report.html

<!DOCTYPE html>
<html>
<head><meta charset="utf-8" />
<title>customer_segments</title><script src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.1.10/require.min.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/2.0.3/jquery.min.js"></script>

<style type="text/css">
    /*!
*
* Twitter Bootstrap
*
*/
/*!
 * Bootstrap v3.3.7 (http://getbootstrap.com)
 * Copyright 2011-2016 Twitter, Inc.
 * Licensed under MIT (https://github.com/twbs/bootstrap/blob/master/LICENSE)
 */
/*! normalize.css v3.0.3 | MIT License | github.com/necolas/normalize.css */
html {
  font-family: sans-serif;
  -ms-text-size-adjust: 100%;
  -webkit-text-size-adjust: 100%;
}
body {
  margin: 0;
}
article,
aside,
details,
figcaption,
figure,
footer,
header,
hgroup,
main,
menu,
nav,
section,
summary {
  display: block;
}
audio,
canvas,
progress,
video {
  display: inline-block;
  vertical-align: baseline;
}
audio:not([controls]) {
  display: none;
  height: 0;
}
[hidden],
template {
  display: none;
}
a {
  background-color: transparent;
}
a:active,
a:hover {
  outline: 0;
}
abbr[title] {
  border-bottom: 1px dotted;
}
b,
strong {
  font-weight: bold;
}
dfn {
  font-style: italic;
}
h1 {
  font-size: 2em;
  margin: 0.67em 0;
}
mark {
  background: #ff0;
  color: #000;
}
small {
  font-size: 80%;
}
sub,
sup {
  font-size: 75%;
  line-height: 0;
  position: relative;
  vertical-align: baseline;
}
sup {
  top: -0.5em;
}
sub {
  bottom: -0.25em;
}
img {
  border: 0;
}
svg:not(:root) {
  overflow: hidden;
}
figure {
  margin: 1em 40px;
}
hr {
  box-sizing: content-box;
  height: 0;
}
pre {
  overflow: auto;
}
code,
kbd,
pre,
samp {
  font-family: monospace, monospace;
  font-size: 1em;
}
button,
input,
optgroup,
select,
textarea {
  color: inherit;
  font: inherit;
  margin: 0;
}
button {
  overflow: visible;
}
button,
select {
  text-transform: none;
}
button,
html input[type="button"],
input[type="reset"],
input[type="submit"] {
  -webkit-appearance: button;
  cursor: pointer;
}
button[disabled],
html input[disabled] {
  cursor: default;
}
button::-moz-focus-inner,
input::-moz-focus-inner {
  border: 0;
  padding: 0;
}
input {
  line-height: normal;
}
input[type="checkbox"],
input[type="radio"] {
  box-sizing: border-box;
  padding: 0;
}
input[type="number"]::-webkit-inner-spin-button,
input[type="number"]::-webkit-outer-spin-button {
  height: auto;
}
input[type="search"] {
  -webkit-appearance: textfield;
  box-sizing: content-box;
}
input[type="search"]::-webkit-search-cancel-button,
input[type="search"]::-webkit-search-decoration {
  -webkit-appearance: none;
}
fieldset {
  border: 1px solid #c0c0c0;
  margin: 0 2px;
  padding: 0.35em 0.625em 0.75em;
}
legend {
  border: 0;
  padding: 0;
}
textarea {
  overflow: auto;
}
optgroup {
  font-weight: bold;
}
table {
  border-collapse: collapse;
  border-spacing: 0;
}
td,
th {
  padding: 0;
}
/*! Source: https://github.com/h5bp/html5-boilerplate/blob/master/src/css/main.css */
@media print {
  *,
  *:before,
  *:after {
    background: transparent !important;
    color: #000 !important;
    box-shadow: none !important;
    text-shadow: none !important;
  }
  a,
  a:visited {
    text-decoration: underline;
  }
  a[href]:after {
    content: " (" attr(href) ")";
  }
  abbr[title]:after {
    content: " (" attr(title) ")";
  }
  a[href^="#"]:after,
  a[href^="javascript:"]:after {
    content: "";
  }
  pre,
  blockquote {
    border: 1px solid #999;
    page-break-inside: avoid;
  }
  thead {
    display: table-header-group;
  }
  tr,
  img {
    page-break-inside: avoid;
  }
  img {
    max-width: 100% !important;
  }
  p,
  h2,
  h3 {
    orphans: 3;
    widows: 3;
  }
  h2,
  h3 {
    page-break-after: avoid;
  }
  .navbar {
    display: none;
  }
  .btn > .caret,
  .dropup > .btn > .caret {
    border-top-color: #000 !important;
  }
  .label {
    border: 1px solid #000;
  }
  .table {
    border-collapse: collapse !important;
  }
  .table td,
  .table th {
    background-color: #fff !important;
  }
  .table-bordered th,
  .table-bordered td {
    border: 1px solid #ddd !important;
  }
}
@font-face {
  font-family: 'Glyphicons Halflings';
  src: url('../components/bootstrap/fonts/glyphicons-halflings-regular.eot');
  src: url('../components/bootstrap/fonts/glyphicons-halflings-regular.eot?#iefix') format('embedded-opentype'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.woff2') format('woff2'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.woff') format('woff'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.ttf') format('truetype'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.svg#glyphicons_halflingsregular') format('svg');
}
.glyphicon {
  position: relative;
  top: 1px;
  display: inline-block;
  font-family: 'Glyphicons Halflings';
  font-style: normal;
  font-weight: normal;
  line-height: 1;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
}
.glyphicon-asterisk:before {
  content: "\002a";
}
.glyphicon-plus:before {
  content: "\002b";
}
.glyphicon-euro:before,
.glyphicon-eur:before {
  content: "\20ac";
}
.glyphicon-minus:before {
  content: "\2212";
}
.glyphicon-cloud:before {
  content: "\2601";
}
.glyphicon-envelope:before {
  content: "\2709";
}
.glyphicon-pencil:before {
  content: "\270f";
}
.glyphicon-glass:before {
  content: "\e001";
}
.glyphicon-music:before {
  content: "\e002";
}
.glyphicon-search:before {
  content: "\e003";
}
.glyphicon-heart:before {
  content: "\e005";
}
.glyphicon-star:before {
  content: "\e006";
}
.glyphicon-star-empty:before {
  content: "\e007";
}
.glyphicon-user:before {
  content: "\e008";
}
.glyphicon-film:before {
  content: "\e009";
}
.glyphicon-th-large:before {
  content: "\e010";
}
.glyphicon-th:before {
  content: "\e011";
}
.glyphicon-th-list:before {
  content: "\e012";
}
.glyphicon-ok:before {
  content: "\e013";
}
.glyphicon-remove:before {
  content: "\e014";
}
.glyphicon-zoom-in:before {
  content: "\e015";
}
.glyphicon-zoom-out:before {
  content: "\e016";
}
.glyphicon-off:before {
  content: "\e017";
}
.glyphicon-signal:before {
  content: "\e018";
}
.glyphicon-cog:before {
  content: "\e019";
}
.glyphicon-trash:before {
  content: "\e020";
}
.glyphicon-home:before {
  content: "\e021";
}
.glyphicon-file:before {
  content: "\e022";
}
.glyphicon-time:before {
  content: "\e023";
}
.glyphicon-road:before {
  content: "\e024";
}
.glyphicon-download-alt:before {
  content: "\e025";
}
.glyphicon-download:before {
  content: "\e026";
}
.glyphicon-upload:before {
  content: "\e027";
}
.glyphicon-inbox:before {
  content: "\e028";
}
.glyphicon-play-circle:before {
  content: "\e029";
}
.glyphicon-repeat:before {
  content: "\e030";
}
.glyphicon-refresh:before {
  content: "\e031";
}
.glyphicon-list-alt:before {
  content: "\e032";
}
.glyphicon-lock:before {
  content: "\e033";
}
.glyphicon-flag:before {
  content: "\e034";
}
.glyphicon-headphones:before {
  content: "\e035";
}
.glyphicon-volume-off:before {
  content: "\e036";
}
.glyphicon-volume-down:before {
  content: "\e037";
}
.glyphicon-volume-up:before {
  content: "\e038";
}
.glyphicon-qrcode:before {
  content: "\e039";
}
.glyphicon-barcode:before {
  content: "\e040";
}
.glyphicon-tag:before {
  content: "\e041";
}
.glyphicon-tags:before {
  content: "\e042";
}
.glyphicon-book:before {
  content: "\e043";
}
.glyphicon-bookmark:before {
  content: "\e044";
}
.glyphicon-print:before {
  content: "\e045";
}
.glyphicon-camera:before {
  content: "\e046";
}
.glyphicon-font:before {
  content: "\e047";
}
.glyphicon-bold:before {
  content: "\e048";
}
.glyphicon-italic:before {
  content: "\e049";
}
.glyphicon-text-height:before {
  content: "\e050";
}
.glyphicon-text-width:before {
  content: "\e051";
}
.glyphicon-align-left:before {
  content: "\e052";
}
.glyphicon-align-center:before {
  content: "\e053";
}
.glyphicon-align-right:before {
  content: "\e054";
}
.glyphicon-align-justify:before {
  content: "\e055";
}
.glyphicon-list:before {
  content: "\e056";
}
.glyphicon-indent-left:before {
  content: "\e057";
}
.glyphicon-indent-right:before {
  content: "\e058";
}
.glyphicon-facetime-video:before {
  content: "\e059";
}
.glyphicon-picture:before {
  content: "\e060";
}
.glyphicon-map-marker:before {
  content: "\e062";
}
.glyphicon-adjust:before {
  content: "\e063";
}
.glyphicon-tint:before {
  content: "\e064";
}
.glyphicon-edit:before {
  content: "\e065";
}
.glyphicon-share:before {
  content: "\e066";
}
.glyphicon-check:before {
  content: "\e067";
}
.glyphicon-move:before {
  content: "\e068";
}
.glyphicon-step-backward:before {
  content: "\e069";
}
.glyphicon-fast-backward:before {
  content: "\e070";
}
.glyphicon-backward:before {
  content: "\e071";
}
.glyphicon-play:before {
  content: "\e072";
}
.glyphicon-pause:before {
  content: "\e073";
}
.glyphicon-stop:before {
  content: "\e074";
}
.glyphicon-forward:before {
  content: "\e075";
}
.glyphicon-fast-forward:before {
  content: "\e076";
}
.glyphicon-step-forward:before {
  content: "\e077";
}
.glyphicon-eject:before {
  content: "\e078";
}
.glyphicon-chevron-left:before {
  content: "\e079";
}
.glyphicon-chevron-right:before {
  content: "\e080";
}
.glyphicon-plus-sign:before {
  content: "\e081";
}
.glyphicon-minus-sign:before {
  content: "\e082";
}
.glyphicon-remove-sign:before {
  content: "\e083";
}
.glyphicon-ok-sign:before {
  content: "\e084";
}
.glyphicon-question-sign:before {
  content: "\e085";
}
.glyphicon-info-sign:before {
  content: "\e086";
}
.glyphicon-screenshot:before {
  content: "\e087";
}
.glyphicon-remove-circle:before {
  content: "\e088";
}
.glyphicon-ok-circle:before {
  content: "\e089";
}
.glyphicon-ban-circle:before {
  content: "\e090";
}
.glyphicon-arrow-left:before {
  content: "\e091";
}
.glyphicon-arrow-right:before {
  content: "\e092";
}
.glyphicon-arrow-up:before {
  content: "\e093";
}
.glyphicon-arrow-down:before {
  content: "\e094";
}
.glyphicon-share-alt:before {
  content: "\e095";
}
.glyphicon-resize-full:before {
  content: "\e096";
}
.glyphicon-resize-small:before {
  content: "\e097";
}
.glyphicon-exclamation-sign:before {
  content: "\e101";
}
.glyphicon-gift:before {
  content: "\e102";
}
.glyphicon-leaf:before {
  content: "\e103";
}
.glyphicon-fire:before {
  content: "\e104";
}
.glyphicon-eye-open:before {
  content: "\e105";
}
.glyphicon-eye-close:before {
  content: "\e106";
}
.glyphicon-warning-sign:before {
  content: "\e107";
}
.glyphicon-plane:before {
  content: "\e108";
}
.glyphicon-calendar:before {
  content: "\e109";
}
.glyphicon-random:before {
  content: "\e110";
}
.glyphicon-comment:before {
  content: "\e111";
}
.glyphicon-magnet:before {
  content: "\e112";
}
.glyphicon-chevron-up:before {
  content: "\e113";
}
.glyphicon-chevron-down:before {
  content: "\e114";
}
.glyphicon-retweet:before {
  content: "\e115";
}
.glyphicon-shopping-cart:before {
  content: "\e116";
}
.glyphicon-folder-close:before {
  content: "\e117";
}
.glyphicon-folder-open:before {
  content: "\e118";
}
.glyphicon-resize-vertical:before {
  content: "\e119";
}
.glyphicon-resize-horizontal:before {
  content: "\e120";
}
.glyphicon-hdd:before {
  content: "\e121";
}
.glyphicon-bullhorn:before {
  content: "\e122";
}
.glyphicon-bell:before {
  content: "\e123";
}
.glyphicon-certificate:before {
  content: "\e124";
}
.glyphicon-thumbs-up:before {
  content: "\e125";
}
.glyphicon-thumbs-down:before {
  content: "\e126";
}
.glyphicon-hand-right:before {
  content: "\e127";
}
.glyphicon-hand-left:before {
  content: "\e128";
}
.glyphicon-hand-up:before {
  content: "\e129";
}
.glyphicon-hand-down:before {
  content: "\e130";
}
.glyphicon-circle-arrow-right:before {
  content: "\e131";
}
.glyphicon-circle-arrow-left:before {
  content: "\e132";
}
.glyphicon-circle-arrow-up:before {
  content: "\e133";
}
.glyphicon-circle-arrow-down:before {
  content: "\e134";
}
.glyphicon-globe:before {
  content: "\e135";
}
.glyphicon-wrench:before {
  content: "\e136";
}
.glyphicon-tasks:before {
  content: "\e137";
}
.glyphicon-filter:before {
  content: "\e138";
}
.glyphicon-briefcase:before {
  content: "\e139";
}
.glyphicon-fullscreen:before {
  content: "\e140";
}
.glyphicon-dashboard:before {
  content: "\e141";
}
.glyphicon-paperclip:before {
  content: "\e142";
}
.glyphicon-heart-empty:before {
  content: "\e143";
}
.glyphicon-link:before {
  content: "\e144";
}
.glyphicon-phone:before {
  content: "\e145";
}
.glyphicon-pushpin:before {
  content: "\e146";
}
.glyphicon-usd:before {
  content: "\e148";
}
.glyphicon-gbp:before {
  content: "\e149";
}
.glyphicon-sort:before {
  content: "\e150";
}
.glyphicon-sort-by-alphabet:before {
  content: "\e151";
}
.glyphicon-sort-by-alphabet-alt:before {
  content: "\e152";
}
.glyphicon-sort-by-order:before {
  content: "\e153";
}
.glyphicon-sort-by-order-alt:before {
  content: "\e154";
}
.glyphicon-sort-by-attributes:before {
  content: "\e155";
}
.glyphicon-sort-by-attributes-alt:before {
  content: "\e156";
}
.glyphicon-unchecked:before {
  content: "\e157";
}
.glyphicon-expand:before {
  content: "\e158";
}
.glyphicon-collapse-down:before {
  content: "\e159";
}
.glyphicon-collapse-up:before {
  content: "\e160";
}
.glyphicon-log-in:before {
  content: "\e161";
}
.glyphicon-flash:before {
  content: "\e162";
}
.glyphicon-log-out:before {
  content: "\e163";
}
.glyphicon-new-window:before {
  content: "\e164";
}
.glyphicon-record:before {
  content: "\e165";
}
.glyphicon-save:before {
  content: "\e166";
}
.glyphicon-open:before {
  content: "\e167";
}
.glyphicon-saved:before {
  content: "\e168";
}
.glyphicon-import:before {
  content: "\e169";
}
.glyphicon-export:before {
  content: "\e170";
}
.glyphicon-send:before {
  content: "\e171";
}
.glyphicon-floppy-disk:before {
  content: "\e172";
}
.glyphicon-floppy-saved:before {
  content: "\e173";
}
.glyphicon-floppy-remove:before {
  content: "\e174";
