cortana Intelligence Gallery</a>. A <a href="https://notebooks.azure.com/library/zZfdk23gVbE">lightly-modified version</a> of the original R notebook is also available on Azure Notebooks.</p>
<h2 id="Outline">Outline<a class="anchor-link" href="#Outline">&#182;</a></h2><ul>
<li><a href="#Problem-Description">Problem Description</a></li>
<li><a href="#Data-Sources">Data Sources</a><ul>
<li><a href="#Telemetry">Telemetry</a></li>
<li><a href="#Errors">Errors</a></li>
<li><a href="#Maintenance">Maintenance</a></li>
<li><a href="#Machines">Machines</a></li>
<li><a href="#Failures">Failures</a></li>
</ul>
</li>
<li><a href="#Feature-Engineering">Feature Engineering</a><ul>
<li><a href="#Lag-Features-from-Telemetry">Lag Features from Telemetry</a></li>
<li><a href="#Lag-Features-from-Errors">Lag Features from Errors</a></li>
<li><a href="#Days-Since-Last-Replacement-from-Maintenance">Days Since Last Replacement from Maintenance</a></li>
<li><a href="#Machine-Features">Machine Features</a></li>
</ul>
</li>
<li><a href="#Label-Construction">Label Construction</a></li>
<li><a href="#Modelling">Modelling</a><ul>
<li><a href="#Training,-Validation-and-Testing">Training, Validation and Testing</a></li>
<li><a href="#Evaluation">Evaluation</a></li>
</ul>
</li>
<li><a href="#Summary">Summary</a></li>
</ul>

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<h2 id="Problem-Description">Problem Description<a class="anchor-link" href="#Problem-Description">&#182;</a></h2><p>A major problem faced by businesses in asset-heavy industries such as manufacturing is the significant costs that are associated with delays in the production process due to mechanical problems. Most of these businesses are interested in predicting these problems in advance so that they can proactively prevent the problems before they occur which will reduce the costly impact caused by downtime. Please refer to the <a href="https://azure.microsoft.com/en-us/documentation/articles/cortana-analytics-playbook-predictive-maintenance/">playbook for predictive maintenance</a> for a detailed explanation of common use cases in predictive maintenance and modelling approaches.</p>
<p>In this notebook, we follow the ideas from the playbook referenced above and aim to provide the steps of implementing a predictive model for a scenario which is based on a synthesis of multiple real-world business problems. This example brings together common data elements observed among many predictive maintenance use cases and the data itself is created by data simulation methods.</p>
<p>The business problem for this example is about predicting problems caused by component failures such that the question "What is the probability that a machine will fail in the near future due to a failure of a certain component?" can be answered.  The problem is formatted as a multi-class classification problem and a machine learning algorithm is used to create the predictive model that learns from historical data collected from machines. In the following sections, we go through the steps of implementing such a model which are feature engineering, label construction, training  and evaluation. First, we start by explaining the data sources in the next section.</p>

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<h2 id="Data-Sources">Data Sources<a class="anchor-link" href="#Data-Sources">&#182;</a></h2><p>Common data sources for predictive maintenance problems are :</p>
<ul>
<li>Failure history: The failure history of a machine or component within the machine.</li>
<li>Maintenance history: The repair history of a machine, e.g. error codes, previous maintenance activities or component replacements.</li>
<li>Machine conditions and usage: The operating conditions of a machine e.g. data collected from sensors.</li>
<li>Machine features: The features of a machine, e.g. engine size, make and model, location.</li>
<li>Operator features: The features of the operator, e.g. gender, past experience</li>
</ul>
<p>The data for this example comes from 4 different sources which are real-time telemetry data collected from machines, error messages, historical maintenance records that include failures and machine information such as type and age.</p>

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<div class=" highlight hl-ipython2"><pre><span></span><span class="kn">import</span> <span class="nn">pandas</span> <span class="kn">as</span> <span class="nn">pd</span>

<span class="o">!</span>wget https://azuremlsampleexperiments.blob.core.windows.net/datasets/PdM_telemetry.csv
<span class="o">!</span>wget https://azuremlsampleexperiments.blob.core.windows.net/datasets/PdM_errors.csv
<span class="o">!</span>wget https://azuremlsampleexperiments.blob.core.windows.net/datasets/PdM_maint.csv
<span class="o">!</span>wget https://azuremlsampleexperiments.blob.core.windows.net/datasets/PdM_failures.csv
<span class="o">!</span>wget https://azuremlsampleexperiments.blob.core.windows.net/datasets/PdM_machines.csv

<span class="n">telemetry</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s1">&#39;PdM_telemetry.csv&#39;</span><span class="p">)</span>
<span class="n">errors</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s1">&#39;PdM_errors.csv&#39;</span><span class="p">)</span>
<span class="n">maint</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s1">&#39;PdM_maint.csv&#39;</span><span class="p">)</span>
<span class="n">failures</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s1">&#39;PdM_failures.csv&#39;</span><span class="p">)</span>
<span class="n">machines</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s1">&#39;PdM_machines.csv&#39;</span><span class="p">)</span>
</pre></div>

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<pre>--2016-08-05 13:24:56--  https://azuremlsampleexperiments.blob.core.windows.net/datasets/PdM_telemetry.csv
Resolving webproxy (webproxy)... 100.72.46.92
Connecting to webproxy (webproxy)|100.72.46.92|:3128... connected.
Proxy request sent, awaiting response... 200 OK
Length: 80142329 (76M) [application/octet-stream]
Saving to: &#39;PdM_telemetry.csv&#39;

100%[======================================&gt;] 80,142,329  41.5MB/s   in 1.8s   

2016-08-05 13:24:58 (41.5 MB/s) - &#39;PdM_telemetry.csv&#39; saved [80142329/80142329]

--2016-08-05 13:24:58--  https://azuremlsampleexperiments.blob.core.windows.net/datasets/PdM_errors.csv
Resolving webproxy (webproxy)... 100.72.46.92
Connecting to webproxy (webproxy)|100.72.46.92|:3128... connected.
Proxy request sent, awaiting response... 200 OK
Length: 129077 (126K) [application/octet-stream]
Saving to: &#39;PdM_errors.csv&#39;

100%[======================================&gt;] 129,077     --.-K/s   in 0.002s  

2016-08-05 13:24:58 (70.3 MB/s) - &#39;PdM_errors.csv&#39; saved [129077/129077]

--2016-08-05 13:24:58--  https://azuremlsampleexperiments.blob.core.windows.net/datasets/PdM_maint.csv
Resolving webproxy (webproxy)... 100.72.46.92
Connecting to webproxy (webproxy)|100.72.46.92|:3128... connected.
Proxy request sent, awaiting response... 200 OK
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<h3 id="Telemetry">Telemetry<a class="anchor-link" href="#Telemetry">&#182;</a></h3><p>The first data source is the telemetry time-series data which consists of voltage, rotation, pressure, and vibration measurements collected from 100 machines in real time averaged over every hour collected during the year 2015. Below, we display the first 10 records in the dataset. A summary of the whole dataset is also provided.</p>

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<div class=" highlight hl-ipython2"><pre><span></span><span class="c1"># format datetime field which comes in as string</span>
<span class="n">telemetry</span><span class="p">[</span><span class="s1">&#39;datetime&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">to_datetime</span><span class="p">(</span><span class="n">telemetry</span><span class="p">[</span><span class="s1">&#39;datetime&#39;</span><span class="p">],</span> <span class="n">format</span><span class="o">=</span><span class="s2">&quot;%Y-%m-</span><span class="si">%d</span><span class="s2"> %H:%M:%S&quot;</span><span class="p">)</span>

<span class="k">print</span><span class="p">(</span><span class="s2">&quot;Total number of telemetry records: </span><span class="si">%d</span><span class="s2">&quot;</span> <span class="o">%</span> <span class="nb">len</span><span class="p">(</span><span class="n">telemetry</span><span class="o">.</span><span class="n">index</span><span class="p">))</span>
<span class="k">print</span><span class="p">(</span><span class="n">telemetry</span><span class="o">.</span><span class="n">head</span><span class="p">())</span>
<span class="n">telemetry</span><span class="o">.</span><span class="n">describe</span><span class="p">()</span>
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<pre>Total number of telemetry records: 876100
             datetime  machineID        volt      rotate    pressure  \
0 2015-01-01 06:00:00          1  176.217853  418.504078  113.077935   
1 2015-01-01 07:00:00          1  162.879223  402.747490   95.460525   
2 2015-01-01 08:00:00          1  170.989902  527.349825   75.237905   
3 2015-01-01 09:00:00          1  162.462833  346.149335  109.248561   
4 2015-01-01 10:00:00          1  157.610021  435.376873  111.886648   

   vibration  
0  45.087686  
1  43.413973  
2  34.178847  
3  41.122144  
4  25.990511  
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<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>machineID</th>
      <th>volt</th>
      <th>rotate</th>
      <th>pressure</th>
      <th>vibration</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>count</th>
      <td>876100.000000</td>
      <td>876100.000000</td>
      <td>876100.000000</td>
      <td>876100.000000</td>
      <td>876100.000000</td>
    </tr>
    <tr>
      <th>mean</th>
      <td>50.500000</td>
      <td>170.777736</td>
      <td>446.605119</td>
      <td>100.858668</td>
      <td>40.385007</td>
    </tr>
    <tr>
      <th>std</th>
      <td>28.866087</td>
      <td>15.509114</td>
      <td>52.673886</td>
      <td>11.048679</td>
      <td>5.370361</td>
    </tr>
    <tr>
      <th>min</th>
      <td>1.000000</td>
      <td>97.333604</td>
      <td>138.432075</td>
      <td>51.237106</td>
      <td>14.877054</td>
    </tr>
    <tr>
      <th>25%</th>
      <td>25.750000</td>
      <td>160.304927</td>
      <td>412.305714</td>
      <td>93.498181</td>
      <td>36.777299</td>
    </tr>
    <tr>
      <th>50%</th>
      <td>50.500000</td>
      <td>170.607338</td>
      <td>447.558150</td>
      <td>100.425559</td>
      <td>40.237247</td>
    </tr>
    <tr>
      <th>75%</th>
      <td>75.250000</td>
      <td>181.004493</td>
      <td>482.176600</td>
      <td>107.555231</td>
      <td>43.784938</td>
    </tr>
    <tr>
      <th>max</th>
      <td>100.000000</td>
      <td>255.124717</td>
      <td>695.020984</td>
      <td>185.951998</td>
      <td>76.791072</td>
    </tr>
  </tbody>
</table>
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<p>As an example, below is a plot of voltage values for machine ID 1 for the first half of 2015.</p>

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<div class=" highlight hl-ipython2"><pre><span></span><span class="o">%</span><span class="k">matplotlib</span> inline
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="kn">as</span> <span class="nn">plt</span>
<span class="kn">import</span> <span class="nn">seaborn</span> <span class="kn">as</span> <span class="nn">sns</span>

<span class="n">plot_df</span> <span class="o">=</span> <span class="n">telemetry</span><span class="o">.</span><span class="n">loc</span><span class="p">[(</span><span class="n">telemetry</span><span class="p">[</span><span class="s1">&#39;machineID&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="mi">1</span><span class="p">)</span> <span class="o">&amp;</span>
                        <span class="p">(</span><span class="n">telemetry</span><span class="p">[</span><span class="s1">&#39;datetime&#39;</span><span class="p">]</span> <span class="o">&gt;</span> <span class="n">pd</span><span class="o">.</span><span class="n">to_datetime</span><span class="p">(</span><span class="s1">&#39;2015-01-01&#39;</span><span class="p">))</span> <span class="o">&amp;</span>
                        <span class="p">(</span><span class="n">telemetry</span><span class="p">[</span><span class="s1">&#39;datetime&#39;</span><span class="p">]</span> <span class="o">&lt;</span> <span class="n">pd</span><span class="o">.</span><span class="n">to_datetime</span><span class="p">(</span><span class="s1">&#39;2015-02-01&#39;</span><span class="p">)),</span> <span class="p">[</span><span class="s1">&#39;datetime&#39;</span><span class="p">,</span> <span class="s1">&#39;volt&#39;</span><span class="p">]]</span>

<span class="n">sns</span><span class="o">.</span><span class="n">set_style</span><span class="p">(</span><span class="s2">&quot;darkgrid&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">12</span><span class="p">,</span> <span class="mi">6</span><span class="p">))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">plot_df</span><span class="p">[</span><span class="s1">&#39;datetime&#39;</span><span class="p">],</span> <span class="n">plot_df</span><span class="p">[</span><span class="s1">&#39;volt&#39;</span><span class="p">])</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;voltage&#39;</span><span class="p">)</span>

<span class="c1"># make x-axis ticks legible</span>
<span class="n">adf</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">gca</span><span class="p">()</span><span class="o">.</span><span class="n">get_xaxis</span><span class="p">()</span><span class="o">.</span><span class="n">get_major_formatter</span><span class="p">()</span>
<span class="n">adf</span><span class="o">.</span><span class="n">scaled</span><span class="p">[</span><span class="mf">1.0</span><span class="p">]</span> <span class="o">=</span> <span class="s1">&#39;%m-</span><span class="si">%d</span><span class="s1">&#39;</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">&#39;Date&#39;</span><span class="p">)</span>
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<pre>:0: FutureWarning: IPython widgets are experimental and may change in the future.
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<h3 id="Errors">Errors<a class="anchor-link" href="#Errors">&#182;</a></h3><p>The second major data source is the error logs. These are non-breaking errors thrown while the machine is still operational and do not constitute as failures. The error date and times are rounded to the closest hour since the telemetry data is collected at an hourly rate.</p>

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<div class="prompt input_prompt">In&nbsp;[4]:</div>
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<div class=" highlight hl-ipython2"><pre><span></span><span class="c1"># format datetime field which comes in as string</span>
<span class="n">errors</span><span class="p">[</span><span class="s1">&#39;datetime&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">to_datetime</span><span class="p">(</span><span class="n">errors</span><span class="p">[</span><span class="s1">&#39;datetime&#39;</span><span class="p">],</span> <span class="n">format</span><span class="o">=</span><span class="s2">&quot;%Y-%m-</span><span class="si">%d</span><span class="s2"> %H:%M:%S&quot;</span><span class="p">)</span>
<span class="n">errors</span><span class="p">[</span><span class="s1">&#39;errorID&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">errors</span><span class="p">[</span><span class="s1">&#39;errorID&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;category&#39;</span><span class="p">)</span>

<span class="k">print</span><span class="p">(</span><span class="s2">&quot;Total number of error records: </span><span class="si">%d</span><span class="s2">&quot;</span> <span class="o">%</span> <span class="nb">len</span><span class="p">(</span><span class="n">errors</span><span class="o">.</span><span class="n">index</span><span class="p">))</span>
<span class="n">errors</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
</pre></div>

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<pre>Total number of error records: 3919
</pre>
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<div class="prompt output_prompt">Out[4]:</div>


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<div>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>datetime</th>
      <th>machineID</th>
      <th>errorID</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>2015-01-03 07:00:00</td>
      <td>1</td>
      <td>error1</td>
    </tr>
    <tr>
      <th>1</th>
      <td>2015-01-03 20:00:00</td>
      <td>1</td>
      <td>error3</td>
    </tr>
    <tr>
      <th>2</th>
      <td>2015-01-04 06:00:00</td>
      <td>1</td>
      <td>error5</td>
    </tr>
    <tr>
      <th>3</th>
      <td>2015-01-10 15:00:00</td>
      <td>1</td>
      <td>error4</td>
    </tr>
    <tr>
      <th>4</th>
      <td>2015-01-22 10:00:00</td>
      <td>1</td>
      <td>error4</td>
    </tr>
  </tbody>
</table>
</div>
</div>

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<div class="prompt input_prompt">In&nbsp;[5]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython2"><pre><span></span><span class="n">sns</span><span class="o">.</span><span class="n">set_style</span><span class="p">(</span><span class="s2">&quot;darkgrid&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">8</span><span class="p">,</span> <span class="mi">4</span><span class="p">))</span>
<span class="n">errors</span><span class="p">[</span><span class="s1">&#39;errorID&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">kind</span><span class="o">=</span><span class="s1">&#39;bar&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;Count&#39;</span><span class="p">)</span>
</pre></div>