}
.glyphicon-floppy-save:before {
  content: "\e175";
}
.glyphicon-floppy-open:before {
  content: "\e176";
}
.glyphicon-credit-card:before {
  content: "\e177";
}
.glyphicon-transfer:before {
  content: "\e178";
}
.glyphicon-cutlery:before {
  content: "\e179";
}
.glyphicon-header:before {
  content: "\e180";
}
.glyphicon-compressed:before {
  content: "\e181";
}
.glyphicon-earphone:before {
  content: "\e182";
}
.glyphicon-phone-alt:before {
  content: "\e183";
}
.glyphicon-tower:before {
  content: "\e184";
}
.glyphicon-stats:before {
  content: "\e185";
}
.glyphicon-sd-video:before {
  content: "\e186";
}
.glyphicon-hd-video:before {
  content: "\e187";
}
.glyphicon-subtitles:before {
  content: "\e188";
}
.glyphicon-sound-stereo:before {
  content: "\e189";
}
.glyphicon-sound-dolby:before {
  content: "\e190";
}
.glyphicon-sound-5-1:before {
  content: "\e191";
}
.glyphicon-sound-6-1:before {
  content: "\e192";
}
.glyphicon-sound-7-1:before {
  content: "\e193";
}
.glyphicon-copyright-mark:before {
  content: "\e194";
}
.glyphicon-registration-mark:before {
  content: "\e195";
}
.glyphicon-cloud-download:before {
  content: "\e197";
}
.glyphicon-cloud-upload:before {
  content: "\e198";
}
.glyphicon-tree-conifer:before {
  content: "\e199";
}
.glyphicon-tree-deciduous:before {
  content: "\e200";
}
.glyphicon-cd:before {
  content: "\e201";
}
.glyphicon-save-file:before {
  content: "\e202";
}
.glyphicon-open-file:before {
  content: "\e203";
}
.glyphicon-level-up:before {
  content: "\e204";
}
.glyphicon-copy:before {
  content: "\e205";
}
.glyphicon-paste:before {
  content: "\e206";
}
.glyphicon-alert:before {
  content: "\e209";
}
.glyphicon-equalizer:before {
  content: "\e210";
}
.glyphicon-king:before {
  content: "\e211";
}
.glyphicon-queen:before {
  content: "\e212";
}
.glyphicon-pawn:before {
  content: "\e213";
}
.glyphicon-bishop:before {
  content: "\e214";
}
.glyphicon-knight:before {
  content: "\e215";
}
.glyphicon-baby-formula:before {
  content: "\e216";
}
.glyphicon-tent:before {
  content: "\26fa";
}
.glyphicon-blackboard:before {
  content: "\e218";
}
.glyphicon-bed:before {
  content: "\e219";
}
.glyphicon-apple:before {
  content: "\f8ff";
}
.glyphicon-erase:before {
  content: "\e221";
}
.glyphicon-hourglass:before {
  content: "\231b";
}
.glyphicon-lamp:before {
  content: "\e223";
}
.glyphicon-duplicate:before {
  content: "\e224";
}
.glyphicon-piggy-bank:before {
  content: "\e225";
}
.glyphicon-scissors:before {
  content: "\e226";
}
.glyphicon-bitcoin:before {
  content: "\e227";
}
.glyphicon-btc:before {
  content: "\e227";
}
.glyphicon-xbt:before {
  content: "\e227";
}
.glyphicon-yen:before {
  content: "\00a5";
}
.glyphicon-jpy:before {
  content: "\00a5";
}
.glyphicon-ruble:before {
  content: "\20bd";
}
.glyphicon-rub:before {
  content: "\20bd";
}
.glyphicon-scale:before {
  content: "\e230";
}
.glyphicon-ice-lolly:before {
  content: "\e231";
}
.glyphicon-ice-lolly-tasted:before {
  content: "\e232";
}
.glyphicon-education:before {
  content: "\e233";
}
.glyphicon-option-horizontal:before {
  content: "\e234";
}
.glyphicon-option-vertical:before {
  content: "\e235";
}
.glyphicon-menu-hamburger:before {
  content: "\e236";
}
.glyphicon-modal-window:before {
  content: "\e237";
}
.glyphicon-oil:before {
  content: "\e238";
}
.glyphicon-grain:before {
  content: "\e239";
}
.glyphicon-sunglasses:before {
  content: "\e240";
}
.glyphicon-text-size:before {
  content: "\e241";
}
.glyphicon-text-color:before {
  content: "\e242";
}
.glyphicon-text-background:before {
  content: "\e243";
}
.glyphicon-object-align-top:before {
  content: "\e244";
}
.glyphicon-object-align-bottom:before {
  content: "\e245";
}
.glyphicon-object-align-horizontal:before {
  content: "\e246";
}
.glyphicon-object-align-left:before {
  content: "\e247";
}
.glyphicon-object-align-vertical:before {
  content: "\e248";
}
.glyphicon-object-align-right:before {
  content: "\e249";
}
.glyphicon-triangle-right:before {
  content: "\e250";
}
.glyphicon-triangle-left:before {
  content: "\e251";
}
.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;
  min-height: 27px;
  margin-left: 0px;
  padding-top: 11px;
  padding-bottom: 3px;
}
#maintoolbar .navbar-text {
  float: none;
  vertical-align: middle;
  text-align: right;
  margin-left: 5px;
  margin-right: 0px;
  margin-top: 0px;
}
.select-xs {
  height: 24px;
}
.pulse,
.dropdown-menu > li > a.pulse,
li.pulse > a.dropdown-toggle,
li.pulse.open > a.dropdown-toggle {
  background-color: #F37626;
  color: white;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
/** WARNING IF YOU ARE EDITTING THIS FILE, if this is a .css file, It has a lot
 * of chance of beeing generated from the ../less/[samename].less file, you can
 * try to get back the less file by reverting somme commit in history
 **/
/*
 * We'll try to get something pretty, so we
 * have some strange css to have the scroll bar on
 * the left with fix button on the top right of the tooltip
 */
@-moz-keyframes fadeOut {
  from {
    opacity: 1;
  }
  to {
    opacity: 0;
  }
}
@-webkit-keyframes fadeOut {
  from {
    opacity: 1;
  }
  to {
    opacity: 0;
  }
}
@-moz-keyframes fadeIn {
  from {
    opacity: 0;
  }
  to {
    opacity: 1;
  }
}
@-webkit-keyframes fadeIn {
  from {
    opacity: 0;
  }
  to {
    opacity: 1;
  }
}
/*properties of tooltip after "expand"*/
.bigtooltip {
  overflow: auto;
  height: 200px;
  -webkit-transition-property: height;
  -webkit-transition-duration: 500ms;
  -moz-transition-property: height;
  -moz-transition-duration: 500ms;
  transition-property: height;
  transition-duration: 500ms;
}
/*properties of tooltip before "expand"*/
.smalltooltip {
  -webkit-transition-property: height;
  -webkit-transition-duration: 500ms;
  -moz-transition-property: height;
  -moz-transition-duration: 500ms;
  transition-property: height;
  transition-duration: 500ms;
  text-overflow: ellipsis;
  overflow: hidden;
  height: 80px;
}
.tooltipbuttons {
  position: absolute;
  padding-right: 15px;
  top: 0px;
  right: 0px;
}
.tooltiptext {
  /*avoid the button to overlap on some docstring*/
  padding-right: 30px;
}
.ipython_tooltip {
  max-width: 700px;
  /*fade-in animation when inserted*/
  -webkit-animation: fadeOut 400ms;
  -moz-animation: fadeOut 400ms;
  animation: fadeOut 400ms;
  -webkit-animation: fadeIn 400ms;
  -moz-animation: fadeIn 400ms;
  animation: fadeIn 400ms;
  vertical-align: middle;
  background-color: #f7f7f7;
  overflow: visible;
  border: #ababab 1px solid;
  outline: none;
  padding: 3px;
  margin: 0px;
  padding-left: 7px;
  font-family: monospace;
  min-height: 50px;
  -moz-box-shadow: 0px 6px 10px -1px #adadad;
  -webkit-box-shadow: 0px 6px 10px -1px #adadad;
  box-shadow: 0px 6px 10px -1px #adadad;
  border-radius: 2px;
  position: absolute;
  z-index: 1000;
}
.ipython_tooltip a {
  float: right;
}
.ipython_tooltip .tooltiptext pre {
  border: 0;
  border-radius: 0;
  font-size: 100%;
  background-color: #f7f7f7;
}
.pretooltiparrow {
  left: 0px;
  margin: 0px;
  top: -16px;
  width: 40px;
  height: 16px;
  overflow: hidden;
  position: absolute;
}
.pretooltiparrow:before {
  background-color: #f7f7f7;
  border: 1px #ababab solid;
  z-index: 11;
  content: "";
  position: absolute;
  left: 15px;
  top: 10px;
  width: 25px;
  height: 25px;
  -webkit-transform: rotate(45deg);
  -moz-transform: rotate(45deg);
  -ms-transform: rotate(45deg);
  -o-transform: rotate(45deg);
}
ul.typeahead-list i {
  margin-left: -10px;
  width: 18px;
}
ul.typeahead-list {
  max-height: 80vh;
  overflow: auto;
}
ul.typeahead-list > li > a {
  /** Firefox bug **/
  /* see https://github.com/jupyter/notebook/issues/559 */
  white-space: normal;
}
.cmd-palette .modal-body {
  padding: 7px;
}
.cmd-palette form {
  background: white;
}
.cmd-palette input {
  outline: none;
}
.no-shortcut {
  display: none;
}
.command-shortcut:before {
  content: "(command)";
  padding-right: 3px;
  color: #777777;
}
.edit-shortcut:before {
  content: "(edit)";
  padding-right: 3px;
  color: #777777;
}
#find-and-replace #replace-preview .match,
#find-and-replace #replace-preview .insert {
  background-color: #BBDEFB;
  border-color: #90CAF9;
  border-style: solid;
  border-width: 1px;
  border-radius: 0px;
}
#find-and-replace #replace-preview .replace .match {
  background-color: #FFCDD2;
  border-color: #EF9A9A;
  border-radius: 0px;
}
#find-and-replace #replace-preview .replace .insert {
  background-color: #C8E6C9;
  border-color: #A5D6A7;
  border-radius: 0px;
}
#find-and-replace #replace-preview {
  max-height: 60vh;
  overflow: auto;
}
#find-and-replace #replace-preview pre {
  padding: 5px 10px;
}
.terminal-app {
  background: #EEE;
}
.terminal-app #header {
  background: #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);
}
.terminal-app .terminal {
  width: 100%;
  float: left;
  font-family: monospace;
  color: white;
  background: black;
  padding: 0.4em;
  border-radius: 2px;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.4);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.4);
}
.terminal-app .terminal,
.terminal-app .terminal dummy-screen {
  line-height: 1em;
  font-size: 14px;
}
.terminal-app .terminal .xterm-rows {
  padding: 10px;
}
.terminal-app .terminal-cursor {
  color: black;
  background: white;
}
.terminal-app #terminado-container {
  margin-top: 20px;
}
/*# sourceMappingURL=style.min.css.map */
    </style>
<style type="text/css">
    .highlight .hll { background-color: #ffffcc }
.highlight  { background: #f8f8f8; }
.highlight .c { color: #408080; font-style: italic } /* Comment */
.highlight .err { border: 1px solid #FF0000 } /* Error */
.highlight .k { color: #008000; font-weight: bold } /* Keyword */
.highlight .o { color: #666666 } /* Operator */
.highlight .ch { color: #408080; font-style: italic } /* Comment.Hashbang */
.highlight .cm { color: #408080; font-style: italic } /* Comment.Multiline */
.highlight .cp { color: #BC7A00 } /* Comment.Preproc */
.highlight .cpf { color: #408080; font-style: italic } /* Comment.PreprocFile */
.highlight .c1 { color: #408080; font-style: italic } /* Comment.Single */
.highlight .cs { color: #408080; font-style: italic } /* Comment.Special */
.highlight .gd { color: #A00000 } /* Generic.Deleted */
.highlight .ge { font-style: italic } /* Generic.Emph */
.highlight .gr { color: #FF0000 } /* Generic.Error */
.highlight .gh { color: #000080; font-weight: bold } /* Generic.Heading */
.highlight .gi { color: #00A000 } /* Generic.Inserted */
.highlight .go { color: #888888 } /* Generic.Output */
.highlight .gp { color: #000080; font-weight: bold } /* Generic.Prompt */
.highlight .gs { font-weight: bold } /* Generic.Strong */
.highlight .gu { color: #800080; font-weight: bold } /* Generic.Subheading */
.highlight .gt { color: #0044DD } /* Generic.Traceback */
.highlight .kc { color: #008000; font-weight: bold } /* Keyword.Constant */
.highlight .kd { color: #008000; font-weight: bold } /* Keyword.Declaration */
.highlight .kn { color: #008000; font-weight: bold } /* Keyword.Namespace */
.highlight .kp { color: #008000 } /* Keyword.Pseudo */
.highlight .kr { color: #008000; font-weight: bold } /* Keyword.Reserved */
.highlight .kt { color: #B00040 } /* Keyword.Type */
.highlight .m { color: #666666 } /* Literal.Number */
.highlight .s { color: #BA2121 } /* Literal.String */
.highlight .na { color: #7D9029 } /* Name.Attribute */
.highlight .nb { color: #008000 } /* Name.Builtin */
.highlight .nc { color: #0000FF; font-weight: bold } /* Name.Class */
.highlight .no { color: #880000 } /* Name.Constant */
.highlight .nd { color: #AA22FF } /* Name.Decorator */
.highlight .ni { color: #999999; font-weight: bold } /* Name.Entity */
.highlight .ne { color: #D2413A; font-weight: bold } /* Name.Exception */
.highlight .nf { color: #0000FF } /* Name.Function */
.highlight .nl { color: #A0A000 } /* Name.Label */
.highlight .nn { color: #0000FF; font-weight: bold } /* Name.Namespace */
.highlight .nt { color: #008000; font-weight: bold } /* Name.Tag */
.highlight .nv { color: #19177C } /* Name.Variable */
.highlight .ow { color: #AA22FF; font-weight: bold } /* Operator.Word */
.highlight .w { color: #bbbbbb } /* Text.Whitespace */
.highlight .mb { color: #666666 } /* Literal.Number.Bin */
.highlight .mf { color: #666666 } /* Literal.Number.Float */
.highlight .mh { color: #666666 } /* Literal.Number.Hex */
.highlight .mi { color: #666666 } /* Literal.Number.Integer */
.highlight .mo { color: #666666 } /* Literal.Number.Oct */
.highlight .sa { color: #BA2121 } /* Literal.String.Affix */
.highlight .sb { color: #BA2121 } /* Literal.String.Backtick */
.highlight .sc { color: #BA2121 } /* Literal.String.Char */
.highlight .dl { color: #BA2121 } /* Literal.String.Delimiter */
.highlight .sd { color: #BA2121; font-style: italic } /* Literal.String.Doc */
.highlight .s2 { color: #BA2121 } /* Literal.String.Double */
.highlight .se { color: #BB6622; font-weight: bold } /* Literal.String.Escape */
.highlight .sh { color: #BA2121 } /* Literal.String.Heredoc */
.highlight .si { color: #BB6688; font-weight: bold } /* Literal.String.Interpol */
.highlight .sx { color: #008000 } /* Literal.String.Other */
.highlight .sr { color: #BB6688 } /* Literal.String.Regex */
.highlight .s1 { color: #BA2121 } /* Literal.String.Single */
.highlight .ss { color: #19177C } /* Literal.String.Symbol */
.highlight .bp { color: #008000 } /* Name.Builtin.Pseudo */
.highlight .fm { color: #0000FF } /* Name.Function.Magic */
.highlight .vc { color: #19177C } /* Name.Variable.Class */
.highlight .vg { color: #19177C } /* Name.Variable.Global */
.highlight .vi { color: #19177C } /* Name.Variable.Instance */
.highlight .vm { color: #19177C } /* Name.Variable.Magic */
.highlight .il { color: #666666 } /* Literal.Number.Integer.Long */
    </style>
<style type="text/css">
    
/* Temporary definitions which will become obsolete with Notebook release 5.0 */
.ansi-black-fg { color: #3E424D; }
.ansi-black-bg { background-color: #3E424D; }
.ansi-black-intense-fg { color: #282C36; }
.ansi-black-intense-bg { background-color: #282C36; }
.ansi-red-fg { color: #E75C58; }
.ansi-red-bg { background-color: #E75C58; }
.ansi-red-intense-fg { color: #B22B31; }
.ansi-red-intense-bg { background-color: #B22B31; }
.ansi-green-fg { color: #00A250; }
.ansi-green-bg { background-color: #00A250; }
.ansi-green-intense-fg { color: #007427; }
.ansi-green-intense-bg { background-color: #007427; }
.ansi-yellow-fg { color: #DDB62B; }
.ansi-yellow-bg { background-color: #DDB62B; }
.ansi-yellow-intense-fg { color: #B27D12; }
.ansi-yellow-intense-bg { background-color: #B27D12; }
.ansi-blue-fg { color: #208FFB; }
.ansi-blue-bg { background-color: #208FFB; }
.ansi-blue-intense-fg { color: #0065CA; }
.ansi-blue-intense-bg { background-color: #0065CA; }
.ansi-magenta-fg { color: #D160C4; }
.ansi-magenta-bg { background-color: #D160C4; }
.ansi-magenta-intense-fg { color: #A03196; }
.ansi-magenta-intense-bg { background-color: #A03196; }
.ansi-cyan-fg { color: #60C6C8; }
.ansi-cyan-bg { background-color: #60C6C8; }
.ansi-cyan-intense-fg { color: #258F8F; }
.ansi-cyan-intense-bg { background-color: #258F8F; }
.ansi-white-fg { color: #C5C1B4; }
.ansi-white-bg { background-color: #C5C1B4; }
.ansi-white-intense-fg { color: #A1A6B2; }
.ansi-white-intense-bg { background-color: #A1A6B2; }