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<div class="prompt output_prompt">Out[5]:</div>


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<pre>&lt;matplotlib.text.Text at 0x7ff51fb19590&gt;</pre>
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>
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<h3 id="Maintenance">Maintenance<a class="anchor-link" href="#Maintenance">&#182;</a></h3><p>These are the scheduled and unscheduled maintenance records which correspond to both regular inspection of components as well as failures. A record is generated if a component is replaced during the scheduled inspection or replaced due to a breakdown. The records that are created due to breakdowns will be called failures which is explained in the later sections. Maintenance data has both 2014 and 2015 records.</p>

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<div class=" highlight hl-ipython2"><pre><span></span><span class="c1"># format datetime field which comes in as string</span>
<span class="n">maint</span><span class="p">[</span><span class="s1">&#39;datetime&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">to_datetime</span><span class="p">(</span><span class="n">maint</span><span class="p">[</span><span class="s1">&#39;datetime&#39;</span><span class="p">],</span> <span class="n">format</span><span class="o">=</span><span class="s2">&quot;%Y-%m-</span><span class="si">%d</span><span class="s2"> %H:%M:%S&quot;</span><span class="p">)</span>
<span class="n">maint</span><span class="p">[</span><span class="s1">&#39;comp&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">maint</span><span class="p">[</span><span class="s1">&#39;comp&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;category&#39;</span><span class="p">)</span>

<span class="k">print</span><span class="p">(</span><span class="s2">&quot;Total number of maintenance records: </span><span class="si">%d</span><span class="s2">&quot;</span> <span class="o">%</span> <span class="nb">len</span><span class="p">(</span><span class="n">maint</span><span class="o">.</span><span class="n">index</span><span class="p">))</span>
<span class="n">maint</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
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<pre>Total number of maintenance records: 3286
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<div>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>datetime</th>
      <th>machineID</th>
      <th>comp</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>2014-06-01 06:00:00</td>
      <td>1</td>
      <td>comp2</td>
    </tr>
    <tr>
      <th>1</th>
      <td>2014-07-16 06:00:00</td>
      <td>1</td>
      <td>comp4</td>
    </tr>
    <tr>
      <th>2</th>
      <td>2014-07-31 06:00:00</td>
      <td>1</td>
      <td>comp3</td>
    </tr>
    <tr>
      <th>3</th>
      <td>2014-12-13 06:00:00</td>
      <td>1</td>
      <td>comp1</td>
    </tr>
    <tr>
      <th>4</th>
      <td>2015-01-05 06:00:00</td>
      <td>1</td>
      <td>comp4</td>
    </tr>
  </tbody>
</table>
</div>
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<div class=" highlight hl-ipython2"><pre><span></span><span class="n">sns</span><span class="o">.</span><span class="n">set_style</span><span class="p">(</span><span class="s2">&quot;darkgrid&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">8</span><span class="p">,</span> <span class="mi">4</span><span class="p">))</span>
<span class="n">maint</span><span class="p">[</span><span class="s1">&#39;comp&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">kind</span><span class="o">=</span><span class="s1">&#39;bar&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;Count&#39;</span><span class="p">)</span>
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<pre>&lt;matplotlib.text.Text at 0x7ff51fadef50&gt;</pre>
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<h3 id="Machines">Machines<a class="anchor-link" href="#Machines">&#182;</a></h3><p>This data set includes some information about the machines: model type and age (years in service).</p>

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<div class=" highlight hl-ipython2"><pre><span></span><span class="n">machines</span><span class="p">[</span><span class="s1">&#39;model&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">machines</span><span class="p">[</span><span class="s1">&#39;model&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;category&#39;</span><span class="p">)</span>

<span class="k">print</span><span class="p">(</span><span class="s2">&quot;Total number of machines: </span><span class="si">%d</span><span class="s2">&quot;</span> <span class="o">%</span> <span class="nb">len</span><span class="p">(</span><span class="n">machines</span><span class="o">.</span><span class="n">index</span><span class="p">))</span>
<span class="n">machines</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
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<pre>Total number of machines: 100
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<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>machineID</th>
      <th>model</th>
      <th>age</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>1</td>
      <td>model3</td>
      <td>18</td>
    </tr>
    <tr>
      <th>1</th>
      <td>2</td>
      <td>model4</td>
      <td>7</td>
    </tr>
    <tr>
      <th>2</th>
      <td>3</td>
      <td>model3</td>
      <td>8</td>
    </tr>
    <tr>
      <th>3</th>
      <td>4</td>
      <td>model3</td>
      <td>7</td>
    </tr>
    <tr>
      <th>4</th>
      <td>5</td>
      <td>model3</td>
      <td>2</td>
    </tr>
  </tbody>
</table>
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<div class=" highlight hl-ipython2"><pre><span></span><span class="n">sns</span><span class="o">.</span><span class="n">set_style</span><span class="p">(</span><span class="s2">&quot;darkgrid&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">8</span><span class="p">,</span> <span class="mi">6</span><span class="p">))</span>
<span class="n">_</span><span class="p">,</span> <span class="n">bins</span><span class="p">,</span> <span class="n">_</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">hist</span><span class="p">([</span><span class="n">machines</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">machines</span><span class="p">[</span><span class="s1">&#39;model&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="s1">&#39;model1&#39;</span><span class="p">,</span> <span class="s1">&#39;age&#39;</span><span class="p">],</span>
                       <span class="n">machines</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">machines</span><span class="p">[</span><span class="s1">&#39;model&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="s1">&#39;model2&#39;</span><span class="p">,</span> <span class="s1">&#39;age&#39;</span><span class="p">],</span>
                       <span class="n">machines</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">machines</span><span class="p">[</span><span class="s1">&#39;model&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="s1">&#39;model3&#39;</span><span class="p">,</span> <span class="s1">&#39;age&#39;</span><span class="p">],</span>
                       <span class="n">machines</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">machines</span><span class="p">[</span><span class="s1">&#39;model&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="s1">&#39;model4&#39;</span><span class="p">,</span> <span class="s1">&#39;age&#39;</span><span class="p">]],</span>
                       <span class="mi">20</span><span class="p">,</span> <span class="n">stacked</span><span class="o">=</span><span class="bp">True</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;model1&#39;</span><span class="p">,</span> <span class="s1">&#39;model2&#39;</span><span class="p">,</span> <span class="s1">&#39;model3&#39;</span><span class="p">,</span> <span class="s1">&#39;model4&#39;</span><span class="p">])</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">&#39;Age (yrs)&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;Count&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
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<pre>&lt;matplotlib.legend.Legend at 0x7ff51fbacdd0&gt;</pre>
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"
>
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<h3 id="Failures">Failures<a class="anchor-link" href="#Failures">&#182;</a></h3><p>These are the records of component replacements due to failures. Each record has a date and time, machine ID, and failed component type.</p>

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<div class="prompt input_prompt">In&nbsp;[10]:</div>
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<div class=" highlight hl-ipython2"><pre><span></span><span class="c1"># format datetime field which comes in as string</span>
<span class="n">failures</span><span class="p">[</span><span class="s1">&#39;datetime&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">to_datetime</span><span class="p">(</span><span class="n">failures</span><span class="p">[</span><span class="s1">&#39;datetime&#39;</span><span class="p">],</span> <span class="n">format</span><span class="o">=</span><span class="s2">&quot;%Y-%m-</span><span class="si">%d</span><span class="s2"> %H:%M:%S&quot;</span><span class="p">)</span>
<span class="n">failures</span><span class="p">[</span><span class="s1">&#39;failure&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">failures</span><span class="p">[</span><span class="s1">&#39;failure&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;category&#39;</span><span class="p">)</span>

<span class="k">print</span><span class="p">(</span><span class="s2">&quot;Total number of failures: </span><span class="si">%d</span><span class="s2">&quot;</span> <span class="o">%</span> <span class="nb">len</span><span class="p">(</span><span class="n">failures</span><span class="o">.</span><span class="n">index</span><span class="p">))</span>
<span class="n">failures</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
</pre></div>

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<pre>Total number of failures: 761
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<div>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>datetime</th>
      <th>machineID</th>
      <th>failure</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>2015-01-05 06:00:00</td>
      <td>1</td>
      <td>comp4</td>
    </tr>
    <tr>
      <th>1</th>
      <td>2015-03-06 06:00:00</td>
      <td>1</td>
      <td>comp1</td>
    </tr>
    <tr>
      <th>2</th>
      <td>2015-04-20 06:00:00</td>
      <td>1</td>
      <td>comp2</td>
    </tr>
    <tr>
      <th>3</th>
      <td>2015-06-19 06:00:00</td>
      <td>1</td>
      <td>comp4</td>
    </tr>
    <tr>
      <th>4</th>
      <td>2015-09-02 06:00:00</td>
      <td>1</td>
      <td>comp4</td>
    </tr>
  </tbody>
</table>
</div>
</div>

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<p>Below is the histogram of the failures due to each component. We see that the most failures happen due to component 2.</p>

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<div class="prompt input_prompt">In&nbsp;[11]:</div>
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<div class=" highlight hl-ipython2"><pre><span></span><span class="n">sns</span><span class="o">.</span><span class="n">set_style</span><span class="p">(</span><span class="s2">&quot;darkgrid&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">8</span><span class="p">,</span> <span class="mi">4</span><span class="p">))</span>
<span class="n">failures</span><span class="p">[</span><span class="s1">&#39;failure&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">kind</span><span class="o">=</span><span class="s1">&#39;bar&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;Count&#39;</span><span class="p">)</span>
</pre></div>

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<pre>&lt;matplotlib.text.Text at 0x7ff5177a2290&gt;</pre>
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<h2 id="Feature-Engineering">Feature Engineering<a class="anchor-link" href="#Feature-Engineering">&#182;</a></h2><p>The first step in predictive maintenance applications is feature engineering which requires bringing the different data sources together to create features that best describe a machines's health condition at a given point in time. In the next sections, several feature engineering methods are used to create features based on the properties of each data source.</p>

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<h3 id="Lag-Features-from-Telemetry">Lag Features from Telemetry<a class="anchor-link" href="#Lag-Features-from-Telemetry">&#182;</a></h3><p>Telemetry data almost always comes with time-stamps which makes it suitable for calculating lagging features. A common method is to pick a window size for the lag features to be created and compute rolling aggregate measures such as mean, standard deviation, minimum, maximum, etc. to represent the short term history of the telemetry over the lag window. In the following, rolling mean and standard deviation of the telemetry data over the last 3 hour lag window is calculated for every 3 hours.</p>

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<div class=" highlight hl-ipython2"><pre><span></span><span class="c1"># Calculate mean values for telemetry features</span>
<span class="n">temp</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">fields</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;volt&#39;</span><span class="p">,</span> <span class="s1">&#39;rotate&#39;</span><span class="p">,</span> <span class="s1">&#39;pressure&#39;</span><span class="p">,</span> <span class="s1">&#39;vibration&#39;</span><span class="p">]</span>
<span class="k">for</span> <span class="n">col</span> <span class="ow">in</span> <span class="n">fields</span><span class="p">:</span>
    <span class="n">temp</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">pivot_table</span><span class="p">(</span><span class="n">telemetry</span><span class="p">,</span>
                               <span class="n">index</span><span class="o">=</span><span class="s1">&#39;datetime&#39;</span><span class="p">,</span>
                               <span class="n">columns</span><span class="o">=</span><span class="s1">&#39;machineID&#39;</span><span class="p">,</span>
                               <span class="n">values</span><span class="o">=</span><span class="n">col</span><span class="p">)</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span><span class="s1">&#39;3H&#39;</span><span class="p">,</span> <span class="n">closed</span><span class="o">=</span><span class="s1">&#39;left&#39;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;right&#39;</span><span class="p">,</span> <span class="n">how</span><span class="o">=</span><span class="s1">&#39;mean&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">unstack</span><span class="p">())</span>
<span class="n">telemetry_mean_3h</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">concat</span><span class="p">(</span><span class="n">temp</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
<span class="n">telemetry_mean_3h</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="p">[</span><span class="n">i</span> <span class="o">+</span> <span class="s1">&#39;mean_3h&#39;</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">fields</span><span class="p">]</span>
<span class="n">telemetry_mean_3h</span><span class="o">.</span><span class="n">reset_index</span><span class="p">(</span><span class="n">inplace</span><span class="o">=</span><span class="bp">True</span><span class="p">)</span>

<span class="c1"># repeat for standard deviation</span>
<span class="n">temp</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">col</span> <span class="ow">in</span> <span class="n">fields</span><span class="p">:</span>
    <span class="n">temp</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">pivot_table</span><span class="p">(</span><span class="n">telemetry</span><span class="p">,</span>
                               <span class="n">index</span><span class="o">=</span><span class="s1">&#39;datetime&#39;</span><span class="p">,</span>
                               <span class="n">columns</span><span class="o">=</span><span class="s1">&#39;machineID&#39;</span><span class="p">,</span>
                               <span class="n">values</span><span class="o">=</span><span class="n">col</span><span class="p">)</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span><span class="s1">&#39;3H&#39;</span><span class="p">,</span> <span class="n">closed</span><span class="o">=</span><span class="s1">&#39;left&#39;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;right&#39;</span><span class="p">,</span> <span class="n">how</span><span class="o">=</span><span class="s1">&#39;std&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">unstack</span><span class="p">())</span>
<span class="n">telemetry_sd_3h</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">concat</span><span class="p">(</span><span class="n">temp</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
<span class="n">telemetry_sd_3h</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="p">[</span><span class="n">i</span> <span class="o">+</span> <span class="s1">&#39;sd_3h&#39;</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">fields</span><span class="p">]</span>
<span class="n">telemetry_sd_3h</span><span class="o">.</span><span class="n">reset_index</span><span class="p">(</span><span class="n">inplace</span><span class="o">=</span><span class="bp">True</span><span class="p">)</span>

<span class="n">telemetry_mean_3h</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
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<pre>/home/nbcommon/env/lib/python2.7/site-packages/IPython/kernel/__main__.py:8: FutureWarning: how in .resample() is deprecated
the new syntax is .resample(...).mean()
/home/nbcommon/env/lib/python2.7/site-packages/IPython/kernel/__main__.py:19: FutureWarning: how in .resample() is deprecated
the new syntax is .resample(...).std()
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<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>machineID</th>
      <th>datetime</th>
      <th>voltmean_3h</th>
      <th>rotatemean_3h</th>
      <th>pressuremean_3h</th>
      <th>vibrationmean_3h</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>1</td>
      <td>2015-01-01 09:00:00</td>
      <td>170.028993</td>
      <td>449.533798</td>
      <td>94.592122</td>
      <td>40.893502</td>
    </tr>
    <tr>
      <th>1</th>
      <td>1</td>
      <td>2015-01-01 12:00:00</td>
      <td>164.192565</td>
      <td>403.949857</td>
      <td>105.687417</td>
      <td>34.255891</td>
    </tr>
    <tr>
      <th>2</th>
      <td>1</td>
      <td>2015-01-01 15:00:00</td>
      <td>168.134445</td>
      <td>435.781707</td>
      <td>107.793709</td>
      <td>41.239405</td>
    </tr>
    <tr>
      <th>3</th>
      <td>1</td>
      <td>2015-01-01 18:00:00</td>
      <td>165.514453</td>
      <td>430.472823</td>
      <td>101.703289</td>
      <td>40.373739</td>
    </tr>
    <tr>
      <th>4</th>
      <td>1</td>
      <td>2015-01-01 21:00:00</td>
      <td>168.809347</td>
      <td>437.111120</td>
      <td>90.911060</td>
      <td>41.738542</td>
    </tr>
  </tbody>
</table>
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<p>For capturing a longer term effect, 24 hour lag features are also calculated as below.</p>