.ansi-bold { font-weight: bold; }

    </style>


<style type="text/css">
/* Overrides of notebook CSS for static HTML export */
body {
  overflow: visible;
  padding: 8px;
}

div#notebook {
  overflow: visible;
  border-top: none;
}@media print {
  div.cell {
    display: block;
    page-break-inside: avoid;
  } 
  div.output_wrapper { 
    display: block;
    page-break-inside: avoid; 
  }
  div.output { 
    display: block;
    page-break-inside: avoid; 
  }
}
</style>

<!-- Custom stylesheet, it must be in the same directory as the html file -->
<link rel="stylesheet" href="custom.css">

<!-- Loading mathjax macro -->
<!-- Load mathjax -->
    <script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS_HTML"></script>
    <!-- MathJax configuration -->
    <script type="text/x-mathjax-config">
    MathJax.Hub.Config({
        tex2jax: {
            inlineMath: [ ['$','$'], ["\\(","\\)"] ],
            displayMath: [ ['$$','$$'], ["\\[","\\]"] ],
            processEscapes: true,
            processEnvironments: true
        },
        // Center justify equations in code and markdown cells. Elsewhere
        // we use CSS to left justify single line equations in code cells.
        displayAlign: 'center',
        "HTML-CSS": {
            styles: {'.MathJax_Display': {"margin": 0}},
            linebreaks: { automatic: true }
        }
    });
    </script>
    <!-- End of mathjax configuration --></head>
<body>
  <div tabindex="-1" id="notebook" class="border-box-sizing">
    <div class="container" id="notebook-container">

<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h1 id="Machine-Learning-Engineer-Nanodegree">Machine Learning Engineer Nanodegree<a class="anchor-link" href="#Machine-Learning-Engineer-Nanodegree">&#182;</a></h1><h2 id="Unsupervised-Learning">Unsupervised Learning<a class="anchor-link" href="#Unsupervised-Learning">&#182;</a></h2><h2 id="Project:-Creating-Customer-Segments">Project: Creating Customer Segments<a class="anchor-link" href="#Project:-Creating-Customer-Segments">&#182;</a></h2>
</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Welcome to the third project of the Machine Learning Engineer Nanodegree! In this notebook, some template code has already been provided for you, and it will be your job to implement the additional functionality necessary to successfully complete this project. Sections that begin with <strong>'Implementation'</strong> in the header indicate that the following block of code will require additional functionality which you must provide. Instructions will be provided for each section and the specifics of the implementation are marked in the code block with a <code>'TODO'</code> statement. Please be sure to read the instructions carefully!</p>
<p>In addition to implementing code, there will be questions that you must answer which relate to the project and your implementation. Each section where you will answer a question is preceded by a <strong>'Question X'</strong> header. Carefully read each question and provide thorough answers in the following text boxes that begin with <strong>'Answer:'</strong>. Your project submission will be evaluated based on your answers to each of the questions and the implementation you provide.</p>
<blockquote><p><strong>Note:</strong> Code and Markdown cells can be executed using the <strong>Shift + Enter</strong> keyboard shortcut. In addition, Markdown cells can be edited by typically double-clicking the cell to enter edit mode.</p>
</blockquote>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h2 id="Getting-Started">Getting Started<a class="anchor-link" href="#Getting-Started">&#182;</a></h2><p>In this project, you will analyze a dataset containing data on various customers' annual spending amounts (reported in <em>monetary units</em>) of diverse product categories for internal structure. One goal of this project is to best describe the variation in the different types of customers that a wholesale distributor interacts with. Doing so would equip the distributor with insight into how to best structure their delivery service to meet the needs of each customer.</p>
<p>The dataset for this project can be found on the <a href="https://archive.ics.uci.edu/ml/datasets/Wholesale+customers">UCI Machine Learning Repository</a>. For the purposes of this project, the features <code>'Channel'</code> and <code>'Region'</code> will be excluded in the analysis — with focus instead on the six product categories recorded for customers.</p>
<p>Run the code block below to load the wholesale customers dataset, along with a few of the necessary Python libraries required for this project. You will know the dataset loaded successfully if the size of the dataset is reported.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[2]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Import libraries necessary for this project</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">from</span> <span class="nn">IPython.display</span> <span class="k">import</span> <span class="n">display</span> <span class="c1"># Allows the use of display() for DataFrames</span>

<span class="c1"># Import supplementary visualizations code visuals.py</span>
<span class="kn">import</span> <span class="nn">visuals</span> <span class="k">as</span> <span class="nn">vs</span>

<span class="c1"># Pretty display for notebooks</span>
<span class="o">%</span><span class="k">matplotlib</span> inline

<span class="c1"># Load the wholesale customers dataset</span>
<span class="k">try</span><span class="p">:</span>
    <span class="n">data</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="s2">&quot;customers.csv&quot;</span><span class="p">)</span>
    <span class="n">data</span><span class="o">.</span><span class="n">drop</span><span class="p">([</span><span class="s1">&#39;Region&#39;</span><span class="p">,</span> <span class="s1">&#39;Channel&#39;</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">inplace</span> <span class="o">=</span> <span class="kc">True</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Wholesale customers dataset has </span><span class="si">{}</span><span class="s2"> samples with </span><span class="si">{}</span><span class="s2"> features each.&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="o">*</span><span class="n">data</span><span class="o">.</span><span class="n">shape</span><span class="p">))</span>
<span class="k">except</span><span class="p">:</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Dataset could not be loaded. Is the dataset missing?&quot;</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>Wholesale customers dataset has 440 samples with 6 features each.
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h2 id="Data-Exploration">Data Exploration<a class="anchor-link" href="#Data-Exploration">&#182;</a></h2><p>In this section, you will begin exploring the data through visualizations and code to understand how each feature is related to the others. You will observe a statistical description of the dataset, consider the relevance of each feature, and select a few sample data points from the dataset which you will track through the course of this project.</p>
<p>Run the code block below to observe a statistical description of the dataset. Note that the dataset is composed of six important product categories: <strong>'Fresh'</strong>, <strong>'Milk'</strong>, <strong>'Grocery'</strong>, <strong>'Frozen'</strong>, <strong>'Detergents_Paper'</strong>, and <strong>'Delicatessen'</strong>. Consider what each category represents in terms of products you could purchase.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[3]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Display a description of the dataset</span>
<span class="n">display</span><span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">describe</span><span class="p">())</span>
<span class="n">data</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_html rendered_html output_subarea ">
<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>Fresh</th>
      <th>Milk</th>
      <th>Grocery</th>
      <th>Frozen</th>
      <th>Detergents_Paper</th>
      <th>Delicatessen</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>count</th>
      <td>440.000000</td>
      <td>440.000000</td>
      <td>440.000000</td>
      <td>440.000000</td>
      <td>440.000000</td>
      <td>440.000000</td>
    </tr>
    <tr>
      <th>mean</th>
      <td>12000.297727</td>
      <td>5796.265909</td>
      <td>7951.277273</td>
      <td>3071.931818</td>
      <td>2881.493182</td>
      <td>1524.870455</td>
    </tr>
    <tr>
      <th>std</th>
      <td>12647.328865</td>
      <td>7380.377175</td>
      <td>9503.162829</td>
      <td>4854.673333</td>
      <td>4767.854448</td>
      <td>2820.105937</td>
    </tr>
    <tr>
      <th>min</th>
      <td>3.000000</td>
      <td>55.000000</td>
      <td>3.000000</td>
      <td>25.000000</td>
      <td>3.000000</td>
      <td>3.000000</td>
    </tr>
    <tr>
      <th>25%</th>
      <td>3127.750000</td>
      <td>1533.000000</td>
      <td>2153.000000</td>
      <td>742.250000</td>
      <td>256.750000</td>
      <td>408.250000</td>
    </tr>
    <tr>
      <th>50%</th>
      <td>8504.000000</td>
      <td>3627.000000</td>
      <td>4755.500000</td>
      <td>1526.000000</td>
      <td>816.500000</td>
      <td>965.500000</td>
    </tr>
    <tr>
      <th>75%</th>
      <td>16933.750000</td>
      <td>7190.250000</td>
      <td>10655.750000</td>
      <td>3554.250000</td>
      <td>3922.000000</td>
      <td>1820.250000</td>
    </tr>
    <tr>
      <th>max</th>
      <td>112151.000000</td>
      <td>73498.000000</td>
      <td>92780.000000</td>
      <td>60869.000000</td>
      <td>40827.000000</td>
      <td>47943.000000</td>
    </tr>
  </tbody>
</table>
</div>
</div>

</div>

<div class="output_area">

<div class="prompt output_prompt">Out[3]:</div>


<div class="output_html rendered_html output_subarea output_execute_result">
<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>Fresh</th>
      <th>Milk</th>
      <th>Grocery</th>
      <th>Frozen</th>
      <th>Detergents_Paper</th>
      <th>Delicatessen</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>12669</td>
      <td>9656</td>
      <td>7561</td>
      <td>214</td>
      <td>2674</td>
      <td>1338</td>
    </tr>
    <tr>
      <th>1</th>
      <td>7057</td>
      <td>9810</td>
      <td>9568</td>
      <td>1762</td>
      <td>3293</td>
      <td>1776</td>
    </tr>
    <tr>
      <th>2</th>
      <td>6353</td>
      <td>8808</td>
      <td>7684</td>
      <td>2405</td>
      <td>3516</td>
      <td>7844</td>
    </tr>
    <tr>
      <th>3</th>
      <td>13265</td>
      <td>1196</td>
      <td>4221</td>
      <td>6404</td>
      <td>507</td>
      <td>1788</td>
    </tr>
    <tr>
      <th>4</th>
      <td>22615</td>
      <td>5410</td>
      <td>7198</td>
      <td>3915</td>
      <td>1777</td>
      <td>5185</td>
    </tr>
  </tbody>
</table>
</div>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="Implementation:-Selecting-Samples">Implementation: Selecting Samples<a class="anchor-link" href="#Implementation:-Selecting-Samples">&#182;</a></h3><p>To get a better understanding of the customers and how their data will transform through the analysis, it would be best to select a few sample data points and explore them in more detail. In the code block below, add <strong>three</strong> indices of your choice to the <code>indices</code> list which will represent the customers to track. It is suggested to try different sets of samples until you obtain customers that vary significantly from one another.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[4]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># TODO: Select three indices of your choice you wish to sample from the dataset</span>
<span class="n">indices</span> <span class="o">=</span> <span class="p">[</span><span class="mi">56</span><span class="p">,</span> <span class="mi">71</span><span class="p">,</span> <span class="mi">85</span><span class="p">]</span>
<span class="c1">#56 Coffe</span>
<span class="c1">#71 delis</span>
<span class="c1">#85 wholesale retailers</span>

<span class="c1"># Create a DataFrame of the chosen samples</span>
<span class="n">samples</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">data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">indices</span><span class="p">],</span> <span class="n">columns</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span><span class="o">.</span><span class="n">reset_index</span><span class="p">(</span><span class="n">drop</span> <span class="o">=</span> <span class="kc">True</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Chosen samples of wholesale customers dataset:&quot;</span><span class="p">)</span>
<span class="n">display</span><span class="p">(</span><span class="n">samples</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>Chosen samples of wholesale customers dataset:
</pre>
</div>
</div>

<div class="output_area">

<div class="prompt"></div>


<div class="output_html rendered_html output_subarea ">
<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>Fresh</th>
      <th>Milk</th>
      <th>Grocery</th>
      <th>Frozen</th>
      <th>Detergents_Paper</th>
      <th>Delicatessen</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>4098</td>
      <td>29892</td>
      <td>26866</td>
      <td>2616</td>
      <td>17740</td>
      <td>1340</td>
    </tr>
    <tr>
      <th>1</th>
      <td>18291</td>
      <td>1266</td>
      <td>21042</td>
      <td>5373</td>
      <td>4173</td>
      <td>14472</td>
    </tr>
    <tr>
      <th>2</th>
      <td>16117</td>
      <td>46197</td>
      <td>92780</td>
      <td>1026</td>
      <td>40827</td>
      <td>2944</td>
    </tr>
  </tbody>
</table>
</div>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="Question-1">Question 1<a class="anchor-link" href="#Question-1">&#182;</a></h3><p>Consider the total purchase cost of each product category and the statistical description of the dataset above for your sample customers.</p>
<ul>
<li>What kind of establishment (customer) could each of the three samples you've chosen represent?</li>
</ul>
<p><strong>Hint:</strong> Examples of establishments include places like markets, cafes, delis, wholesale retailers, among many others. Avoid using names for establishments, such as saying <em>"McDonalds"</em> when describing a sample customer as a restaurant. You can use the mean values for reference to compare your samples with. The mean values are as follows:</p>
<ul>
<li>Fresh: 12000.2977</li>
<li>Milk: 5796.2</li>
<li>Grocery: 7951.3</li>
<li>Detergents_paper: 2881.4</li>
<li>Delicatessen: 1524.8</li>
</ul>
<p>Knowing this, how do your samples compare? Does that help in driving your insight into what kind of establishments they might be?</p>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p><strong>Answer:</strong></p>
<p>I use Excel to organize the data, and then analyze the number of items purchased by each customer using the following formula:</p>
<p>Category / All Categories * 100%</p>
<p>This assumes how many items will be purchased by each category when each customer has the same amount.</p>
<p>The total number of sizes can be understood as the size of the customer's company.</p>
<h3 id="56:">56:<a class="anchor-link" href="#56:">&#182;</a></h3><ul>
<li>Fresh: 4098 (4.96%)</li>
<li>Milk: 29892 (36.21%)</li>
<li>Grocery: 26866 (32.54%)</li>
<li>Frozen: 2616(3.17%)</li>
<li>Detergents_paper: 17740 (21.49%)</li>
<li>Delicatessen: 1340 (1.62%)</li>
</ul>
<p>I think 56 is the reason for the coffee shop because the coffee shop always uses more milk to make latte drinks. And because you need to wash your guests' cups, cutlery, etc., you will need more detergent.</p>
<h3 id="71:">71:<a class="anchor-link" href="#71:">&#182;</a></h3><ul>
<li>Fresh: 18291 (28.31%)</li>
<li>Milk: 1266 (1.96%)</li>
<li>Grocery: 21042 (32.56%)</li>
<li>Frozen: 5373(8.32%)</li>
<li>Detergents_paper: 4173 (6.46%)</li>
<li>Delicatessen: 14472 (22.40%)</li>
</ul>
<p>I think the reason why 71 is a deli is because the deli will supply more cooked food and need fresh food to cook, as well as some seasonings.</p>
<h3 id="85:">85:<a class="anchor-link" href="#85:">&#182;</a></h3><ul>
<li>Fresh: 16117 (8.06%)</li>
<li>Milk: 46197 (23.11%)</li>
<li>Grocery: 92780 (46.42%)</li>
<li>Frozen: 1026(0.51%)</li>
<li>Detergents_paper: 40827 (20.42%)</li>
<li>Delicatessen: 2944 (1.47%)</li>
</ul>
<p>I think that 85 is the wholesale retailers because wholesale retailers sell a lot of groceries, detergents, etc., and also sell milk, cheese and other goods.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="Implementation:-Feature-Relevance">Implementation: Feature Relevance<a class="anchor-link" href="#Implementation:-Feature-Relevance">&#182;</a></h3><p>One interesting thought to consider is if one (or more) of the six product categories is actually relevant for understanding customer purchasing. That is to say, is it possible to determine whether customers purchasing some amount of one category of products will necessarily purchase some proportional amount of another category of products? We can make this determination quite easily by training a supervised regression learner on a subset of the data with one feature removed, and then score how well that model can predict the removed feature.</p>
<p>In the code block below, you will need to implement the following:</p>
<ul>
<li>Assign <code>new_data</code> a copy of the data by removing a feature of your choice using the <code>DataFrame.drop</code> function.</li>
<li>Use <code>sklearn.cross_validation.train_test_split</code> to split the dataset into training and testing sets.<ul>
<li>Use the removed feature as your target label. Set a <code>test_size</code> of <code>0.25</code> and set a <code>random_state</code>.</li>
</ul>
</li>
<li>Import a decision tree regressor, set a <code>random_state</code>, and fit the learner to the training data.</li>
<li>Report the prediction score of the testing set using the regressor's <code>score</code> function.</li>
</ul>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[5]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">sklearn.model_selection</span> <span class="k">import</span> <span class="n">train_test_split</span>
<span class="kn">from</span> <span class="nn">sklearn.tree</span> <span class="k">import</span> <span class="n">DecisionTreeRegressor</span>

<span class="c1"># TODO: Make a copy of the DataFrame, using the &#39;drop&#39; function to drop the given feature</span>
<span class="n">new_data</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">drop</span><span class="p">([</span><span class="s1">&#39;Grocery&#39;</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"># TODO: Split the data into training and testing sets(0.25) using the given feature as the target</span>
<span class="c1"># Set a random state.</span>
<span class="n">X_train</span><span class="p">,</span> <span class="n">X_test</span><span class="p">,</span> <span class="n">y_train</span><span class="p">,</span> <span class="n">y_test</span> <span class="o">=</span> <span class="n">train_test_split</span><span class="p">(</span><span class="n">new_data</span><span class="p">,</span> <span class="n">data</span><span class="o">.</span><span class="n">Grocery</span><span class="p">,</span> <span class="n">test_size</span><span class="o">=</span><span class="mf">0.25</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="mi">4</span><span class="p">)</span>