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<div class=" highlight hl-ipython2"><pre><span></span><span class="n">temp</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">fields</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;volt&#39;</span><span class="p">,</span> <span class="s1">&#39;rotate&#39;</span><span class="p">,</span> <span class="s1">&#39;pressure&#39;</span><span class="p">,</span> <span class="s1">&#39;vibration&#39;</span><span class="p">]</span>
<span class="k">for</span> <span class="n">col</span> <span class="ow">in</span> <span class="n">fields</span><span class="p">:</span>
    <span class="n">temp</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">rolling_mean</span><span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">pivot_table</span><span class="p">(</span><span class="n">telemetry</span><span class="p">,</span>
                                               <span class="n">index</span><span class="o">=</span><span class="s1">&#39;datetime&#39;</span><span class="p">,</span>
                                               <span class="n">columns</span><span class="o">=</span><span class="s1">&#39;machineID&#39;</span><span class="p">,</span>
                                               <span class="n">values</span><span class="o">=</span><span class="n">col</span><span class="p">),</span> <span class="n">window</span><span class="o">=</span><span class="mi">24</span><span class="p">)</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span><span class="s1">&#39;3H&#39;</span><span class="p">,</span>
                                                                                <span class="n">closed</span><span class="o">=</span><span class="s1">&#39;left&#39;</span><span class="p">,</span>
                                                                                <span class="n">label</span><span class="o">=</span><span class="s1">&#39;right&#39;</span><span class="p">,</span>
                                                                                <span class="n">how</span><span class="o">=</span><span class="s1">&#39;first&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">unstack</span><span class="p">())</span>
<span class="n">telemetry_mean_24h</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">concat</span><span class="p">(</span><span class="n">temp</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
<span class="n">telemetry_mean_24h</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="p">[</span><span class="n">i</span> <span class="o">+</span> <span class="s1">&#39;mean_24h&#39;</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">fields</span><span class="p">]</span>
<span class="n">telemetry_mean_24h</span><span class="o">.</span><span class="n">reset_index</span><span class="p">(</span><span class="n">inplace</span><span class="o">=</span><span class="bp">True</span><span class="p">)</span>
<span class="n">telemetry_mean_24h</span> <span class="o">=</span> <span class="n">telemetry_mean_24h</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="o">-</span><span class="n">telemetry_mean_24h</span><span class="p">[</span><span class="s1">&#39;voltmean_24h&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">isnull</span><span class="p">()]</span>

<span class="c1"># repeat for standard deviation</span>
<span class="n">temp</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">fields</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;volt&#39;</span><span class="p">,</span> <span class="s1">&#39;rotate&#39;</span><span class="p">,</span> <span class="s1">&#39;pressure&#39;</span><span class="p">,</span> <span class="s1">&#39;vibration&#39;</span><span class="p">]</span>
<span class="k">for</span> <span class="n">col</span> <span class="ow">in</span> <span class="n">fields</span><span class="p">:</span>
    <span class="n">temp</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">rolling_std</span><span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">pivot_table</span><span class="p">(</span><span class="n">telemetry</span><span class="p">,</span>
                                               <span class="n">index</span><span class="o">=</span><span class="s1">&#39;datetime&#39;</span><span class="p">,</span>
                                               <span class="n">columns</span><span class="o">=</span><span class="s1">&#39;machineID&#39;</span><span class="p">,</span>
                                               <span class="n">values</span><span class="o">=</span><span class="n">col</span><span class="p">),</span> <span class="n">window</span><span class="o">=</span><span class="mi">24</span><span class="p">)</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span><span class="s1">&#39;3H&#39;</span><span class="p">,</span>
                                                                                <span class="n">closed</span><span class="o">=</span><span class="s1">&#39;left&#39;</span><span class="p">,</span>
                                                                                <span class="n">label</span><span class="o">=</span><span class="s1">&#39;right&#39;</span><span class="p">,</span>
                                                                                <span class="n">how</span><span class="o">=</span><span class="s1">&#39;first&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">unstack</span><span class="p">())</span>
<span class="n">telemetry_sd_24h</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">concat</span><span class="p">(</span><span class="n">temp</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
<span class="n">telemetry_sd_24h</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="p">[</span><span class="n">i</span> <span class="o">+</span> <span class="s1">&#39;sd_24h&#39;</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">fields</span><span class="p">]</span>
<span class="n">telemetry_sd_24h</span><span class="o">.</span><span class="n">reset_index</span><span class="p">(</span><span class="n">inplace</span><span class="o">=</span><span class="bp">True</span><span class="p">)</span>
<span class="n">telemetry_sd_24h</span> <span class="o">=</span> <span class="n">telemetry_sd_24h</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="o">-</span><span class="n">telemetry_sd_24h</span><span class="p">[</span><span class="s1">&#39;voltsd_24h&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">isnull</span><span class="p">()]</span>

<span class="c1"># Notice that a 24h rolling average is not available at the earliest timepoints</span>
<span class="n">telemetry_mean_24h</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
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<pre>/home/nbcommon/env/lib/python2.7/site-packages/IPython/kernel/__main__.py:7: FutureWarning: pd.rolling_mean is deprecated for DataFrame and will be removed in a future version, replace with 
	DataFrame.rolling(window=24,center=False).mean()
/home/nbcommon/env/lib/python2.7/site-packages/IPython/kernel/__main__.py:10: FutureWarning: how in .resample() is deprecated
the new syntax is .resample(...).first()
/home/nbcommon/env/lib/python2.7/site-packages/IPython/kernel/__main__.py:23: FutureWarning: pd.rolling_std is deprecated for DataFrame and will be removed in a future version, replace with 
	DataFrame.rolling(window=24,center=False).std()
/home/nbcommon/env/lib/python2.7/site-packages/IPython/kernel/__main__.py:26: FutureWarning: how in .resample() is deprecated
the new syntax is .resample(...).first()
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<div>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>machineID</th>
      <th>datetime</th>
      <th>voltmean_24h</th>
      <th>rotatemean_24h</th>
      <th>pressuremean_24h</th>
      <th>vibrationmean_24h</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>7</th>
      <td>1</td>
      <td>2015-01-02 06:00:00</td>
      <td>169.733809</td>
      <td>445.179865</td>
      <td>96.797113</td>
      <td>40.385160</td>
    </tr>
    <tr>
      <th>8</th>
      <td>1</td>
      <td>2015-01-02 09:00:00</td>
      <td>170.614862</td>
      <td>446.364859</td>
      <td>96.849785</td>
      <td>39.736826</td>
    </tr>
    <tr>
      <th>9</th>
      <td>1</td>
      <td>2015-01-02 12:00:00</td>
      <td>169.893965</td>
      <td>447.009407</td>
      <td>97.715600</td>
      <td>39.498374</td>
    </tr>
    <tr>
      <th>10</th>
      <td>1</td>
      <td>2015-01-02 15:00:00</td>
      <td>171.243444</td>
      <td>444.233563</td>
      <td>96.666060</td>
      <td>40.229370</td>
    </tr>
    <tr>
      <th>11</th>
      <td>1</td>
      <td>2015-01-02 18:00:00</td>
      <td>170.792486</td>
      <td>448.440437</td>
      <td>95.766838</td>
      <td>40.055214</td>
    </tr>
    <tr>
      <th>12</th>
      <td>1</td>
      <td>2015-01-02 21:00:00</td>
      <td>170.556674</td>
      <td>452.267095</td>
      <td>98.065860</td>
      <td>40.033247</td>
    </tr>
    <tr>
      <th>13</th>
      <td>1</td>
      <td>2015-01-03 00:00:00</td>
      <td>168.460525</td>
      <td>451.031783</td>
      <td>99.273286</td>
      <td>38.903462</td>
    </tr>
    <tr>
      <th>14</th>
      <td>1</td>
      <td>2015-01-03 03:00:00</td>
      <td>169.772951</td>
      <td>447.502464</td>
      <td>99.005946</td>
      <td>39.389725</td>
    </tr>
    <tr>
      <th>15</th>
      <td>1</td>
      <td>2015-01-03 06:00:00</td>
      <td>170.900562</td>
      <td>453.864597</td>
      <td>100.877342</td>
      <td>38.696225</td>
    </tr>
    <tr>
      <th>16</th>
      <td>1</td>
      <td>2015-01-03 09:00:00</td>
      <td>169.533156</td>
      <td>454.785072</td>
      <td>100.050567</td>
      <td>39.449734</td>
    </tr>
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<p>Next, the columns of the feature datasets created earlier are merged to create the final feature set from telemetry.</p>

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<div class=" highlight hl-ipython2"><pre><span></span><span class="c1"># merge columns of feature sets created earlier</span>
<span class="n">telemetry_feat</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">concat</span><span class="p">([</span><span class="n">telemetry_mean_3h</span><span class="p">,</span>
                            <span class="n">telemetry_sd_3h</span><span class="o">.</span><span class="n">ix</span><span class="p">[:,</span> <span class="mi">2</span><span class="p">:</span><span class="mi">6</span><span class="p">],</span>
                            <span class="n">telemetry_mean_24h</span><span class="o">.</span><span class="n">ix</span><span class="p">[:,</span> <span class="mi">2</span><span class="p">:</span><span class="mi">6</span><span class="p">],</span>
                            <span class="n">telemetry_sd_24h</span><span class="o">.</span><span class="n">ix</span><span class="p">[:,</span> <span class="mi">2</span><span class="p">:</span><span class="mi">6</span><span class="p">]],</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">dropna</span><span class="p">()</span>
<span class="n">telemetry_feat</span><span class="o">.</span><span class="n">describe</span><span class="p">()</span>
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<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>machineID</th>
      <th>voltmean_3h</th>
      <th>rotatemean_3h</th>
      <th>pressuremean_3h</th>
      <th>vibrationmean_3h</th>
      <th>voltsd_3h</th>
      <th>rotatesd_3h</th>
      <th>pressuresd_3h</th>
      <th>vibrationsd_3h</th>
      <th>voltmean_24h</th>
      <th>rotatemean_24h</th>
      <th>pressuremean_24h</th>
      <th>vibrationmean_24h</th>
      <th>voltsd_24h</th>
      <th>rotatesd_24h</th>
      <th>pressuresd_24h</th>
      <th>vibrationsd_24h</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>count</th>
      <td>291300.00000</td>
      <td>291300.000000</td>
      <td>291300.000000</td>
      <td>291300.000000</td>
      <td>291300.000000</td>
      <td>291300.000000</td>
      <td>291300.000000</td>
      <td>291300.000000</td>
      <td>291300.000000</td>
      <td>291300.000000</td>
      <td>291300.000000</td>
      <td>291300.000000</td>
      <td>291300.000000</td>
      <td>291300.000000</td>
      <td>291300.000000</td>
      <td>291300.000000</td>
      <td>291300.000000</td>
    </tr>
    <tr>
      <th>mean</th>
      <td>50.50000</td>
      <td>170.771416</td>
      <td>446.612973</td>
      <td>100.855301</td>
      <td>40.384328</td>
      <td>13.299858</td>
      <td>44.456335</td>
      <td>8.885822</td>
      <td>4.440660</td>
      <td>170.772579</td>
      <td>446.613440</td>
      <td>100.854547</td>
      <td>40.384564</td>
      <td>14.918849</td>
      <td>49.947916</td>
      <td>10.046687</td>
      <td>5.002065</td>
    </tr>
    <tr>
      <th>std</th>
      <td>28.86612</td>
      <td>9.497201</td>
      <td>33.122865</td>
      <td>7.408854</td>
      <td>3.476641</td>
      <td>6.966647</td>
      <td>23.216421</td>
      <td>4.656341</td>
      <td>2.320066</td>
      <td>4.716970</td>
      <td>18.074248</td>
      <td>4.733098</td>
      <td>2.059861</td>
      <td>2.260726</td>
      <td>7.682126</td>
      <td>1.713726</td>
      <td>0.799820</td>
    </tr>
    <tr>
      <th>min</th>
      <td>1.00000</td>
      <td>125.532506</td>
      <td>211.811184</td>
      <td>72.118639</td>
      <td>26.569635</td>
      <td>0.025509</td>
      <td>0.078991</td>
      <td>0.027417</td>
      <td>0.015278</td>
      <td>155.812721</td>
      <td>266.010419</td>
      <td>91.057429</td>
      <td>35.060087</td>
      <td>6.380619</td>
      <td>18.385248</td>
      <td>4.145308</td>
      <td>2.144863</td>
    </tr>
    <tr>
      <th>25%</th>
      <td>25.75000</td>
      <td>164.445576</td>
      <td>427.568132</td>
      <td>96.238173</td>
      <td>38.147839</td>
      <td>8.027455</td>
      <td>26.903567</td>
      <td>5.370647</td>
      <td>2.684308</td>
      <td>168.070890</td>
      <td>441.549802</td>
      <td>98.668589</td>
      <td>39.354062</td>
      <td>13.358663</td>
      <td>44.668824</td>
      <td>8.924317</td>
      <td>4.460347</td>
    </tr>
    <tr>
      <th>50%</th>
      <td>50.50000</td>
      <td>170.430790</td>
      <td>448.385564</td>
      <td>100.233139</td>
      <td>40.146085</td>
      <td>12.495595</td>
      <td>41.795700</td>
      <td>8.345785</td>
      <td>4.173854</td>
      <td>170.210913</td>
      <td>449.212554</td>
      <td>100.097694</td>
      <td>40.072752</td>
      <td>14.853948</td>
      <td>49.613807</td>
      <td>9.921407</td>
      <td>4.958594</td>
    </tr>
    <tr>
      <th>75%</th>
      <td>75.25000</td>
      <td>176.607051</td>
      <td>468.447680</td>
      <td>104.404520</td>
      <td>42.227392</td>
      <td>17.689118</td>
      <td>59.103715</td>
      <td>11.789645</td>
      <td>5.898997</td>
      <td>172.459612</td>
      <td>456.368008</td>
      <td>101.611121</td>
      <td>40.833364</td>
      <td>16.394764</td>
      <td>54.821318</td>
      <td>10.980498</td>
      <td>5.484480</td>
    </tr>
    <tr>
      <th>max</th>
      <td>100.00000</td>
      <td>241.420717</td>
      <td>586.682904</td>
      <td>162.309656</td>
      <td>69.311324</td>
      <td>58.444332</td>
      <td>179.903039</td>
      <td>35.659369</td>
      <td>18.305595</td>
      <td>220.782618</td>
      <td>499.096975</td>
      <td>152.310351</td>
      <td>61.932124</td>
      <td>27.664538</td>
      <td>103.819404</td>
      <td>28.654103</td>
      <td>12.325783</td>
    </tr>
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<div class=" highlight hl-ipython2"><pre><span></span><span class="n">telemetry_feat</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
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<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>machineID</th>
      <th>datetime</th>
      <th>voltmean_3h</th>
      <th>rotatemean_3h</th>
      <th>pressuremean_3h</th>
      <th>vibrationmean_3h</th>
      <th>voltsd_3h</th>
      <th>rotatesd_3h</th>
      <th>pressuresd_3h</th>
      <th>vibrationsd_3h</th>
      <th>voltmean_24h</th>
      <th>rotatemean_24h</th>
      <th>pressuremean_24h</th>
      <th>vibrationmean_24h</th>
      <th>voltsd_24h</th>
      <th>rotatesd_24h</th>
      <th>pressuresd_24h</th>
      <th>vibrationsd_24h</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>7</th>
      <td>1</td>
      <td>2015-01-02 06:00:00</td>
      <td>180.133784</td>
      <td>440.608320</td>
      <td>94.137969</td>
      <td>41.551544</td>
      <td>21.322735</td>
      <td>48.770512</td>
      <td>2.135684</td>
      <td>10.037208</td>
      <td>169.733809</td>
      <td>445.179865</td>
      <td>96.797113</td>
      <td>40.385160</td>
      <td>11.233120</td>
      <td>48.717395</td>
      <td>10.079880</td>
      <td>5.853209</td>
    </tr>
    <tr>
      <th>8</th>
      <td>1</td>
      <td>2015-01-02 09:00:00</td>
      <td>176.364293</td>
      <td>439.349655</td>
      <td>101.553209</td>
      <td>36.105580</td>
      <td>18.952210</td>
      <td>51.329636</td>
      <td>13.789279</td>
      <td>6.737739</td>
      <td>170.614862</td>
      <td>446.364859</td>
      <td>96.849785</td>
      <td>39.736826</td>
      <td>12.519402</td>
      <td>48.385076</td>
      <td>10.171540</td>
      <td>6.163231</td>
    </tr>
    <tr>
      <th>9</th>
      <td>1</td>
      <td>2015-01-02 12:00:00</td>
      <td>160.384568</td>
      <td>424.385316</td>
      <td>99.598722</td>
      <td>36.094637</td>
      <td>13.047080</td>
      <td>13.702496</td>
      <td>9.988609</td>
      <td>1.639962</td>
      <td>169.893965</td>
      <td>447.009407</td>
      <td>97.715600</td>
      <td>39.498374</td>
      <td>13.370357</td>
      <td>42.432317</td>
      <td>9.471669</td>
      <td>6.195076</td>
    </tr>
    <tr>
      <th>10</th>
      <td>1</td>
      <td>2015-01-02 15:00:00</td>
      <td>170.472461</td>
      <td>442.933997</td>
      <td>102.380586</td>
      <td>40.483002</td>
      <td>16.642354</td>
      <td>56.290447</td>
      <td>3.305739</td>
      <td>8.854145</td>
      <td>171.243444</td>
      <td>444.233563</td>
      <td>96.666060</td>
      <td>40.229370</td>
      <td>13.299281</td>
      <td>41.346121</td>
      <td>8.731229</td>
      <td>5.687944</td>
    </tr>
    <tr>
      <th>11</th>
      <td>1</td>
      <td>2015-01-02 18:00:00</td>
      <td>163.263806</td>
      <td>468.937558</td>
      <td>102.726648</td>
      <td>40.921802</td>
      <td>17.424688</td>
      <td>38.680380</td>
      <td>9.105775</td>
      <td>3.060781</td>
      <td>170.792486</td>
      <td>448.440437</td>
      <td>95.766838</td>
      <td>40.055214</td>
      <td>13.954518</td>
      <td>43.490234</td>
      <td>8.061653</td>
      <td>5.898069</td>
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<h3 id="Lag-Features-from-Errors">Lag Features from Errors<a class="anchor-link" href="#Lag-Features-from-Errors">&#182;</a></h3><p>Like telemetry data, errors come with timestamps. An important difference is that the error IDs are categorical values and should not be averaged over time intervals like the telemetry measurements. Instead, we count the number of errors of each type in a lagging window. We begin by reformatting the error data to have one entry per machine per time at which at least one error occurred:</p>