<span class="c1"># TODO: Create a decision tree regressor and fit it to the training set</span>
<span class="n">regressor</span> <span class="o">=</span> <span class="n">DecisionTreeRegressor</span><span class="p">(</span><span class="n">random_state</span><span class="o">=</span><span class="mi">4</span><span class="p">)</span>
<span class="n">regressor</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X_train</span><span class="p">,</span><span class="n">y_train</span><span class="p">)</span>
<span class="c1"># TODO: Report the score of the prediction using the testing set</span>
<span class="n">score</span> <span class="o">=</span> <span class="n">regressor</span><span class="o">.</span><span class="n">score</span><span class="p">(</span><span class="n">X_test</span><span class="p">,</span><span class="n">y_test</span><span class="p">)</span>

<span class="nb">print</span><span class="p">(</span><span class="n">score</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>0.7131841978038828
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="Question-2">Question 2<a class="anchor-link" href="#Question-2">&#182;</a></h3><ul>
<li>Which feature did you attempt to predict? </li>
<li>What was the reported prediction score? </li>
<li>Is this feature necessary for identifying customers' spending habits?</li>
</ul>
<p><strong>Hint:</strong> The coefficient of determination, <code>R^2</code>, is scored between 0 and 1, with 1 being a perfect fit. A negative <code>R^2</code> implies the model fails to fit the data. If you get a low score for a particular feature, that lends us to beleive that that feature point is hard to predict using the other features, thereby making it an important feature to consider when considering relevance.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p><strong>Answer:</strong></p>
<p>After trying to predict the "Grocery" feature, the predicted score on the test set was found to be 0.713. This represents the variables Fresh, Milk, Frozen, Detergents Paper and Delicatessen explaining the 71.3% variance of the Grocery variable. This variable can help improve customer spending habits, but we should be able to use other variables to understand the spending habits of most customers.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="Visualize-Feature-Distributions">Visualize Feature Distributions<a class="anchor-link" href="#Visualize-Feature-Distributions">&#182;</a></h3><p>To get a better understanding of the dataset, we can construct a scatter matrix of each of the six product features present in the data. If you found that the feature you attempted to predict above is relevant for identifying a specific customer, then the scatter matrix below may not show any correlation between that feature and the others. Conversely, if you believe that feature is not relevant for identifying a specific customer, the scatter matrix might show a correlation between that feature and another feature in the data. Run the code block below to produce a scatter matrix.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[6]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Produce a scatter matrix for each pair of features in the data</span>
<span class="n">pd</span><span class="o">.</span><span class="n">scatter_matrix</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">alpha</span> <span class="o">=</span> <span class="mf">0.3</span><span class="p">,</span> <span class="n">figsize</span> <span class="o">=</span> <span class="p">(</span><span class="mi">14</span><span class="p">,</span><span class="mi">8</span><span class="p">),</span> <span class="n">diagonal</span> <span class="o">=</span> <span class="s1">&#39;kde&#39;</span><span class="p">);</span>
<span class="n">data</span><span class="o">.</span><span class="n">corr</span><span class="p">()</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stderr output_text">
<pre>C:\Users\fgria\AppData\Local\conda\conda\envs\carnd-term1\lib\site-packages\ipykernel_launcher.py:2: FutureWarning: pandas.scatter_matrix is deprecated, use pandas.plotting.scatter_matrix instead
  
</pre>
</div>
</div>

<div class="output_area">

<div class="prompt output_prompt">Out[6]:</div>


<div class="output_html rendered_html output_subarea output_execute_result">
<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>Fresh</th>
      <th>Milk</th>
      <th>Grocery</th>
      <th>Frozen</th>
      <th>Detergents_Paper</th>
      <th>Delicatessen</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>Fresh</th>
      <td>1.000000</td>
      <td>0.100510</td>
      <td>-0.011854</td>
      <td>0.345881</td>
      <td>-0.101953</td>
      <td>0.244690</td>
    </tr>
    <tr>
      <th>Milk</th>
      <td>0.100510</td>
      <td>1.000000</td>
      <td>0.728335</td>
      <td>0.123994</td>
      <td>0.661816</td>
      <td>0.406368</td>
    </tr>
    <tr>
      <th>Grocery</th>
      <td>-0.011854</td>
      <td>0.728335</td>
      <td>1.000000</td>
      <td>-0.040193</td>
      <td>0.924641</td>
      <td>0.205497</td>
    </tr>
    <tr>
      <th>Frozen</th>
      <td>0.345881</td>
      <td>0.123994</td>
      <td>-0.040193</td>
      <td>1.000000</td>
      <td>-0.131525</td>
      <td>0.390947</td>
    </tr>
    <tr>
      <th>Detergents_Paper</th>
      <td>-0.101953</td>
      <td>0.661816</td>
      <td>0.924641</td>
      <td>-0.131525</td>
      <td>1.000000</td>
      <td>0.069291</td>
    </tr>
    <tr>
      <th>Delicatessen</th>
      <td>0.244690</td>
      <td>0.406368</td>
      <td>0.205497</td>
      <td>0.390947</td>
      <td>0.069291</td>
      <td>1.000000</td>
    </tr>
  </tbody>
</table>
</div>
</div>

</div>

<div class="output_area">

<div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,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
"
>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="Question-3">Question 3<a class="anchor-link" href="#Question-3">&#182;</a></h3><ul>
<li>Using the scatter matrix as a reference, discuss the distribution of the dataset, specifically talk about the normality, outliers, large number of data points near 0 among others. If you need to sepearate out some of the plots individually to further accentuate your point, you may do so as well.</li>
<li>Are there any pairs of features which exhibit some degree of correlation? </li>
<li>Does this confirm or deny your suspicions about the relevance of the feature you attempted to predict? </li>
<li>How is the data for those features distributed?</li>
</ul>
<p><strong>Hint:</strong> Is the data normally distributed? Where do most of the data points lie? You can use <a href="https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.corr.html">corr()</a> to get the feature correlations and then visualize them using a <a href="http://seaborn.pydata.org/generated/seaborn.heatmap.html">heatmap</a>(the data that would be fed into the heatmap would be the correlation values, for eg: <code>data.corr()</code>) to gain further insight.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p><strong>Answer:</strong></p>
<p>Based on the above information, we can observe that the Grocery features correspond to Milk and Detergents. Detergent paper also seems to have a corresponding relationship with milk. Because Grocery is related to Milk and Detergents, this confirms that we suspect that Grocery functionality is not related to identifying specific customers. These data are biased to the right.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h2 id="Data-Preprocessing">Data Preprocessing<a class="anchor-link" href="#Data-Preprocessing">&#182;</a></h2><p>In this section, you will preprocess the data to create a better representation of customers by performing a scaling on the data and detecting (and optionally removing) outliers. Preprocessing data is often times a critical step in assuring that results you obtain from your analysis are significant and meaningful.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="Implementation:-Feature-Scaling">Implementation: Feature Scaling<a class="anchor-link" href="#Implementation:-Feature-Scaling">&#182;</a></h3><p>If data is not normally distributed, especially if the mean and median vary significantly (indicating a large skew), it is most <a href="http://econbrowser.com/archives/2014/02/use-of-logarithms-in-economics">often appropriate</a> to apply a non-linear scaling — particularly for financial data. One way to achieve this scaling is by using a <a href="http://scipy.github.io/devdocs/generated/scipy.stats.boxcox.html">Box-Cox test</a>, which calculates the best power transformation of the data that reduces skewness. A simpler approach which can work in most cases would be applying the natural logarithm.</p>
<p>In the code block below, you will need to implement the following:</p>
<ul>
<li>Assign a copy of the data to <code>log_data</code> after applying logarithmic scaling. Use the <code>np.log</code> function for this.</li>
<li>Assign a copy of the sample data to <code>log_samples</code> after applying logarithmic scaling. Again, use <code>np.log</code>.</li>
</ul>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[199]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># TODO: Scale the data using the natural logarithm</span>
<span class="n">log_data</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>

<span class="c1"># TODO: Scale the sample data using the natural logarithm</span>
<span class="n">log_samples</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="n">samples</span><span class="p">)</span>

<span class="c1"># Produce a scatter matrix for each pair of newly-transformed features</span>
<span class="n">pd</span><span class="o">.</span><span class="n">scatter_matrix</span><span class="p">(</span><span class="n">log_data</span><span class="p">,</span> <span class="n">alpha</span> <span class="o">=</span> <span class="mf">0.3</span><span class="p">,</span> <span class="n">figsize</span> <span class="o">=</span> <span class="p">(</span><span class="mi">14</span><span class="p">,</span><span class="mi">8</span><span class="p">),</span> <span class="n">diagonal</span> <span class="o">=</span> <span class="s1">&#39;kde&#39;</span><span class="p">);</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stderr output_text">
<pre>C:\Users\fgria\AppData\Local\conda\conda\envs\carnd-term1\lib\site-packages\ipykernel_launcher.py:8: FutureWarning: pandas.scatter_matrix is deprecated, use pandas.plotting.scatter_matrix instead
  