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<div class=" highlight hl-ipython2"><pre><span></span><span class="c1"># create a column for each error type</span>
<span class="n">error_count</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">get_dummies</span><span class="p">(</span><span class="n">errors</span><span class="o">.</span><span class="n">set_index</span><span class="p">(</span><span class="s1">&#39;datetime&#39;</span><span class="p">))</span><span class="o">.</span><span class="n">reset_index</span><span class="p">()</span>
<span class="n">error_count</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;datetime&#39;</span><span class="p">,</span> <span class="s1">&#39;machineID&#39;</span><span class="p">,</span> <span class="s1">&#39;error1&#39;</span><span class="p">,</span> <span class="s1">&#39;error2&#39;</span><span class="p">,</span> <span class="s1">&#39;error3&#39;</span><span class="p">,</span> <span class="s1">&#39;error4&#39;</span><span class="p">,</span> <span class="s1">&#39;error5&#39;</span><span class="p">]</span>

<span class="c1"># combine errors for a given machine in a given hour</span>
<span class="n">error_count</span> <span class="o">=</span> <span class="n">error_count</span><span class="o">.</span><span class="n">groupby</span><span class="p">([</span><span class="s1">&#39;machineID&#39;</span><span class="p">,</span> <span class="s1">&#39;datetime&#39;</span><span class="p">])</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span><span class="o">.</span><span class="n">reset_index</span><span class="p">()</span>
<span class="n">error_count</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">13</span><span class="p">)</span>
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<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>machineID</th>
      <th>datetime</th>
      <th>error1</th>
      <th>error2</th>
      <th>error3</th>
      <th>error4</th>
      <th>error5</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>1</td>
      <td>2015-01-03 07:00:00</td>
      <td>1.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <th>1</th>
      <td>1</td>
      <td>2015-01-03 20:00:00</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>0.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <th>2</th>
      <td>1</td>
      <td>2015-01-04 06:00:00</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>1.0</td>
    </tr>
    <tr>
      <th>3</th>
      <td>1</td>
      <td>2015-01-10 15:00:00</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <th>4</th>
      <td>1</td>
      <td>2015-01-22 10:00:00</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <th>5</th>
      <td>1</td>
      <td>2015-01-25 15:00:00</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <th>6</th>
      <td>1</td>
      <td>2015-01-27 04:00:00</td>
      <td>1.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <th>7</th>
      <td>1</td>
      <td>2015-03-03 22:00:00</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <th>8</th>
      <td>1</td>
      <td>2015-03-05 06:00:00</td>
      <td>1.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <th>9</th>
      <td>1</td>
      <td>2015-03-20 18:00:00</td>
      <td>1.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <th>10</th>
      <td>1</td>
      <td>2015-03-26 01:00:00</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <th>11</th>
      <td>1</td>
      <td>2015-03-31 23:00:00</td>
      <td>1.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <th>12</th>
      <td>1</td>
      <td>2015-04-19 06:00:00</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>1.0</td>
      <td>0.0</td>
      <td>0.0</td>
    </tr>
  </tbody>
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<p>Now we add blank entries for all other hourly timepoints (since no errors occurred at those times):</p>

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<div class=" highlight hl-ipython2"><pre><span></span><span class="n">error_count</span> <span class="o">=</span> <span class="n">telemetry</span><span class="p">[[</span><span class="s1">&#39;datetime&#39;</span><span class="p">,</span> <span class="s1">&#39;machineID&#39;</span><span class="p">]]</span><span class="o">.</span><span class="n">merge</span><span class="p">(</span><span class="n">error_count</span><span class="p">,</span> <span class="n">on</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;machineID&#39;</span><span class="p">,</span> <span class="s1">&#39;datetime&#39;</span><span class="p">],</span> <span class="n">how</span><span class="o">=</span><span class="s1">&#39;left&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="mf">0.0</span><span class="p">)</span>
<span class="n">error_count</span><span class="o">.</span><span class="n">describe</span><span class="p">()</span>
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<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>machineID</th>
      <th>error1</th>
      <th>error2</th>
      <th>error3</th>
      <th>error4</th>
      <th>error5</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>count</th>
      <td>876100.000000</td>
      <td>876100.000000</td>
      <td>876100.000000</td>
      <td>876100.000000</td>
      <td>876100.000000</td>
      <td>876100.000000</td>
    </tr>
    <tr>
      <th>mean</th>
      <td>50.500000</td>
      <td>0.001153</td>
      <td>0.001128</td>
      <td>0.000957</td>
      <td>0.000830</td>
      <td>0.000406</td>
    </tr>
    <tr>
      <th>std</th>
      <td>28.866087</td>
      <td>0.033934</td>
      <td>0.033563</td>
      <td>0.030913</td>
      <td>0.028795</td>
      <td>0.020154</td>
    </tr>
    <tr>
      <th>min</th>
      <td>1.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
    </tr>
    <tr>
      <th>25%</th>
      <td>25.750000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
    </tr>
    <tr>
      <th>50%</th>
      <td>50.500000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
    </tr>
    <tr>
      <th>75%</th>
      <td>75.250000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
    </tr>
    <tr>
      <th>max</th>
      <td>100.000000</td>
      <td>1.000000</td>
      <td>1.000000</td>
      <td>1.000000</td>
      <td>1.000000</td>
      <td>1.000000</td>
    </tr>
  </tbody>
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<p>Finally, we can compute the total number of errors of each type over the last 24 hours, for timepoints taken every three hours:</p>

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<div class=" highlight hl-ipython2"><pre><span></span><span class="n">temp</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">fields</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;error</span><span class="si">%d</span><span class="s1">&#39;</span> <span class="o">%</span> <span class="n">i</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span><span class="mi">6</span><span class="p">)]</span>
<span class="k">for</span> <span class="n">col</span> <span class="ow">in</span> <span class="n">fields</span><span class="p">:</span>
    <span class="n">temp</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">rolling_sum</span><span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">pivot_table</span><span class="p">(</span><span class="n">error_count</span><span class="p">,</span>
                                               <span class="n">index</span><span class="o">=</span><span class="s1">&#39;datetime&#39;</span><span class="p">,</span>
                                               <span class="n">columns</span><span class="o">=</span><span class="s1">&#39;machineID&#39;</span><span class="p">,</span>
                                               <span class="n">values</span><span class="o">=</span><span class="n">col</span><span class="p">),</span> <span class="n">window</span><span class="o">=</span><span class="mi">24</span><span class="p">)</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span><span class="s1">&#39;3H&#39;</span><span class="p">,</span>
                                                                             <span class="n">closed</span><span class="o">=</span><span class="s1">&#39;left&#39;</span><span class="p">,</span>
                                                                             <span class="n">label</span><span class="o">=</span><span class="s1">&#39;right&#39;</span><span class="p">,</span>
                                                                             <span class="n">how</span><span class="o">=</span><span class="s1">&#39;first&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">unstack</span><span class="p">())</span>
<span class="n">error_count</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">concat</span><span class="p">(</span><span class="n">temp</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
<span class="n">error_count</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="p">[</span><span class="n">i</span> <span class="o">+</span> <span class="s1">&#39;count&#39;</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">fields</span><span class="p">]</span>
<span class="n">error_count</span><span class="o">.</span><span class="n">reset_index</span><span class="p">(</span><span class="n">inplace</span><span class="o">=</span><span class="bp">True</span><span class="p">)</span>
<span class="n">error_count</span> <span class="o">=</span> <span class="n">error_count</span><span class="o">.</span><span class="n">dropna</span><span class="p">()</span>
<span class="n">error_count</span><span class="o">.</span><span class="n">describe</span><span class="p">()</span>
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<pre>/home/nbcommon/env/lib/python2.7/site-packages/IPython/kernel/__main__.py:7: FutureWarning: pd.rolling_sum is deprecated for DataFrame and will be removed in a future version, replace with 
	DataFrame.rolling(window=24,center=False).sum()
/home/nbcommon/env/lib/python2.7/site-packages/IPython/kernel/__main__.py:10: FutureWarning: how in .resample() is deprecated
the new syntax is .resample(...).first()
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<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>machineID</th>
      <th>error1count</th>
      <th>error2count</th>
      <th>error3count</th>
      <th>error4count</th>
      <th>error5count</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>count</th>
      <td>291400.00000</td>
      <td>291400.000000</td>
      <td>291400.000000</td>
      <td>291400.000000</td>
      <td>291400.000000</td>
      <td>291400.000000</td>
    </tr>
    <tr>
      <th>mean</th>
      <td>50.50000</td>
      <td>0.027649</td>
      <td>0.027069</td>
      <td>0.022907</td>
      <td>0.019904</td>
      <td>0.009753</td>
    </tr>
    <tr>
      <th>std</th>
      <td>28.86612</td>
      <td>0.166273</td>
      <td>0.164429</td>
      <td>0.151453</td>
      <td>0.140820</td>
      <td>0.098797</td>
    </tr>
    <tr>
      <th>min</th>
      <td>1.00000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
    </tr>
    <tr>
      <th>25%</th>
      <td>25.75000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
    </tr>
    <tr>
      <th>50%</th>
      <td>50.50000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
    </tr>
    <tr>
      <th>75%</th>
      <td>75.25000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
    </tr>
    <tr>
      <th>max</th>
      <td>100.00000</td>
      <td>2.000000</td>
      <td>2.000000</td>
      <td>2.000000</td>
      <td>2.000000</td>
      <td>2.000000</td>
    </tr>
  </tbody>
</table>
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<div class=" highlight hl-ipython2"><pre><span></span><span class="n">error_count</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
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  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>machineID</th>
      <th>datetime</th>
      <th>error1count</th>
      <th>error2count</th>
      <th>error3count</th>
      <th>error4count</th>
      <th>error5count</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>7</th>
      <td>1</td>
      <td>2015-01-02 06:00:00</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <th>8</th>
      <td>1</td>
      <td>2015-01-02 09:00:00</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <th>9</th>
      <td>1</td>
      <td>2015-01-02 12:00:00</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <th>10</th>
      <td>1</td>
      <td>2015-01-02 15:00:00</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
    </tr>
    <tr>
      <th>11</th>
      <td>1</td>
      <td>2015-01-02 18:00:00</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
    </tr>
  </tbody>
</table>
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<h3 id="Days-Since-Last-Replacement-from-Maintenance">Days Since Last Replacement from Maintenance<a class="anchor-link" href="#Days-Since-Last-Replacement-from-Maintenance">&#182;</a></h3><p>A crucial data set in this example is the maintenance records which contain the information of component replacement records. Possible features from this data set can be, for example, the number of replacements of each component in the last 3 months to incorporate the frequency of replacements. However, more relevent information would be to calculate how long it has been since a component is last replaced as that would be expected to correlate better with component failures since the longer a component is used, the more degradation should be expected.</p>
<p>As a side note, creating lagging features from maintenance data is not as straightforward as for telemetry and errors, so the features from this data are generated in a more custom way. This type of ad-hoc feature engineering is very common in predictive maintenance since domain knowledge plays a big role in understanding the predictors of a problem. In the following, the days since last component replacement are calculated for each component type as features from the maintenance data.</p>

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<div class=" highlight hl-ipython2"><pre><span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="kn">as</span> <span class="nn">np</span>

<span class="c1"># create a column for each error type</span>
<span class="n">comp_rep</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">get_dummies</span><span class="p">(</span><span class="n">maint</span><span class="o">.</span><span class="n">set_index</span><span class="p">(</span><span class="s1">&#39;datetime&#39;</span><span class="p">))</span><span class="o">.</span><span class="n">reset_index</span><span class="p">()</span>
<span class="n">comp_rep</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;datetime&#39;</span><span class="p">,</span> <span class="s1">&#39;machineID&#39;</span><span class="p">,</span> <span class="s1">&#39;comp1&#39;</span><span class="p">,</span> <span class="s1">&#39;comp2&#39;</span><span class="p">,</span> <span class="s1">&#39;comp3&#39;</span><span class="p">,</span> <span class="s1">&#39;comp4&#39;</span><span class="p">]</span>

<span class="c1"># combine repairs for a given machine in a given hour</span>
<span class="n">comp_rep</span> <span class="o">=</span> <span class="n">comp_rep</span><span class="o">.</span><span class="n">groupby</span><span class="p">([</span><span class="s1">&#39;machineID&#39;</span><span class="p">,</span> <span class="s1">&#39;datetime&#39;</span><span class="p">])</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span><span class="o">.</span><span class="n">reset_index</span><span class="p">()</span>

<span class="c1"># add timepoints where no components were replaced</span>
<span class="n">comp_rep</span> <span class="o">=</span> <span class="n">telemetry</span><span class="p">[[</span><span class="s1">&#39;datetime&#39;</span><span class="p">,</span> <span class="s1">&#39;machineID&#39;</span><span class="p">]]</span><span class="o">.</span><span class="n">merge</span><span class="p">(</span><span class="n">comp_rep</span><span class="p">,</span>
                                                      <span class="n">on</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;datetime&#39;</span><span class="p">,</span> <span class="s1">&#39;machineID&#39;</span><span class="p">],</span>
                                                      <span class="n">how</span><span class="o">=</span><span class="s1">&#39;outer&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">sort_values</span><span class="p">(</span><span class="n">by</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;machineID&#39;</span><span class="p">,</span> <span class="s1">&#39;datetime&#39;</span><span class="p">])</span>

<span class="n">components</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;comp1&#39;</span><span class="p">,</span> <span class="s1">&#39;comp2&#39;</span><span class="p">,</span> <span class="s1">&#39;comp3&#39;</span><span class="p">,</span> <span class="s1">&#39;comp4&#39;</span><span class="p">]</span>
<span class="k">for</span> <span class="n">comp</span> <span class="ow">in</span> <span class="n">components</span><span class="p">:</span>
    <span class="c1"># convert indicator to most recent date of component change</span>
    <span class="n">comp_rep</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">comp_rep</span><span class="p">[</span><span class="n">comp</span><span class="p">]</span> <span class="o">&lt;</span> <span class="mi">1</span><span class="p">,</span> <span class="n">comp</span><span class="p">]</span> <span class="o">=</span> <span class="bp">None</span>
    <span class="n">comp_rep</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="o">-</span><span class="n">comp_rep</span><span class="p">[</span><span class="n">comp</span><span class="p">]</span><span class="o">.</span><span class="n">isnull</span><span class="p">(),</span> <span class="n">comp</span><span class="p">]</span> <span class="o">=</span> <span class="n">comp_rep</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="o">-</span><span class="n">comp_rep</span><span class="p">[</span><span class="n">comp</span><span class="p">]</span><span class="o">.</span><span class="n">isnull</span><span class="p">(),</span> <span class="s1">&#39;datetime&#39;</span><span class="p">]</span>
    
    <span class="c1"># forward-fill the most-recent date of component change</span>
    <span class="n">comp_rep</span><span class="p">[</span><span class="n">comp</span><span class="p">]</span> <span class="o">=</span> <span class="n">comp_rep</span><span class="p">[</span><span class="n">comp</span><span class="p">]</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="n">method</span><span class="o">=</span><span class="s1">&#39;ffill&#39;</span><span class="p">)</span>

<span class="c1"># remove dates in 2014 (may have NaN or future component change dates)    </span>
<span class="n">comp_rep</span> <span class="o">=</span> <span class="n">comp_rep</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">comp_rep</span><span class="p">[</span><span class="s1">&#39;datetime&#39;</span><span class="p">]</span> <span class="o">&gt;</span> <span class="n">pd</span><span class="o">.</span><span class="n">to_datetime</span><span class="p">(</span><span class="s1">&#39;2015-01-01&#39;</span><span class="p">)]</span>

<span class="c1"># replace dates of most recent component change with days since most recent component change</span>
<span class="k">for</span> <span class="n">comp</span> <span class="ow">in</span> <span class="n">components</span><span class="p">:</span>
    <span class="n">comp_rep</span><span class="p">[</span><span class="n">comp</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span><span class="n">comp_rep</span><span class="p">[</span><span class="s1">&#39;datetime&#39;</span><span class="p">]</span> <span class="o">-</span> <span class="n">comp_rep</span><span class="p">[</span><span class="n">comp</span><span class="p">])</span> <span class="o">/</span> <span class="n">np</span><span class="o">.</span><span class="n">timedelta64</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="s1">&#39;D&#39;</span><span class="p">)</span>
    
<span class="n">comp_rep</span><span class="o">.</span><span class="n">describe</span><span class="p">()</span>
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<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>machineID</th>
      <th>comp1</th>
      <th>comp2</th>
      <th>comp3</th>
      <th>comp4</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>count</th>
      <td>876100.000000</td>
      <td>876100.000000</td>
      <td>876100.000000</td>
      <td>876100.000000</td>
      <td>876100.000000</td>
    </tr>
    <tr>
      <th>mean</th>
      <td>50.500000</td>
      <td>53.525185</td>
      <td>51.540806</td>
      <td>52.725962</td>
      <td>53.834191</td>
    </tr>
    <tr>
      <th>std</th>
      <td>28.866087</td>
      <td>62.491679</td>
      <td>59.269254</td>
      <td>58.873114</td>
      <td>59.707978</td>
    </tr>
    <tr>
      <th>min</th>
      <td>1.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
    </tr>
    <tr>
      <th>25%</th>
      <td>25.750000</td>
      <td>13.291667</td>
      <td>12.125000</td>
      <td>13.125000</td>
      <td>13.000000</td>
    </tr>
    <tr>
      <th>50%</th>
      <td>50.500000</td>
      <td>32.791667</td>
      <td>29.666667</td>
      <td>32.291667</td>
      <td>32.500000</td>
    </tr>
    <tr>
      <th>75%</th>
      <td>75.250000</td>
      <td>68.708333</td>
      <td>66.541667</td>
      <td>67.333333</td>
      <td>70.458333</td>
    </tr>
    <tr>
      <th>max</th>
      <td>100.000000</td>
      <td>491.958333</td>
      <td>348.958333</td>
      <td>370.958333</td>
      <td>394.958333</td>
    </tr>
  </tbody>
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<div class=" highlight hl-ipython2"><pre><span></span><span class="n">comp_rep</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
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<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>datetime</th>
      <th>machineID</th>
      <th>comp1</th>
      <th>comp2</th>
      <th>comp3</th>
      <th>comp4</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>2015-01-01 06:00:00</td>
      <td>1.0</td>
      <td>19.000000</td>
      <td>214.000000</td>
      <td>154.000000</td>
      <td>169.000000</td>
    </tr>
    <tr>
      <th>1</th>
      <td>2015-01-01 07:00:00</td>
      <td>1.0</td>
      <td>19.041667</td>
      <td>214.041667</td>
      <td>154.041667</td>
      <td>169.041667</td>
    </tr>
    <tr>
      <th>2</th>
      <td>2015-01-01 08:00:00</td>
      <td>1.0</td>
      <td>19.083333</td>
      <td>214.083333</td>
      <td>154.083333</td>
      <td>169.083333</td>
    </tr>
    <tr>
      <th>3</th>
      <td>2015-01-01 09:00:00</td>
      <td>1.0</td>
      <td>19.125000</td>
      <td>214.125000</td>
      <td>154.125000</td>
      <td>169.125000</td>
    </tr>
    <tr>
      <th>4</th>
      <td>2015-01-01 10:00:00</td>
      <td>1.0</td>
      <td>19.166667</td>
      <td>214.166667</td>
      <td>154.166667</td>
      <td>169.166667</td>
    </tr>
  </tbody>
</table>
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<h3 id="Machine-Features">Machine Features<a class="anchor-link" href="#Machine-Features">&#182;</a></h3><p>The machine features can be used without further modification. These include descriptive information about the type of each machine and its age (number of years in service). If the age information had been recorded as a "first use date" for each machine, a transformation would have been necessary to turn those into a numeric values indicating the years in service.</p>
<p>Lastly, we merge all the feature data sets we created earlier to get the final feature matrix.</p>

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<div class=" highlight hl-ipython2"><pre><span></span><span class="n">final_feat</span> <span class="o">=</span> <span class="n">telemetry_feat</span><span class="o">.</span><span class="n">merge</span><span class="p">(</span><span class="n">error_count</span><span class="p">,</span> <span class="n">on</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;datetime&#39;</span><span class="p">,</span> <span class="s1">&#39;machineID&#39;</span><span class="p">],</span> <span class="n">how</span><span class="o">=</span><span class="s1">&#39;left&#39;</span><span class="p">)</span>
<span class="n">final_feat</span> <span class="o">=</span> <span class="n">final_feat</span><span class="o">.</span><span class="n">merge</span><span class="p">(</span><span class="n">comp_rep</span><span class="p">,</span> <span class="n">on</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;datetime&#39;</span><span class="p">,</span> <span class="s1">&#39;machineID&#39;</span><span class="p">],</span> <span class="n">how</span><span class="o">=</span><span class="s1">&#39;left&#39;</span><span class="p">)</span>
<span class="n">final_feat</span> <span class="o">=</span> <span class="n">final_feat</span><span class="o">.</span><span class="n">merge</span><span class="p">(</span><span class="n">machines</span><span class="p">,</span> <span class="n">on</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;machineID&#39;</span><span class="p">],</span> <span class="n">how</span><span class="o">=</span><span class="s1">&#39;left&#39;</span><span class="p">)</span>

<span class="k">print</span><span class="p">(</span><span class="n">final_feat</span><span class="o">.</span><span class="n">head</span><span class="p">())</span>
<span class="n">final_feat</span><span class="o">.</span><span class="n">describe</span><span class="p">()</span>
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<pre>   machineID            datetime  voltmean_3h  rotatemean_3h  pressuremean_3h  \
0          1 2015-01-02 06:00:00   180.133784     440.608320        94.137969   
1          1 2015-01-02 09:00:00   176.364293     439.349655       101.553209   
2          1 2015-01-02 12:00:00   160.384568     424.385316        99.598722   
3          1 2015-01-02 15:00:00   170.472461     442.933997       102.380586   
4          1 2015-01-02 18:00:00   163.263806     468.937558       102.726648   

   vibrationmean_3h  voltsd_3h  rotatesd_3h  pressuresd_3h  vibrationsd_3h  \
0         41.551544  21.322735    48.770512       2.135684       10.037208   
1         36.105580  18.952210    51.329636      13.789279        6.737739   
2         36.094637  13.047080    13.702496       9.988609        1.639962   
3         40.483002  16.642354    56.290447       3.305739        8.854145   
4         40.921802  17.424688    38.680380       9.105775        3.060781   

  ...   error2count  error3count  error4count  error5count   comp1    comp2  \
0 ...           0.0          0.0          0.0          0.0  20.000  215.000   
1 ...           0.0          0.0          0.0          0.0  20.125  215.125   
2 ...           0.0          0.0          0.0          0.0  20.250  215.250   
3 ...           0.0          0.0          0.0          0.0  20.375  215.375   
4 ...           0.0          0.0          0.0          0.0  20.500  215.500   

     comp3    comp4   model  age  
0  155.000  170.000  model3   18  
1  155.125  170.125  model3   18  
2  155.250  170.250  model3   18  
3  155.375  170.375  model3   18  
4  155.500  170.500  model3   18  

[5 rows x 29 columns]
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<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>machineID</th>
      <th>voltmean_3h</th>
      <th>rotatemean_3h</th>
      <th>pressuremean_3h</th>
      <th>vibrationmean_3h</th>
      <th>voltsd_3h</th>
      <th>rotatesd_3h</th>
      <th>pressuresd_3h</th>
      <th>vibrationsd_3h</th>
      <th>voltmean_24h</th>
      <th>...</th>
      <th>error1count</th>
      <th>error2count</th>
      <th>error3count</th>
      <th>error4count</th>
      <th>error5count</th>
      <th>comp1</th>
      <th>comp2</th>
      <th>comp3</th>
      <th>comp4</th>
      <th>age</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>count</th>
      <td>291300.00000</td>
      <td>291300.000000</td>
      <td>291300.000000</td>
      <td>291300.000000</td>
      <td>291300.000000</td>
      <td>291300.000000</td>
      <td>291300.000000</td>
      <td>291300.000000</td>
      <td>291300.000000</td>
      <td>291300.000000</td>
      <td>...</td>
      <td>291300.000000</td>
      <td>291300.000000</td>
      <td>291300.000000</td>
      <td>291300.000000</td>
      <td>291300.000000</td>
      <td>291300.000000</td>
      <td>291300.000000</td>
      <td>291300.000000</td>
      <td>291300.000000</td>
      <td>291300.000000</td>
    </tr>
    <tr>
      <th>mean</th>
      <td>50.50000</td>
      <td>170.771416</td>
      <td>446.612973</td>
      <td>100.855301</td>
      <td>40.384328</td>
      <td>13.299858</td>
      <td>44.456335</td>
      <td>8.885822</td>
      <td>4.440660</td>
      <td>170.772579</td>
      <td>...</td>
      <td>0.027659</td>
      <td>0.027075</td>
      <td>0.022901</td>
      <td>0.019907</td>
      <td>0.009756</td>
      <td>53.350748</td>
      <td>51.318963</td>
      <td>52.512108</td>
      <td>53.619118</td>
      <td>11.330000</td>
    </tr>
    <tr>
      <th>std</th>
      <td>28.86612</td>
      <td>9.497201</td>
      <td>33.122865</td>
      <td>7.408854</td>
      <td>3.476641</td>
      <td>6.966647</td>
      <td>23.216421</td>
      <td>4.656341</td>
      <td>2.320066</td>
      <td>4.716970</td>
      <td>...</td>
      <td>0.166301</td>
      <td>0.164446</td>
      <td>0.151435</td>
      <td>0.140832</td>
      <td>0.098813</td>
      <td>62.418063</td>
      <td>59.140743</td>
      <td>58.765904</td>
      <td>59.606886</td>
      <td>5.827625</td>
    </tr>
    <tr>
      <th>min</th>
      <td>1.00000</td>
      <td>125.532506</td>
      <td>211.811184</td>
      <td>72.118639</td>
      <td>26.569635</td>
      <td>0.025509</td>
      <td>0.078991</td>
      <td>0.027417</td>
      <td>0.015278</td>
      <td>155.812721</td>
      <td>...</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
    </tr>
    <tr>
      <th>25%</th>
      <td>25.75000</td>
      <td>164.445576</td>
      <td>427.568132</td>
      <td>96.238173</td>
      <td>38.147839</td>
      <td>8.027455</td>
      <td>26.903567</td>
      <td>5.370647</td>
      <td>2.684308</td>
      <td>168.070890</td>
      <td>...</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>13.250000</td>
      <td>12.000000</td>
      <td>13.000000</td>
      <td>12.875000</td>
      <td>6.750000</td>
    </tr>
    <tr>
      <th>50%</th>
      <td>50.50000</td>
      <td>170.430790</td>
      <td>448.385564</td>
      <td>100.233139</td>
      <td>40.146085</td>
      <td>12.495595</td>
      <td>41.795700</td>
      <td>8.345785</td>
      <td>4.173854</td>
      <td>170.210913</td>
      <td>...</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>32.625000</td>
      <td>29.500000</td>
      <td>32.125000</td>
      <td>32.375000</td>
      <td>12.000000</td>
    </tr>
    <tr>
      <th>75%</th>
      <td>75.25000</td>
      <td>176.607051</td>
      <td>468.447680</td>
      <td>104.404520</td>
      <td>42.227392</td>
      <td>17.689118</td>
      <td>59.103715</td>
      <td>11.789645</td>
      <td>5.898997</td>
      <td>172.459612</td>
      <td>...</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>68.500000</td>
      <td>66.250000</td>
      <td>67.000000</td>
      <td>70.125000</td>
      <td>16.000000</td>
    </tr>
    <tr>
      <th>max</th>
      <td>100.00000</td>
      <td>241.420717</td>
      <td>586.682904</td>
      <td>162.309656</td>
      <td>69.311324</td>
      <td>58.444332</td>
      <td>179.903039</td>
      <td>35.659369</td>
      <td>18.305595</td>
      <td>220.782618</td>
      <td>...</td>
      <td>2.000000</td>
      <td>2.000000</td>
      <td>2.000000</td>
      <td>2.000000</td>
      <td>2.000000</td>
      <td>491.875000</td>
      <td>348.875000</td>
      <td>370.875000</td>
      <td>394.875000</td>
      <td>20.000000</td>
    </tr>
  </tbody>
</table>
<p>8 rows × 27 columns</p>
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<h2 id="Label-Construction">Label Construction<a class="anchor-link" href="#Label-Construction">&#182;</a></h2><p>When using multi-class classification for predicting failure due to a problem, labelling is done by taking a time window prior to the failure of an asset and labelling the feature records that fall into that window as "about to fail due to a problem" while labelling all other records as "ÂÂnormal." This time window should be picked according to the business case: in some situations it may be enough to predict failures hours in advance, while in others days or weeks may be needed to allow e.g. for arrival of replacement parts.</p>
<p>The prediction problem for this example scenerio is to estimate the probability that a machine will fail in the near future due to a failure of a certain component. More specifically, the goal is to compute the probability that a machine will fail in the next 24 hours due to a certain component failure (component 1, 2, 3, or 4). Below, a categorical <code>failure</code> feature is created to serve as the label. All records within a 24 hour window before a failure of component 1 have <code>failure=comp1</code>, and so on for components 2, 3, and 4; all records not within 24 hours of a component failure have <code>failure=none</code>.</p>