</pre>
</div>
</div>

<div class="output_area">

<div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,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
"
>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="Observation">Observation<a class="anchor-link" href="#Observation">&#182;</a></h3><p>After applying a natural logarithm scaling to the data, the distribution of each feature should appear much more normal. For any pairs of features you may have identified earlier as being correlated, observe here whether that correlation is still present (and whether it is now stronger or weaker than before).</p>
<p>Run the code below to see how the sample data has changed after having the natural logarithm applied to it.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[200]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Display the log-transformed sample data</span>
<span class="n">display</span><span class="p">(</span><span class="n">log_samples</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_html rendered_html output_subarea ">
<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>Fresh</th>
      <th>Milk</th>
      <th>Grocery</th>
      <th>Frozen</th>
      <th>Detergents_Paper</th>
      <th>Delicatessen</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>8.318254</td>
      <td>10.305346</td>
      <td>10.198617</td>
      <td>7.869402</td>
      <td>9.783577</td>
      <td>7.200425</td>
    </tr>
    <tr>
      <th>1</th>
      <td>9.814164</td>
      <td>7.143618</td>
      <td>9.954276</td>
      <td>8.589142</td>
      <td>8.336390</td>
      <td>9.579971</td>
    </tr>
    <tr>
      <th>2</th>
      <td>9.687630</td>
      <td>10.740670</td>
      <td>11.437986</td>
      <td>6.933423</td>
      <td>10.617099</td>
      <td>7.987524</td>
    </tr>
  </tbody>
</table>
</div>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="Implementation:-Outlier-Detection">Implementation: Outlier Detection<a class="anchor-link" href="#Implementation:-Outlier-Detection">&#182;</a></h3><p>Detecting outliers in the data is extremely important in the data preprocessing step of any analysis. The presence of outliers can often skew results which take into consideration these data points. There are many "rules of thumb" for what constitutes an outlier in a dataset. Here, we will use <a href="http://datapigtechnologies.com/blog/index.php/highlighting-outliers-in-your-data-with-the-tukey-method/">Tukey's Method for identfying outliers</a>: An <em>outlier step</em> is calculated as 1.5 times the interquartile range (IQR). A data point with a feature that is beyond an outlier step outside of the IQR for that feature is considered abnormal.</p>
<p>In the code block below, you will need to implement the following:</p>
<ul>
<li>Assign the value of the 25th percentile for the given feature to <code>Q1</code>. Use <code>np.percentile</code> for this.</li>
<li>Assign the value of the 75th percentile for the given feature to <code>Q3</code>. Again, use <code>np.percentile</code>.</li>
<li>Assign the calculation of an outlier step for the given feature to <code>step</code>.</li>
<li>Optionally remove data points from the dataset by adding indices to the <code>outliers</code> list.</li>
</ul>
<p><strong>NOTE:</strong> If you choose to remove any outliers, ensure that the sample data does not contain any of these points!<br>
Once you have performed this implementation, the dataset will be stored in the variable <code>good_data</code>.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[201]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># For each feature find the data points with extreme high or low values</span>
<span class="n">total_outliers</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">feature</span> <span class="ow">in</span> <span class="n">log_data</span><span class="o">.</span><span class="n">keys</span><span class="p">():</span>
    
    <span class="c1"># TODO: Calculate Q1 (25th percentile of the data) for the given feature</span>
    <span class="n">Q1</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">percentile</span><span class="p">(</span><span class="n">log_data</span><span class="p">[</span><span class="n">feature</span><span class="p">],</span> <span class="n">q</span><span class="o">=</span><span class="mi">25</span><span class="p">)</span>
    
    <span class="c1"># TODO: Calculate Q3 (75th percentile of the data) for the given feature</span>
    <span class="n">Q3</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">percentile</span><span class="p">(</span><span class="n">log_data</span><span class="p">[</span><span class="n">feature</span><span class="p">],</span> <span class="n">q</span><span class="o">=</span><span class="mi">75</span><span class="p">)</span>
    
    <span class="c1"># TODO: Use the interquartile range to calculate an outlier step (1.5 times the interquartile range)</span>
    <span class="n">step</span> <span class="o">=</span> <span class="p">(</span><span class="n">Q3</span><span class="o">-</span><span class="n">Q1</span><span class="p">)</span><span class="o">*</span><span class="mf">1.5</span>
    
    <span class="c1"># Display the outliers</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Data points considered outliers for the feature &#39;</span><span class="si">{}</span><span class="s2">&#39;:&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">feature</span><span class="p">))</span>
    <span class="n">out</span> <span class="o">=</span> <span class="n">log_data</span><span class="p">[</span><span class="o">~</span><span class="p">((</span><span class="n">log_data</span><span class="p">[</span><span class="n">feature</span><span class="p">]</span> <span class="o">&gt;=</span> <span class="n">Q1</span> <span class="o">-</span> <span class="n">step</span><span class="p">)</span> <span class="o">&amp;</span> <span class="p">(</span><span class="n">log_data</span><span class="p">[</span><span class="n">feature</span><span class="p">]</span> <span class="o">&lt;=</span> <span class="n">Q3</span> <span class="o">+</span> <span class="n">step</span><span class="p">))]</span>
    <span class="n">display</span><span class="p">(</span><span class="n">out</span><span class="p">)</span>
    <span class="n">total_outliers</span> <span class="o">+=</span> <span class="nb">list</span><span class="p">(</span><span class="n">out</span><span class="o">.</span><span class="n">index</span><span class="o">.</span><span class="n">values</span><span class="p">)</span>
<span class="c1"># OPTIONAL: Select the indices for data points you wish to remove</span>
<span class="c1">#print</span>
<span class="n">result</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">value_counts</span><span class="p">(</span><span class="n">total_outliers</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Total outliers:&quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">result</span><span class="o">.</span><span class="n">index</span><span class="p">)))</span>
<span class="n">outliers</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">result</span><span class="p">[</span><span class="n">result</span><span class="o">.</span><span class="n">values</span><span class="o">&gt;</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">index</span><span class="o">.</span><span class="n">values</span><span class="p">)</span>
<span class="n">outliers</span><span class="o">.</span><span class="n">sort</span><span class="p">()</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;The list is considered as an outlier:&quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">outliers</span><span class="p">))</span>
<span class="c1"># Remove the outliers, if any were specified</span>
<span class="n">good_data</span> <span class="o">=</span> <span class="n">log_data</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="n">log_data</span><span class="o">.</span><span class="n">index</span><span class="p">[</span><span class="n">outliers</span><span class="p">])</span><span class="o">.</span><span class="n">reset_index</span><span class="p">(</span><span class="n">drop</span> <span class="o">=</span> <span class="kc">True</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>Data points considered outliers for the feature &#39;Fresh&#39;:
</pre>
</div>
</div>

<div class="output_area">

<div class="prompt"></div>


<div class="output_html rendered_html output_subarea ">
<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>Fresh</th>
      <th>Milk</th>
      <th>Grocery</th>
      <th>Frozen</th>
      <th>Detergents_Paper</th>
      <th>Delicatessen</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>65</th>
      <td>4.442651</td>
      <td>9.950323</td>
      <td>10.732651</td>
      <td>3.583519</td>
      <td>10.095388</td>
      <td>7.260523</td>
    </tr>
    <tr>
      <th>66</th>
      <td>2.197225</td>
      <td>7.335634</td>
      <td>8.911530</td>
      <td>5.164786</td>
      <td>8.151333</td>
      <td>3.295837</td>
    </tr>
    <tr>
      <th>81</th>
      <td>5.389072</td>
      <td>9.163249</td>
      <td>9.575192</td>
      <td>5.645447</td>
      <td>8.964184</td>
      <td>5.049856</td>
    </tr>
    <tr>
      <th>95</th>
      <td>1.098612</td>
      <td>7.979339</td>
      <td>8.740657</td>
      <td>6.086775</td>
      <td>5.407172</td>
      <td>6.563856</td>
    </tr>
    <tr>
      <th>96</th>
      <td>3.135494</td>
      <td>7.869402</td>
      <td>9.001839</td>
      <td>4.976734</td>
      <td>8.262043</td>
      <td>5.379897</td>
    </tr>
    <tr>
      <th>128</th>
      <td>4.941642</td>
      <td>9.087834</td>
      <td>8.248791</td>
      <td>4.955827</td>
      <td>6.967909</td>
      <td>1.098612</td>
    </tr>
    <tr>
      <th>171</th>
      <td>5.298317</td>
      <td>10.160530</td>
      <td>9.894245</td>
      <td>6.478510</td>
      <td>9.079434</td>
      <td>8.740337</td>
    </tr>
    <tr>
      <th>193</th>
      <td>5.192957</td>
      <td>8.156223</td>
      <td>9.917982</td>
      <td>6.865891</td>
      <td>8.633731</td>
      <td>6.501290</td>
    </tr>
    <tr>
      <th>218</th>
      <td>2.890372</td>
      <td>8.923191</td>
      <td>9.629380</td>
      <td>7.158514</td>
      <td>8.475746</td>
      <td>8.759669</td>
    </tr>
    <tr>
      <th>304</th>
      <td>5.081404</td>
      <td>8.917311</td>
      <td>10.117510</td>
      <td>6.424869</td>
      <td>9.374413</td>
      <td>7.787382</td>
    </tr>
    <tr>
      <th>305</th>
      <td>5.493061</td>
      <td>9.468001</td>
      <td>9.088399</td>
      <td>6.683361</td>
      <td>8.271037</td>
      <td>5.351858</td>
    </tr>
    <tr>
      <th>338</th>
      <td>1.098612</td>
      <td>5.808142</td>
      <td>8.856661</td>
      <td>9.655090</td>
      <td>2.708050</td>
      <td>6.309918</td>
    </tr>
    <tr>
      <th>353</th>
      <td>4.762174</td>
      <td>8.742574</td>
      <td>9.961898</td>
      <td>5.429346</td>
      <td>9.069007</td>
      <td>7.013016</td>
    </tr>
    <tr>
      <th>355</th>
      <td>5.247024</td>
      <td>6.588926</td>
      <td>7.606885</td>
      <td>5.501258</td>
      <td>5.214936</td>
      <td>4.844187</td>
    </tr>
    <tr>
      <th>357</th>
      <td>3.610918</td>
      <td>7.150701</td>
      <td>10.011086</td>
      <td>4.919981</td>
      <td>8.816853</td>
      <td>4.700480</td>
    </tr>
    <tr>
      <th>412</th>
      <td>4.574711</td>
      <td>8.190077</td>
      <td>9.425452</td>
      <td>4.584967</td>
      <td>7.996317</td>
      <td>4.127134</td>
    </tr>
  </tbody>
</table>
</div>
</div>

</div>

<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>Data points considered outliers for the feature &#39;Milk&#39;:
</pre>
</div>
</div>

<div class="output_area">

<div class="prompt"></div>


<div class="output_html rendered_html output_subarea ">
<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>Fresh</th>
      <th>Milk</th>
      <th>Grocery</th>
      <th>Frozen</th>
      <th>Detergents_Paper</th>
      <th>Delicatessen</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>86</th>
      <td>10.039983</td>
      <td>11.205013</td>
      <td>10.377047</td>
      <td>6.894670</td>
      <td>9.906981</td>
      <td>6.805723</td>
    </tr>
    <tr>
      <th>98</th>
      <td>6.220590</td>
      <td>4.718499</td>
      <td>6.656727</td>
      <td>6.796824</td>
      <td>4.025352</td>
      <td>4.882802</td>
    </tr>
    <tr>
      <th>154</th>
      <td>6.432940</td>
      <td>4.007333</td>
      <td>4.919981</td>
      <td>4.317488</td>
      <td>1.945910</td>
      <td>2.079442</td>
    </tr>
    <tr>
      <th>356</th>
      <td>10.029503</td>
      <td>4.897840</td>
      <td>5.384495</td>
      <td>8.057377</td>
      <td>2.197225</td>
      <td>6.306275</td>
    </tr>
  </tbody>
</table>
</div>
</div>