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<div class=" highlight hl-ipython2"><pre><span></span><span class="n">labeled_features</span> <span class="o">=</span> <span class="n">final_feat</span><span class="o">.</span><span class="n">merge</span><span class="p">(</span><span class="n">failures</span><span class="p">,</span> <span class="n">on</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;datetime&#39;</span><span class="p">,</span> <span class="s1">&#39;machineID&#39;</span><span class="p">],</span> <span class="n">how</span><span class="o">=</span><span class="s1">&#39;left&#39;</span><span class="p">)</span>
<span class="n">labeled_features</span> <span class="o">=</span> <span class="n">labeled_features</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="n">method</span><span class="o">=</span><span class="s1">&#39;bfill&#39;</span><span class="p">,</span> <span class="n">limit</span><span class="o">=</span><span class="mi">7</span><span class="p">)</span> <span class="c1"># fill backward up to 24h</span>
<span class="n">labeled_features</span> <span class="o">=</span> <span class="n">labeled_features</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="s1">&#39;none&#39;</span><span class="p">)</span>
<span class="n">labeled_features</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
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<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>machineID</th>
      <th>datetime</th>
      <th>voltmean_3h</th>
      <th>rotatemean_3h</th>
      <th>pressuremean_3h</th>
      <th>vibrationmean_3h</th>
      <th>voltsd_3h</th>
      <th>rotatesd_3h</th>
      <th>pressuresd_3h</th>
      <th>vibrationsd_3h</th>
      <th>...</th>
      <th>error3count</th>
      <th>error4count</th>
      <th>error5count</th>
      <th>comp1</th>
      <th>comp2</th>
      <th>comp3</th>
      <th>comp4</th>
      <th>model</th>
      <th>age</th>
      <th>failure</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>1</td>
      <td>2015-01-02 06:00:00</td>
      <td>180.133784</td>
      <td>440.608320</td>
      <td>94.137969</td>
      <td>41.551544</td>
      <td>21.322735</td>
      <td>48.770512</td>
      <td>2.135684</td>
      <td>10.037208</td>
      <td>...</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>20.000</td>
      <td>215.000</td>
      <td>155.000</td>
      <td>170.000</td>
      <td>model3</td>
      <td>18</td>
      <td>none</td>
    </tr>
    <tr>
      <th>1</th>
      <td>1</td>
      <td>2015-01-02 09:00:00</td>
      <td>176.364293</td>
      <td>439.349655</td>
      <td>101.553209</td>
      <td>36.105580</td>
      <td>18.952210</td>
      <td>51.329636</td>
      <td>13.789279</td>
      <td>6.737739</td>
      <td>...</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>20.125</td>
      <td>215.125</td>
      <td>155.125</td>
      <td>170.125</td>
      <td>model3</td>
      <td>18</td>
      <td>none</td>
    </tr>
    <tr>
      <th>2</th>
      <td>1</td>
      <td>2015-01-02 12:00:00</td>
      <td>160.384568</td>
      <td>424.385316</td>
      <td>99.598722</td>
      <td>36.094637</td>
      <td>13.047080</td>
      <td>13.702496</td>
      <td>9.988609</td>
      <td>1.639962</td>
      <td>...</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>20.250</td>
      <td>215.250</td>
      <td>155.250</td>
      <td>170.250</td>
      <td>model3</td>
      <td>18</td>
      <td>none</td>
    </tr>
    <tr>
      <th>3</th>
      <td>1</td>
      <td>2015-01-02 15:00:00</td>
      <td>170.472461</td>
      <td>442.933997</td>
      <td>102.380586</td>
      <td>40.483002</td>
      <td>16.642354</td>
      <td>56.290447</td>
      <td>3.305739</td>
      <td>8.854145</td>
      <td>...</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>20.375</td>
      <td>215.375</td>
      <td>155.375</td>
      <td>170.375</td>
      <td>model3</td>
      <td>18</td>
      <td>none</td>
    </tr>
    <tr>
      <th>4</th>
      <td>1</td>
      <td>2015-01-02 18:00:00</td>
      <td>163.263806</td>
      <td>468.937558</td>
      <td>102.726648</td>
      <td>40.921802</td>
      <td>17.424688</td>
      <td>38.680380</td>
      <td>9.105775</td>
      <td>3.060781</td>
      <td>...</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>20.500</td>
      <td>215.500</td>
      <td>155.500</td>
      <td>170.500</td>
      <td>model3</td>
      <td>18</td>
      <td>none</td>
    </tr>
  </tbody>
</table>
<p>5 rows × 30 columns</p>
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<p>Below is an example of records that are labeled as <code>failure=comp4</code> in the failure column. Notice that the first 8 records all occur in the 24-hour window before the first recorded failure of component 4. The next 8 records are within the 24 hour window before another failure of component 4.</p>

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<div class=" highlight hl-ipython2"><pre><span></span><span class="n">labeled_features</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">labeled_features</span><span class="p">[</span><span class="s1">&#39;failure&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="s1">&#39;comp4&#39;</span><span class="p">][:</span><span class="mi">16</span><span class="p">]</span>
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<div>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>machineID</th>
      <th>datetime</th>
      <th>voltmean_3h</th>
      <th>rotatemean_3h</th>
      <th>pressuremean_3h</th>
      <th>vibrationmean_3h</th>
      <th>voltsd_3h</th>
      <th>rotatesd_3h</th>
      <th>pressuresd_3h</th>
      <th>vibrationsd_3h</th>
      <th>...</th>
      <th>error3count</th>
      <th>error4count</th>
      <th>error5count</th>
      <th>comp1</th>
      <th>comp2</th>
      <th>comp3</th>
      <th>comp4</th>
      <th>model</th>
      <th>age</th>
      <th>failure</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>17</th>
      <td>1</td>
      <td>2015-01-04 09:00:00</td>
      <td>166.281848</td>
      <td>453.787824</td>
      <td>106.187582</td>
      <td>51.990080</td>
      <td>24.276228</td>
      <td>23.621315</td>
      <td>11.176731</td>
      <td>3.394073</td>
      <td>...</td>
      <td>1.0</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>22.125</td>
      <td>217.125</td>
      <td>157.125</td>
      <td>172.125</td>
      <td>model3</td>
      <td>18</td>
      <td>comp4</td>
    </tr>
    <tr>
      <th>18</th>
      <td>1</td>
      <td>2015-01-04 12:00:00</td>
      <td>175.412103</td>
      <td>445.450581</td>
      <td>100.887363</td>
      <td>54.251534</td>
      <td>34.918687</td>
      <td>11.001625</td>
      <td>10.580336</td>
      <td>2.921501</td>
      <td>...</td>
      <td>1.0</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>22.250</td>
      <td>217.250</td>
      <td>157.250</td>
      <td>172.250</td>
      <td>model3</td>
      <td>18</td>
      <td>comp4</td>
    </tr>
    <tr>
      <th>19</th>
      <td>1</td>
      <td>2015-01-04 15:00:00</td>
      <td>157.347716</td>
      <td>451.882075</td>
      <td>101.289380</td>
      <td>48.602686</td>
      <td>24.617739</td>
      <td>28.950883</td>
      <td>9.966729</td>
      <td>2.356486</td>
      <td>...</td>
      <td>1.0</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>22.375</td>
      <td>217.375</td>
      <td>157.375</td>
      <td>172.375</td>
      <td>model3</td>
      <td>18</td>
      <td>comp4</td>
    </tr>
    <tr>
      <th>20</th>
      <td>1</td>
      <td>2015-01-04 18:00:00</td>
      <td>176.450550</td>
      <td>446.033068</td>
      <td>84.521555</td>
      <td>47.638836</td>
      <td>8.071400</td>
      <td>76.511343</td>
      <td>2.636879</td>
      <td>4.108621</td>
      <td>...</td>
      <td>1.0</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>22.500</td>
      <td>217.500</td>
      <td>157.500</td>
      <td>172.500</td>
      <td>model3</td>
      <td>18</td>
      <td>comp4</td>
    </tr>
    <tr>
      <th>21</th>
      <td>1</td>
      <td>2015-01-04 21:00:00</td>
      <td>190.325814</td>
      <td>422.692565</td>
      <td>107.393234</td>
      <td>49.552856</td>
      <td>8.390777</td>
      <td>7.176553</td>
      <td>4.262645</td>
      <td>7.598552</td>
      <td>...</td>
      <td>1.0</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>22.625</td>
      <td>217.625</td>
      <td>157.625</td>
      <td>172.625</td>
      <td>model3</td>
      <td>18</td>
      <td>comp4</td>
    </tr>
    <tr>
      <th>22</th>
      <td>1</td>
      <td>2015-01-05 00:00:00</td>
      <td>169.985134</td>
      <td>458.929418</td>
      <td>91.494362</td>
      <td>54.882021</td>
      <td>9.451483</td>
      <td>12.052752</td>
      <td>3.685906</td>
      <td>6.621183</td>
      <td>...</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>22.750</td>
      <td>217.750</td>
      <td>157.750</td>
      <td>172.750</td>
      <td>model3</td>
      <td>18</td>
      <td>comp4</td>
    </tr>
    <tr>
      <th>23</th>
      <td>1</td>
      <td>2015-01-05 03:00:00</td>
      <td>149.082619</td>
      <td>412.180336</td>
      <td>93.509785</td>
      <td>54.386079</td>
      <td>19.075952</td>
      <td>30.715081</td>
      <td>3.090266</td>
      <td>6.530610</td>
      <td>...</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>22.875</td>
      <td>217.875</td>
      <td>157.875</td>
      <td>172.875</td>
      <td>model3</td>
      <td>18</td>
      <td>comp4</td>
    </tr>
    <tr>
      <th>24</th>
      <td>1</td>
      <td>2015-01-05 06:00:00</td>
      <td>185.782709</td>
      <td>439.531288</td>
      <td>99.413660</td>
      <td>51.558082</td>
      <td>14.495664</td>
      <td>45.663743</td>
      <td>4.289212</td>
      <td>7.330397</td>
      <td>...</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>0.000</td>
      <td>218.000</td>
      <td>158.000</td>
      <td>0.000</td>
      <td>model3</td>
      <td>18</td>
      <td>comp4</td>
    </tr>
    <tr>
      <th>1337</th>
      <td>1</td>
      <td>2015-06-18 09:00:00</td>
      <td>169.324639</td>
      <td>453.923471</td>
      <td>101.313249</td>
      <td>53.092274</td>
      <td>28.155693</td>
      <td>42.557599</td>
      <td>7.688674</td>
      <td>2.488851</td>
      <td>...</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>89.125</td>
      <td>29.125</td>
      <td>14.125</td>
      <td>134.125</td>
      <td>model3</td>
      <td>18</td>
      <td>comp4</td>
    </tr>
    <tr>
      <th>1338</th>
      <td>1</td>
      <td>2015-06-18 12:00:00</td>
      <td>190.691297</td>
      <td>441.577271</td>
      <td>97.192512</td>
      <td>44.025425</td>
      <td>6.296827</td>
      <td>47.271008</td>
      <td>7.577957</td>
      <td>4.648336</td>
      <td>...</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>89.250</td>
      <td>29.250</td>
      <td>14.250</td>
      <td>134.250</td>
      <td>model3</td>
      <td>18</td>
      <td>comp4</td>
    </tr>
    <tr>
      <th>1339</th>
      <td>1</td>
      <td>2015-06-18 15:00:00</td>
      <td>163.602957</td>
      <td>433.781185</td>
      <td>93.173047</td>
      <td>43.051368</td>
      <td>18.147449</td>
      <td>30.242516</td>
      <td>10.870615</td>
      <td>2.740922</td>
      <td>...</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>89.375</td>
      <td>29.375</td>
      <td>14.375</td>
      <td>134.375</td>
      <td>model3</td>
      <td>18</td>
      <td>comp4</td>
    </tr>
    <tr>
      <th>1340</th>
      <td>1</td>
      <td>2015-06-18 18:00:00</td>
      <td>178.587550</td>
      <td>427.300815</td>
      <td>118.643186</td>
      <td>50.958609</td>
      <td>2.229649</td>
      <td>17.168087</td>
      <td>15.714144</td>
      <td>5.669003</td>
      <td>...</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>89.500</td>
      <td>29.500</td>
      <td>14.500</td>
      <td>134.500</td>
      <td>model3</td>
      <td>18</td>
      <td>comp4</td>
    </tr>
    <tr>
      <th>1341</th>
      <td>1</td>
      <td>2015-06-18 21:00:00</td>
      <td>158.851795</td>
      <td>520.113831</td>
      <td>101.974559</td>
      <td>44.156671</td>
      <td>14.554854</td>
      <td>77.101968</td>
      <td>4.788908</td>
      <td>5.468742</td>
      <td>...</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>89.625</td>
      <td>29.625</td>
      <td>14.625</td>
      <td>134.625</td>
      <td>model3</td>
      <td>18</td>
      <td>comp4</td>
    </tr>
    <tr>
      <th>1342</th>
      <td>1</td>
      <td>2015-06-19 00:00:00</td>
      <td>162.191516</td>
      <td>453.545010</td>
      <td>101.521779</td>
      <td>49.136659</td>
      <td>12.553190</td>
      <td>33.332139</td>
      <td>5.983913</td>
      <td>1.893250</td>
      <td>...</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>89.750</td>
      <td>29.750</td>
      <td>14.750</td>
      <td>134.750</td>
      <td>model3</td>
      <td>18</td>
      <td>comp4</td>
    </tr>
    <tr>
      <th>1343</th>
      <td>1</td>
      <td>2015-06-19 03:00:00</td>
      <td>166.732741</td>
      <td>485.036994</td>
      <td>100.284288</td>
      <td>44.587560</td>
      <td>11.099161</td>
      <td>57.308864</td>
      <td>3.052958</td>
      <td>3.062215</td>
      <td>...</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>89.875</td>
      <td>29.875</td>
      <td>14.875</td>
      <td>134.875</td>
      <td>model3</td>
      <td>18</td>
      <td>comp4</td>
    </tr>
    <tr>
      <th>1344</th>
      <td>1</td>
      <td>2015-06-19 06:00:00</td>
      <td>172.059069</td>
      <td>463.242610</td>
      <td>96.905050</td>
      <td>53.701413</td>
      <td>14.757880</td>
      <td>55.874000</td>
      <td>3.204981</td>
      <td>2.329615</td>
      <td>...</td>
      <td>0.0</td>
      <td>0.0</td>
      <td>1.0</td>
      <td>0.000</td>
      <td>30.000</td>
      <td>15.000</td>
      <td>0.000</td>
      <td>model3</td>
      <td>18</td>
      <td>comp4</td>
    </tr>
  </tbody>
</table>
<p>16 rows × 30 columns</p>
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<h2 id="Modelling">Modelling<a class="anchor-link" href="#Modelling">&#182;</a></h2><p>After the feature engineering and labelling steps, either Azure Machine Learning Studio or this notebook can be used to create a predictive model. The recommend Azure Machine Learning Studio experiment can be found in the Cortana Intelligence Gallery: <a href="https://gallery.cortanaintelligence.com/Experiment/Predictive-Maintenance-Modelling-Guide-Experiment-1">Predictive Maintenance Modelling Guide Experiment</a>. Below, we describe the modelling process and provide an example Python model.</p>

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<h3 id="Training,-Validation-and-Testing">Training, Validation and Testing<a class="anchor-link" href="#Training,-Validation-and-Testing">&#182;</a></h3><p>When working with time-stamped data as in this example, record partitioning into training, validation, and test sets should be performed carefully to prevent overestimating the performance of the models. In predictive maintenance, the features are usually generated using lagging aggregates: records in the same time window will likely have identical labels and similar feature values. These correlations can give a model an "unfair advantage" when predicting on a test set record that shares its time window with a training set record. We therefore partition records into training, validation, and test sets in large chunks, to minimize the number of time intervals shared between them.</p>
<p>Predictive models have no advance knowledge of future chronological trends: in practice, such trends are likely to exist and to adversely impact the model's performance. To obtain an accurate assessment of a predictive model's performance, we recommend training on older records and validating/testing using newer records.</p>
<p>For both of these reasons, a time-dependent record splitting strategy is an excellent choice for predictive maintenace models. The split is effected by choosing a point in time based on the desired size of the training and test sets: all records before the timepoint are used for training the model, and all remaining records are used for testing. (If desired, the timeline could be further divided to create validation sets for parameter selection.) To prevent any records in the training set from sharing time windows with the records in the test set, we remove any records at the boundary -- in this case, by ignoring 24 hours' worth of data prior to the timepoint.</p>

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<div class=" highlight hl-ipython2"><pre><span></span><span class="kn">from</span> <span class="nn">sklearn.ensemble</span> <span class="kn">import</span> <span class="n">GradientBoostingClassifier</span>

<span class="c1"># make test and training splits</span>
<span class="n">threshold_dates</span> <span class="o">=</span> <span class="p">[[</span><span class="n">pd</span><span class="o">.</span><span class="n">to_datetime</span><span class="p">(</span><span class="s1">&#39;2015-07-31 01:00:00&#39;</span><span class="p">),</span> <span class="n">pd</span><span class="o">.</span><span class="n">to_datetime</span><span class="p">(</span><span class="s1">&#39;2015-08-01 01:00:00&#39;</span><span class="p">)],</span>
                   <span class="p">[</span><span class="n">pd</span><span class="o">.</span><span class="n">to_datetime</span><span class="p">(</span><span class="s1">&#39;2015-08-31 01:00:00&#39;</span><span class="p">),</span> <span class="n">pd</span><span class="o">.</span><span class="n">to_datetime</span><span class="p">(</span><span class="s1">&#39;2015-09-01 01:00:00&#39;</span><span class="p">)],</span>
                   <span class="p">[</span><span class="n">pd</span><span class="o">.</span><span class="n">to_datetime</span><span class="p">(</span><span class="s1">&#39;2015-09-30 01:00:00&#39;</span><span class="p">),</span> <span class="n">pd</span><span class="o">.</span><span class="n">to_datetime</span><span class="p">(</span><span class="s1">&#39;2015-10-01 01:00:00&#39;</span><span class="p">)]]</span>

<span class="n">test_results</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">models</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">last_train_date</span><span class="p">,</span> <span class="n">first_test_date</span> <span class="ow">in</span> <span class="n">threshold_dates</span><span class="p">:</span>
    <span class="c1"># split out training and test data</span>
    <span class="n">train_y</span> <span class="o">=</span> <span class="n">labeled_features</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">labeled_features</span><span class="p">[</span><span class="s1">&#39;datetime&#39;</span><span class="p">]</span> <span class="o">&lt;</span> <span class="n">last_train_date</span><span class="p">,</span> <span class="s1">&#39;failure&#39;</span><span class="p">]</span>
    <span class="n">train_X</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">get_dummies</span><span class="p">(</span><span class="n">labeled_features</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">labeled_features</span><span class="p">[</span><span class="s1">&#39;datetime&#39;</span><span class="p">]</span> <span class="o">&lt;</span> <span class="n">last_train_date</span><span class="p">]</span><span class="o">.</span><span class="n">drop</span><span class="p">([</span><span class="s1">&#39;datetime&#39;</span><span class="p">,</span>
                                                                                                        <span class="s1">&#39;machineID&#39;</span><span class="p">,</span>
                                                                                                        <span class="s1">&#39;failure&#39;</span><span class="p">],</span> <span class="mi">1</span><span class="p">))</span>
    <span class="n">test_X</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">get_dummies</span><span class="p">(</span><span class="n">labeled_features</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">labeled_features</span><span class="p">[</span><span class="s1">&#39;datetime&#39;</span><span class="p">]</span> <span class="o">&gt;</span> <span class="n">first_test_date</span><span class="p">]</span><span class="o">.</span><span class="n">drop</span><span class="p">([</span><span class="s1">&#39;datetime&#39;</span><span class="p">,</span>
                                                                                                       <span class="s1">&#39;machineID&#39;</span><span class="p">,</span>
                                                                                                       <span class="s1">&#39;failure&#39;</span><span class="p">],</span> <span class="mi">1</span><span class="p">))</span>
    <span class="c1"># train and predict using the model, storing results for later</span>
    <span class="n">my_model</span> <span class="o">=</span> <span class="n">GradientBoostingClassifier</span><span class="p">(</span><span class="n">random_state</span><span class="o">=</span><span class="mi">42</span><span class="p">)</span>
    <span class="n">my_model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">train_X</span><span class="p">,</span> <span class="n">train_y</span><span class="p">)</span>
    <span class="n">test_result</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">labeled_features</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">labeled_features</span><span class="p">[</span><span class="s1">&#39;datetime&#39;</span><span class="p">]</span> <span class="o">&gt;</span> <span class="n">first_test_date</span><span class="p">])</span>
    <span class="n">test_result</span><span class="p">[</span><span class="s1">&#39;predicted_failure&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">my_model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">test_X</span><span class="p">)</span>
    <span class="n">test_results</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">test_result</span><span class="p">)</span>
    <span class="n">models</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">my_model</span><span class="p">)</span>
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<p>Below, we plot the feature importances in the (first) trained model:</p>

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<div class=" highlight hl-ipython2"><pre><span></span><span class="n">sns</span><span class="o">.</span><span class="n">set_style</span><span class="p">(</span><span class="s2">&quot;darkgrid&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">6</span><span class="p">))</span>
<span class="n">labels</span><span class="p">,</span> <span class="n">importances</span> <span class="o">=</span> <span class="nb">zip</span><span class="p">(</span><span class="o">*</span><span class="nb">sorted</span><span class="p">(</span><span class="nb">zip</span><span class="p">(</span><span class="n">test_X</span><span class="o">.</span><span class="n">columns</span><span class="p">,</span> <span class="n">models</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">feature_importances_</span><span class="p">),</span> <span class="n">reverse</span><span class="o">=</span><span class="bp">True</span><span class="p">,</span> <span class="n">key</span><span class="o">=</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">]))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xticks</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">labels</span><span class="p">)),</span> <span class="n">labels</span><span class="p">)</span>
<span class="n">_</span><span class="p">,</span> <span class="n">labels</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">xticks</span><span class="p">()</span>
<span class="n">plt</span><span class="o">.</span><span class="n">setp</span><span class="p">(</span><span class="n">labels</span><span class="p">,</span> <span class="n">rotation</span><span class="o">=</span><span class="mi">90</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">bar</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">importances</span><span class="p">)),</span> <span class="n">importances</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;Importance&#39;</span><span class="p">)</span>
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<pre>&lt;Container object of 30 artists&gt;</pre>
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<h2 id="Evaluation">Evaluation<a class="anchor-link" href="#Evaluation">&#182;</a></h2><p>In predictive maintenance, machine failures are usually rare occurrences in the lifetime of the assets compared to normal operation. This causes an imbalance in the label distribution which usually causes poor performance as algorithms tend to classify majority class examples better at the expense of minority class examples as the total misclassification error is much improved when majority class is labeled correctly.  This causes low recall rates although accuracy can be high and becomes a larger problem when the cost of false alarms to the business is very high. To help with this problem, sampling techniques such as oversampling of the minority examples are usually used along with more sophisticated techniques which are not covered in this notebook.</p>

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<div class=" highlight hl-ipython2"><pre><span></span><span class="n">sns</span><span class="o">.</span><span class="n">set_style</span><span class="p">(</span><span class="s2">&quot;darkgrid&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">8</span><span class="p">,</span> <span class="mi">4</span><span class="p">))</span>
<span class="n">labeled_features</span><span class="p">[</span><span class="s1">&#39;failure&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">kind</span><span class="o">=</span><span class="s1">&#39;bar&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">&#39;Component failing&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;Count&#39;</span><span class="p">)</span>
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<p>Also, due to the class imbalance problem, it is important to look at evaluation metrics other than accuracy alone and compare those metrics to the baseline metrics which are computed when random chance is used to make predictions rather than a machine learning model.  The comparison will bring out the value and benefits of using a machine learning model better.</p>
<p>In the following, we use an evaluation function that computes many important evaluation metrics along with baseline metrics for classification problems. For a detailed explanation of the metrics, please refer to the <code>scikit-learn</code> documentation and a companion blog post (with examples in R, not Python), <a href="http://blog.revolutionanalytics.com/2016/03/com_class_eval_metrics_r.html">Computing Classification Evaluation Metrics in R</a> .</p>

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<div class=" highlight hl-ipython2"><pre><span></span><span class="kn">from</span> <span class="nn">sklearn.metrics</span> <span class="kn">import</span> <span class="n">confusion_matrix</span><span class="p">,</span> <span class="n">recall_score</span><span class="p">,</span> <span class="n">accuracy_score</span><span class="p">,</span> <span class="n">precision_score</span>

<span class="k">def</span> <span class="nf">Evaluate</span><span class="p">(</span><span class="n">predicted</span><span class="p">,</span> <span class="n">actual</span><span class="p">,</span> <span class="n">labels</span><span class="p">):</span>
    <span class="n">output_labels</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="n">output</span> <span class="o">=</span> <span class="p">[]</span>
    
    <span class="c1"># Calculate and display confusion matrix</span>
    <span class="n">cm</span> <span class="o">=</span> <span class="n">confusion_matrix</span><span class="p">(</span><span class="n">actual</span><span class="p">,</span> <span class="n">predicted</span><span class="p">,</span> <span class="n">labels</span><span class="o">=</span><span class="n">labels</span><span class="p">)</span>
    <span class="k">print</span><span class="p">(</span><span class="s1">&#39;Confusion matrix</span><span class="se">\n</span><span class="s1">- x-axis is true labels (none, comp1, etc.)</span><span class="se">\n</span><span class="s1">- y-axis is predicted labels&#39;</span><span class="p">)</span>
    <span class="k">print</span><span class="p">(</span><span class="n">cm</span><span class="p">)</span>
    
    <span class="c1"># Calculate precision, recall, and F1 score</span>
    <span class="n">accuracy</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="nb">float</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">trace</span><span class="p">(</span><span class="n">cm</span><span class="p">))</span> <span class="o">/</span> <span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">cm</span><span class="p">)]</span> <span class="o">*</span> <span class="nb">len</span><span class="p">(</span><span class="n">labels</span><span class="p">))</span>
    <span class="n">precision</span> <span class="o">=</span> <span class="n">precision_score</span><span class="p">(</span><span class="n">actual</span><span class="p">,</span> <span class="n">predicted</span><span class="p">,</span> <span class="n">average</span><span class="o">=</span><span class="bp">None</span><span class="p">,</span> <span class="n">labels</span><span class="o">=</span><span class="n">labels</span><span class="p">)</span>
    <span class="n">recall</span> <span class="o">=</span> <span class="n">recall_score</span><span class="p">(</span><span class="n">actual</span><span class="p">,</span> <span class="n">predicted</span><span class="p">,</span> <span class="n">average</span><span class="o">=</span><span class="bp">None</span><span class="p">,</span> <span class="n">labels</span><span class="o">=</span><span class="n">labels</span><span class="p">)</span>
    <span class="n">f1</span> <span class="o">=</span> <span class="mi">2</span> <span class="o">*</span> <span class="n">precision</span> <span class="o">*</span> <span class="n">recall</span> <span class="o">/</span> <span class="p">(</span><span class="n">precision</span> <span class="o">+</span> <span class="n">recall</span><span class="p">)</span>
    <span class="n">output</span><span class="o">.</span><span class="n">extend</span><span class="p">([</span><span class="n">accuracy</span><span class="o">.</span><span class="n">tolist</span><span class="p">(),</span> <span class="n">precision</span><span class="o">.</span><span class="n">tolist</span><span class="p">(),</span> <span class="n">recall</span><span class="o">.</span><span class="n">tolist</span><span class="p">(),</span> <span class="n">f1</span><span class="o">.</span><span class="n">tolist</span><span class="p">()])</span>
    <span class="n">output_labels</span><span class="o">.</span><span class="n">extend</span><span class="p">([</span><span class="s1">&#39;accuracy&#39;</span><span class="p">,</span> <span class="s1">&#39;precision&#39;</span><span class="p">,</span> <span class="s1">&#39;recall&#39;</span><span class="p">,</span> <span class="s1">&#39;F1&#39;</span><span class="p">])</span>
    
    <span class="c1"># Calculate the macro versions of these metrics</span>
    <span class="n">output</span><span class="o">.</span><span class="n">extend</span><span class="p">([[</span><span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">precision</span><span class="p">)]</span> <span class="o">*</span> <span class="nb">len</span><span class="p">(</span><span class="n">labels</span><span class="p">),</span>
                   <span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">recall</span><span class="p">)]</span> <span class="o">*</span> <span class="nb">len</span><span class="p">(</span><span class="n">labels</span><span class="p">),</span>
                   <span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">f1</span><span class="p">)]</span> <span class="o">*</span> <span class="nb">len</span><span class="p">(</span><span class="n">labels</span><span class="p">)])</span>
    <span class="n">output_labels</span><span class="o">.</span><span class="n">extend</span><span class="p">([</span><span class="s1">&#39;macro precision&#39;</span><span class="p">,</span> <span class="s1">&#39;macro recall&#39;</span><span class="p">,</span> <span class="s1">&#39;macro F1&#39;</span><span class="p">])</span>
    
    <span class="c1"># Find the one-vs.-all confusion matrix</span>
    <span class="n">cm_row_sums</span> <span class="o">=</span> <span class="n">cm</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">axis</span> <span class="o">=</span> <span class="mi">1</span><span class="p">)</span>
    <span class="n">cm_col_sums</span> <span class="o">=</span> <span class="n">cm</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">axis</span> <span class="o">=</span> <span class="mi">0</span><span class="p">)</span>
    <span class="n">s</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">))</span>
    <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">labels</span><span class="p">)):</span>
        <span class="n">v</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([[</span><span class="n">cm</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="n">i</span><span class="p">],</span>
                       <span class="n">cm_row_sums</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">-</span> <span class="n">cm</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="n">i</span><span class="p">]],</span>
                      <span class="p">[</span><span class="n">cm_col_sums</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">-</span> <span class="n">cm</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="n">i</span><span class="p">],</span>
                       <span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">cm</span><span class="p">)</span> <span class="o">+</span> <span class="n">cm</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="n">i</span><span class="p">]</span> <span class="o">-</span> <span class="p">(</span><span class="n">cm_row_sums</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">+</span> <span class="n">cm_col_sums</span><span class="p">[</span><span class="n">i</span><span class="p">])]])</span>
        <span class="n">s</span> <span class="o">+=</span> <span class="n">v</span>
    <span class="n">s_row_sums</span> <span class="o">=</span> <span class="n">s</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">axis</span> <span class="o">=</span> <span class="mi">1</span><span class="p">)</span>
    
    <span class="c1"># Add average accuracy and micro-averaged  precision/recall/F1</span>
    <span class="n">avg_accuracy</span> <span class="o">=</span> <span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">trace</span><span class="p">(</span><span class="n">s</span><span class="p">)</span> <span class="o">/</span> <span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">s</span><span class="p">)]</span> <span class="o">*</span> <span class="nb">len</span><span class="p">(</span><span class="n">labels</span><span class="p">)</span>
    <span class="n">micro_prf</span> <span class="o">=</span> <span class="p">[</span><span class="nb">float</span><span class="p">(</span><span class="n">s</span><span class="p">[</span><span class="mi">0</span><span class="p">,</span><span class="mi">0</span><span class="p">])</span> <span class="o">/</span> <span class="n">s_row_sums</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span> <span class="o">*</span> <span class="nb">len</span><span class="p">(</span><span class="n">labels</span><span class="p">)</span>
    <span class="n">output</span><span class="o">.</span><span class="n">extend</span><span class="p">([</span><span class="n">avg_accuracy</span><span class="p">,</span> <span class="n">micro_prf</span><span class="p">])</span>
    <span class="n">output_labels</span><span class="o">.</span><span class="n">extend</span><span class="p">([</span><span class="s1">&#39;average accuracy&#39;</span><span class="p">,</span>
                          <span class="s1">&#39;micro-averaged precision/recall/F1&#39;</span><span class="p">])</span>
    
    <span class="c1"># Compute metrics for the majority classifier</span>
    <span class="n">mc_index</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">where</span><span class="p">(</span><span class="n">cm_row_sums</span> <span class="o">==</span> <span class="n">np</span><span class="o">.</span><span class="n">max</span><span class="p">(</span><span class="n">cm_row_sums</span><span class="p">))[</span><span class="mi">0</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
    <span class="n">cm_row_dist</span> <span class="o">=</span> <span class="n">cm_row_sums</span> <span class="o">/</span> <span class="nb">float</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">cm</span><span class="p">))</span>
    <span class="n">mc_accuracy</span> <span class="o">=</span> <span class="mi">0</span> <span class="o">*</span> <span class="n">cm_row_dist</span><span class="p">;</span> <span class="n">mc_accuracy</span><span class="p">[</span><span class="n">mc_index</span><span class="p">]</span> <span class="o">=</span> <span class="n">cm_row_dist</span><span class="p">[</span><span class="n">mc_index</span><span class="p">]</span>
    <span class="n">mc_recall</span> <span class="o">=</span> <span class="mi">0</span> <span class="o">*</span> <span class="n">cm_row_dist</span><span class="p">;</span> <span class="n">mc_recall</span><span class="p">[</span><span class="n">mc_index</span><span class="p">]</span> <span class="o">=</span> <span class="mi">1</span>
    <span class="n">mc_precision</span> <span class="o">=</span> <span class="mi">0</span> <span class="o">*</span> <span class="n">cm_row_dist</span>
    <span class="n">mc_precision</span><span class="p">[</span><span class="n">mc_index</span><span class="p">]</span> <span class="o">=</span> <span class="n">cm_row_dist</span><span class="p">[</span><span class="n">mc_index</span><span class="p">]</span>
    <span class="n">mc_F1</span> <span class="o">=</span> <span class="mi">0</span> <span class="o">*</span> <span class="n">cm_row_dist</span><span class="p">;</span>
    <span class="n">mc_F1</span><span class="p">[</span><span class="n">mc_index</span><span class="p">]</span> <span class="o">=</span> <span class="mi">2</span> <span class="o">*</span> <span class="n">mc_precision</span><span class="p">[</span><span class="n">mc_index</span><span class="p">]</span> <span class="o">/</span> <span class="p">(</span><span class="n">mc_precision</span><span class="p">[</span><span class="n">mc_index</span><span class="p">]</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span>
    <span class="n">output</span><span class="o">.</span><span class="n">extend</span><span class="p">([</span><span class="n">mc_accuracy</span><span class="o">.</span><span class="n">tolist</span><span class="p">(),</span> <span class="n">mc_recall</span><span class="o">.</span><span class="n">tolist</span><span class="p">(),</span>
                   <span class="n">mc_precision</span><span class="o">.</span><span class="n">tolist</span><span class="p">(),</span> <span class="n">mc_F1</span><span class="o">.</span><span class="n">tolist</span><span class="p">()])</span>
    <span class="n">output_labels</span><span class="o">.</span><span class="n">extend</span><span class="p">([</span><span class="s1">&#39;majority class accuracy&#39;</span><span class="p">,</span> <span class="s1">&#39;majority class recall&#39;</span><span class="p">,</span>
                          <span class="s1">&#39;majority class precision&#39;</span><span class="p">,</span> <span class="s1">&#39;majority class F1&#39;</span><span class="p">])</span>
        
    <span class="c1"># Random accuracy and kappa</span>
    <span class="n">cm_col_dist</span> <span class="o">=</span> <span class="n">cm_col_sums</span> <span class="o">/</span> <span class="nb">float</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">cm</span><span class="p">))</span>
    <span class="n">exp_accuracy</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">cm_row_dist</span> <span class="o">*</span> <span class="n">cm_col_dist</span><span class="p">)]</span> <span class="o">*</span> <span class="nb">len</span><span class="p">(</span><span class="n">labels</span><span class="p">))</span>
    <span class="n">kappa</span> <span class="o">=</span> <span class="p">(</span><span class="n">accuracy</span> <span class="o">-</span> <span class="n">exp_accuracy</span><span class="p">)</span> <span class="o">/</span> <span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">exp_accuracy</span><span class="p">)</span>
    <span class="n">output</span><span class="o">.</span><span class="n">extend</span><span class="p">([</span><span class="n">exp_accuracy</span><span class="o">.</span><span class="n">tolist</span><span class="p">(),</span> <span class="n">kappa</span><span class="o">.</span><span class="n">tolist</span><span class="p">()])</span>
    <span class="n">output_labels</span><span class="o">.</span><span class="n">extend</span><span class="p">([</span><span class="s1">&#39;expected accuracy&#39;</span><span class="p">,</span> <span class="s1">&#39;kappa&#39;</span><span class="p">])</span>
    

    <span class="c1"># Random guess</span>
    <span class="n">rg_accuracy</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ones</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">labels</span><span class="p">))</span> <span class="o">/</span> <span class="nb">float</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">labels</span><span class="p">))</span>
    <span class="n">rg_precision</span> <span class="o">=</span> <span class="n">cm_row_dist</span>
    <span class="n">rg_recall</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ones</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">labels</span><span class="p">))</span> <span class="o">/</span> <span class="nb">float</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">labels</span><span class="p">))</span>
    <span class="n">rg_F1</span> <span class="o">=</span> <span class="mi">2</span> <span class="o">*</span> <span class="n">cm_row_dist</span> <span class="o">/</span> <span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">labels</span><span class="p">)</span> <span class="o">*</span> <span class="n">cm_row_dist</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span>
    <span class="n">output</span><span class="o">.</span><span class="n">extend</span><span class="p">([</span><span class="n">rg_accuracy</span><span class="o">.</span><span class="n">tolist</span><span class="p">(),</span> <span class="n">rg_precision</span><span class="o">.</span><span class="n">tolist</span><span class="p">(),</span>
                   <span class="n">rg_recall</span><span class="o">.</span><span class="n">tolist</span><span class="p">(),</span> <span class="n">rg_F1</span><span class="o">.</span><span class="n">tolist</span><span class="p">()])</span>
    <span class="n">output_labels</span><span class="o">.</span><span class="n">extend</span><span class="p">([</span><span class="s1">&#39;random guess accuracy&#39;</span><span class="p">,</span> <span class="s1">&#39;random guess precision&#39;</span><span class="p">,</span>
                          <span class="s1">&#39;random guess recall&#39;</span><span class="p">,</span> <span class="s1">&#39;random guess F1&#39;</span><span class="p">])</span>
    
    <span class="c1"># Random weighted guess</span>
    <span class="n">rwg_accuracy</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ones</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">labels</span><span class="p">))</span> <span class="o">*</span> <span class="nb">sum</span><span class="p">(</span><span class="n">cm_row_dist</span><span class="o">**</span><span class="mi">2</span><span class="p">)</span>
    <span class="n">rwg_precision</span> <span class="o">=</span> <span class="n">cm_row_dist</span>
    <span class="n">rwg_recall</span> <span class="o">=</span> <span class="n">cm_row_dist</span>
    <span class="n">rwg_F1</span> <span class="o">=</span> <span class="n">cm_row_dist</span>
    <span class="n">output</span><span class="o">.</span><span class="n">extend</span><span class="p">([</span><span class="n">rwg_accuracy</span><span class="o">.</span><span class="n">tolist</span><span class="p">(),</span> <span class="n">rwg_precision</span><span class="o">.</span><span class="n">tolist</span><span class="p">(),</span>
                   <span class="n">rwg_recall</span><span class="o">.</span><span class="n">tolist</span><span class="p">(),</span> <span class="n">rwg_F1</span><span class="o">.</span><span class="n">tolist</span><span class="p">()])</span>
    <span class="n">output_labels</span><span class="o">.</span><span class="n">extend</span><span class="p">([</span><span class="s1">&#39;random weighted guess accuracy&#39;</span><span class="p">,</span>
                          <span class="s1">&#39;random weighted guess precision&#39;</span><span class="p">,</span>
                          <span class="s1">&#39;random weighted guess recall&#39;</span><span class="p">,</span>
                          <span class="s1">&#39;random weighted guess F1&#39;</span><span class="p">])</span>

    <span class="n">output_df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">output</span><span class="p">,</span> <span class="n">columns</span><span class="o">=</span><span class="n">labels</span><span class="p">)</span>
    <span class="n">output_df</span><span class="o">.</span><span class="n">index</span> <span class="o">=</span> <span class="n">output_labels</span>
                  
    <span class="k">return</span> <span class="n">output_df</span>
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<div class=" highlight hl-ipython2"><pre><span></span><span class="n">evaluation_results</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">test_result</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">test_results</span><span class="p">):</span>
    <span class="k">print</span><span class="p">(</span><span class="s1">&#39;</span><span class="se">\n</span><span class="s1">Split </span><span class="si">%d</span><span class="s1">:&#39;</span> <span class="o">%</span> <span class="p">(</span><span class="n">i</span><span class="o">+</span><span class="mi">1</span><span class="p">))</span>
    <span class="n">evaluation_result</span> <span class="o">=</span> <span class="n">Evaluate</span><span class="p">(</span><span class="n">actual</span> <span class="o">=</span> <span class="n">test_result</span><span class="p">[</span><span class="s1">&#39;failure&#39;</span><span class="p">],</span>
                                 <span class="n">predicted</span> <span class="o">=</span> <span class="n">test_result</span><span class="p">[</span><span class="s1">&#39;predicted_failure&#39;</span><span class="p">],</span>
                                 <span class="n">labels</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;none&#39;</span><span class="p">,</span> <span class="s1">&#39;comp1&#39;</span><span class="p">,</span> <span class="s1">&#39;comp2&#39;</span><span class="p">,</span> <span class="s1">&#39;comp3&#39;</span><span class="p">,</span> <span class="s1">&#39;comp4&#39;</span><span class="p">])</span>
    <span class="n">evaluation_results</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">evaluation_result</span><span class="p">)</span>
<span class="n">evaluation_results</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>  <span class="c1"># show full results for first split only</span>
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<pre>
Split 1:
Confusion matrix
- x-axis is true labels (none, comp1, etc.)
- y-axis is predicted labels
[[120285     21      0      4      3]
 [    18    515      2      5      2]
 [     0      1    867      0      1]
 [    12      0      2    373      1]
 [     2      1      6      0    498]]

Split 2:
Confusion matrix
- x-axis is true labels (none, comp1, etc.)
- y-axis is predicted labels
[[95957    13     0     4     3]
 [   19   400     1     1     1]
 [    0     1   707     0     0]
 [   12     0     2   291     1]
 [    2     2     4     0   392]]

Split 3:
Confusion matrix
- x-axis is true labels (none, comp1, etc.)
- y-axis is predicted labels
[[72415     7     0     4     3]
 [   17   299     1     1     2]
 [    0     1   555     0     0]
 [   11     0     0   212     1]
 [    2     0     3     0   275]]
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<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>none</th>
      <th>comp1</th>
      <th>comp2</th>
      <th>comp3</th>
      <th>comp4</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>accuracy</th>
      <td>0.999339</td>
      <td>0.999339</td>
      <td>0.999339</td>
      <td>0.999339</td>
      <td>0.999339</td>
    </tr>
    <tr>
      <th>precision</th>
      <td>0.999734</td>
      <td>0.957249</td>
      <td>0.988597</td>
      <td>0.976440</td>
      <td>0.986139</td>
    </tr>
    <tr>
      <th>recall</th>
      <td>0.999767</td>
      <td>0.950185</td>
      <td>0.997699</td>
      <td>0.961340</td>
      <td>0.982249</td>
    </tr>
    <tr>
      <th>F1</th>
      <td>0.999751</td>
      <td>0.953704</td>
      <td>0.993127</td>
      <td>0.968831</td>
      <td>0.984190</td>
    </tr>
    <tr>
      <th>macro precision</th>
      <td>0.981632</td>
      <td>0.981632</td>
      <td>0.981632</td>
      <td>0.981632</td>
      <td>0.981632</td>
    </tr>
    <tr>
      <th>macro recall</th>
      <td>0.978248</td>
      <td>0.978248</td>
      <td>0.978248</td>
      <td>0.978248</td>
      <td>0.978248</td>
    </tr>
    <tr>
      <th>macro F1</th>
      <td>0.979920</td>
      <td>0.979920</td>
      <td>0.979920</td>
      <td>0.979920</td>
      <td>0.979920</td>
    </tr>
    <tr>
      <th>average accuracy</th>
      <td>0.999736</td>
      <td>0.999736</td>
      <td>0.999736</td>
      <td>0.999736</td>
      <td>0.999736</td>
    </tr>
    <tr>
      <th>micro-averaged precision/recall/F1</th>
      <td>0.999339</td>
      <td>0.999339</td>
      <td>0.999339</td>
      <td>0.999339</td>
      <td>0.999339</td>
    </tr>
    <tr>
      <th>majority class accuracy</th>
      <td>0.981194</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
    </tr>
    <tr>
      <th>majority class recall</th>
      <td>1.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
    </tr>
    <tr>
      <th>majority class precision</th>
      <td>0.981194</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
    </tr>
    <tr>
      <th>majority class F1</th>
      <td>0.990508</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
    </tr>
    <tr>
      <th>expected accuracy</th>
      <td>0.962870</td>
      <td>0.962870</td>
      <td>0.962870</td>
      <td>0.962870</td>
      <td>0.962870</td>
    </tr>
    <tr>
      <th>kappa</th>
      <td>0.982209</td>
      <td>0.982209</td>
      <td>0.982209</td>
      <td>0.982209</td>
      <td>0.982209</td>
    </tr>
    <tr>
      <th>random guess accuracy</th>
      <td>0.200000</td>
      <td>0.200000</td>
      <td>0.200000</td>
      <td>0.200000</td>
      <td>0.200000</td>
    </tr>
    <tr>
      <th>random guess precision</th>
      <td>0.981194</td>
      <td>0.004420</td>
      <td>0.007087</td>
      <td>0.003164</td>
      <td>0.004135</td>
    </tr>
    <tr>
      <th>random guess recall</th>
      <td>0.200000</td>
      <td>0.200000</td>
      <td>0.200000</td>
      <td>0.200000</td>
      <td>0.200000</td>
    </tr>
    <tr>
      <th>random guess F1</th>
      <td>0.332272</td>
      <td>0.008649</td>
      <td>0.013689</td>
      <td>0.006230</td>
      <td>0.008102</td>
    </tr>
    <tr>
      <th>random weighted guess accuracy</th>
      <td>0.962838</td>
      <td>0.962838</td>
      <td>0.962838</td>
      <td>0.962838</td>
      <td>0.962838</td>
    </tr>
    <tr>
      <th>random weighted guess precision</th>
      <td>0.981194</td>
      <td>0.004420</td>
      <td>0.007087</td>
      <td>0.003164</td>
      <td>0.004135</td>
    </tr>
    <tr>
      <th>random weighted guess recall</th>
      <td>0.981194</td>
      <td>0.004420</td>
      <td>0.007087</td>
      <td>0.003164</td>
      <td>0.004135</td>
    </tr>
    <tr>
      <th>random weighted guess F1</th>
      <td>0.981194</td>
      <td>0.004420</td>
      <td>0.007087</td>
      <td>0.003164</td>
      <td>0.004135</td>
    </tr>
  </tbody>
</table>
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<p>In predictive maintenance, we are often most concerned with how many of the actual failures were predicted by the model, i.e. the model's recall. (Recall becomes more important as the consequences of <em>false negatives</em> -- true failures that the model did not predict -- exceed the consequences of <em>false positives</em>, viz. false prediction of impending failure.) Below, we compare the recall rates for each failure type for the three models. The recall rates for all components as well as no failure are all above 90% meaning the model was able to capture above 90% of the failures correctly.</p>

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<div class=" highlight hl-ipython2"><pre><span></span><span class="n">recall_df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">([</span><span class="n">evaluation_results</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">&#39;recall&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">,</span>
                          <span class="n">evaluation_results</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">&#39;recall&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">,</span>
                          <span class="n">evaluation_results</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">&#39;recall&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">],</span>
                         <span class="n">columns</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;none&#39;</span><span class="p">,</span> <span class="s1">&#39;comp1&#39;</span><span class="p">,</span> <span class="s1">&#39;comp2&#39;</span><span class="p">,</span> <span class="s1">&#39;comp3&#39;</span><span class="p">,</span> <span class="s1">&#39;comp4&#39;</span><span class="p">],</span>
                         <span class="n">index</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;recall for first split&#39;</span><span class="p">,</span>
                                  <span class="s1">&#39;recall for second split&#39;</span><span class="p">,</span>
                                  <span class="s1">&#39;recall for third split&#39;</span><span class="p">])</span>
<span class="n">recall_df</span>
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      <th>recall for first split</th>
      <td>0.999767</td>
      <td>0.950185</td>
      <td>0.997699</td>
      <td>0.961340</td>
      <td>0.982249</td>
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      <th>recall for second split</th>
      <td>0.999792</td>
      <td>0.947867</td>
      <td>0.998588</td>
      <td>0.950980</td>
      <td>0.980000</td>
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      <th>recall for third split</th>
      <td>0.999807</td>
      <td>0.934375</td>
      <td>0.998201</td>
      <td>0.946429</td>
      <td>0.982143</td>
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<h2 id="Summary">Summary<a class="anchor-link" href="#Summary">&#182;</a></h2><p>In this notebook,  the steps of implementing a predictive maintenance model is provided using an example scenario where the goal is to predict failures due to certain components of a machine. Typical steps of predictive maintenance such as feature engineering, labelling, training and evaluation are explained using the example data sets. Predictive models are built both using Python packages and Azure Machine Learning Studio.</p>

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