</div>

<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>Data points considered outliers for the feature &#39;Grocery&#39;:
</pre>
</div>
</div>

<div class="output_area">

<div class="prompt"></div>


<div class="output_html rendered_html output_subarea ">
<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>Fresh</th>
      <th>Milk</th>
      <th>Grocery</th>
      <th>Frozen</th>
      <th>Detergents_Paper</th>
      <th>Delicatessen</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>75</th>
      <td>9.923192</td>
      <td>7.036148</td>
      <td>1.098612</td>
      <td>8.390949</td>
      <td>1.098612</td>
      <td>6.882437</td>
    </tr>
    <tr>
      <th>154</th>
      <td>6.432940</td>
      <td>4.007333</td>
      <td>4.919981</td>
      <td>4.317488</td>
      <td>1.945910</td>
      <td>2.079442</td>
    </tr>
  </tbody>
</table>
</div>
</div>

</div>

<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>Data points considered outliers for the feature &#39;Frozen&#39;:
</pre>
</div>
</div>

<div class="output_area">

<div class="prompt"></div>


<div class="output_html rendered_html output_subarea ">
<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>Fresh</th>
      <th>Milk</th>
      <th>Grocery</th>
      <th>Frozen</th>
      <th>Detergents_Paper</th>
      <th>Delicatessen</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>38</th>
      <td>8.431853</td>
      <td>9.663261</td>
      <td>9.723703</td>
      <td>3.496508</td>
      <td>8.847360</td>
      <td>6.070738</td>
    </tr>
    <tr>
      <th>57</th>
      <td>8.597297</td>
      <td>9.203618</td>
      <td>9.257892</td>
      <td>3.637586</td>
      <td>8.932213</td>
      <td>7.156177</td>
    </tr>
    <tr>
      <th>65</th>
      <td>4.442651</td>
      <td>9.950323</td>
      <td>10.732651</td>
      <td>3.583519</td>
      <td>10.095388</td>
      <td>7.260523</td>
    </tr>
    <tr>
      <th>145</th>
      <td>10.000569</td>
      <td>9.034080</td>
      <td>10.457143</td>
      <td>3.737670</td>
      <td>9.440738</td>
      <td>8.396155</td>
    </tr>
    <tr>
      <th>175</th>
      <td>7.759187</td>
      <td>8.967632</td>
      <td>9.382106</td>
      <td>3.951244</td>
      <td>8.341887</td>
      <td>7.436617</td>
    </tr>
    <tr>
      <th>264</th>
      <td>6.978214</td>
      <td>9.177714</td>
      <td>9.645041</td>
      <td>4.110874</td>
      <td>8.696176</td>
      <td>7.142827</td>
    </tr>
    <tr>
      <th>325</th>
      <td>10.395650</td>
      <td>9.728181</td>
      <td>9.519735</td>
      <td>11.016479</td>
      <td>7.148346</td>
      <td>8.632128</td>
    </tr>
    <tr>
      <th>420</th>
      <td>8.402007</td>
      <td>8.569026</td>
      <td>9.490015</td>
      <td>3.218876</td>
      <td>8.827321</td>
      <td>7.239215</td>
    </tr>
    <tr>
      <th>429</th>
      <td>9.060331</td>
      <td>7.467371</td>
      <td>8.183118</td>
      <td>3.850148</td>
      <td>4.430817</td>
      <td>7.824446</td>
    </tr>
    <tr>
      <th>439</th>
      <td>7.932721</td>
      <td>7.437206</td>
      <td>7.828038</td>
      <td>4.174387</td>
      <td>6.167516</td>
      <td>3.951244</td>
    </tr>
  </tbody>
</table>
</div>
</div>

</div>

<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>Data points considered outliers for the feature &#39;Detergents_Paper&#39;:
</pre>
</div>
</div>

<div class="output_area">

<div class="prompt"></div>


<div class="output_html rendered_html output_subarea ">
<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>Fresh</th>
      <th>Milk</th>
      <th>Grocery</th>
      <th>Frozen</th>
      <th>Detergents_Paper</th>
      <th>Delicatessen</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>75</th>
      <td>9.923192</td>
      <td>7.036148</td>
      <td>1.098612</td>
      <td>8.390949</td>
      <td>1.098612</td>
      <td>6.882437</td>
    </tr>
    <tr>
      <th>161</th>
      <td>9.428190</td>
      <td>6.291569</td>
      <td>5.645447</td>
      <td>6.995766</td>
      <td>1.098612</td>
      <td>7.711101</td>
    </tr>
  </tbody>
</table>
</div>
</div>

</div>

<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>Data points considered outliers for the feature &#39;Delicatessen&#39;:
</pre>
</div>
</div>

<div class="output_area">

<div class="prompt"></div>


<div class="output_html rendered_html output_subarea ">
<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>Fresh</th>
      <th>Milk</th>
      <th>Grocery</th>
      <th>Frozen</th>
      <th>Detergents_Paper</th>
      <th>Delicatessen</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>66</th>
      <td>2.197225</td>
      <td>7.335634</td>
      <td>8.911530</td>
      <td>5.164786</td>
      <td>8.151333</td>
      <td>3.295837</td>
    </tr>
    <tr>
      <th>109</th>
      <td>7.248504</td>
      <td>9.724899</td>
      <td>10.274568</td>
      <td>6.511745</td>
      <td>6.728629</td>
      <td>1.098612</td>
    </tr>
    <tr>
      <th>128</th>
      <td>4.941642</td>
      <td>9.087834</td>
      <td>8.248791</td>
      <td>4.955827</td>
      <td>6.967909</td>
      <td>1.098612</td>
    </tr>
    <tr>
      <th>137</th>
      <td>8.034955</td>
      <td>8.997147</td>
      <td>9.021840</td>
      <td>6.493754</td>
      <td>6.580639</td>
      <td>3.583519</td>
    </tr>
    <tr>
      <th>142</th>
      <td>10.519646</td>
      <td>8.875147</td>
      <td>9.018332</td>
      <td>8.004700</td>
      <td>2.995732</td>
      <td>1.098612</td>
    </tr>
    <tr>
      <th>154</th>
      <td>6.432940</td>
      <td>4.007333</td>
      <td>4.919981</td>
      <td>4.317488</td>
      <td>1.945910</td>
      <td>2.079442</td>
    </tr>
    <tr>
      <th>183</th>
      <td>10.514529</td>
      <td>10.690808</td>
      <td>9.911952</td>
      <td>10.505999</td>
      <td>5.476464</td>
      <td>10.777768</td>
    </tr>
    <tr>
      <th>184</th>
      <td>5.789960</td>
      <td>6.822197</td>
      <td>8.457443</td>
      <td>4.304065</td>
      <td>5.811141</td>
      <td>2.397895</td>
    </tr>
    <tr>
      <th>187</th>
      <td>7.798933</td>
      <td>8.987447</td>
      <td>9.192075</td>
      <td>8.743372</td>
      <td>8.148735</td>
      <td>1.098612</td>
    </tr>
    <tr>
      <th>203</th>
      <td>6.368187</td>
      <td>6.529419</td>
      <td>7.703459</td>
      <td>6.150603</td>
      <td>6.860664</td>
      <td>2.890372</td>
    </tr>
    <tr>
      <th>233</th>
      <td>6.871091</td>
      <td>8.513988</td>
      <td>8.106515</td>
      <td>6.842683</td>
      <td>6.013715</td>
      <td>1.945910</td>
    </tr>
    <tr>
      <th>285</th>
      <td>10.602965</td>
      <td>6.461468</td>
      <td>8.188689</td>
      <td>6.948897</td>
      <td>6.077642</td>
      <td>2.890372</td>
    </tr>
    <tr>
      <th>289</th>
      <td>10.663966</td>
      <td>5.655992</td>
      <td>6.154858</td>
      <td>7.235619</td>
      <td>3.465736</td>
      <td>3.091042</td>
    </tr>
    <tr>
      <th>343</th>
      <td>7.431892</td>
      <td>8.848509</td>
      <td>10.177932</td>
      <td>7.283448</td>
      <td>9.646593</td>
      <td>3.610918</td>
    </tr>
  </tbody>
</table>
</div>
</div>

</div>

<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>Total outliers:42
The list is considered as an outlier:[65, 66, 75, 128, 154]
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="Question-4">Question 4<a class="anchor-link" href="#Question-4">&#182;</a></h3><ul>
<li>Are there any data points considered outliers for more than one feature based on the definition above? </li>
<li>Should these data points be removed from the dataset? </li>
<li>If any data points were added to the <code>outliers</code> list to be removed, explain why.</li>
</ul>
<p><strong> Hint: </strong> If you have datapoints that are outliers in multiple categories think about why that may be and if they warrant removal. Also note how k-means is affected by outliers and whether or not this plays a factor in your analysis of whether or not to remove them.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p><strong>Answer:</strong></p>
<p>According to the above information, 42 data are considered as outliers. However, there are only a few outliers with more than one feature (ie, numbers 65, 66, 75, 128, 154). I won't delete all outliers because they account for 9.5% of the data set. Deleting these anomalous data can cause us to lose important information needed to properly classify customer behavior. I only choose to delete 5 data points that are considered outliers in multiple features to reduce the likelihood of distorting the results.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h2 id="Feature-Transformation">Feature Transformation<a class="anchor-link" href="#Feature-Transformation">&#182;</a></h2><p>In this section you will use principal component analysis (PCA) to draw conclusions about the underlying structure of the wholesale customer data. Since using PCA on a dataset calculates the dimensions which best maximize variance, we will find which compound combinations of features best describe customers.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="Implementation:-PCA">Implementation: PCA<a class="anchor-link" href="#Implementation:-PCA">&#182;</a></h3><p>Now that the data has been scaled to a more normal distribution and has had any necessary outliers removed, we can now apply PCA to the <code>good_data</code> to discover which dimensions about the data best maximize the variance of features involved. In addition to finding these dimensions, PCA will also report the <em>explained variance ratio</em> of each dimension — how much variance within the data is explained by that dimension alone. Note that a component (dimension) from PCA can be considered a new "feature" of the space, however it is a composition of the original features present in the data.</p>
<p>In the code block below, you will need to implement the following:</p>
<ul>
<li>Import <code>sklearn.decomposition.PCA</code> and assign the results of fitting PCA in six dimensions with <code>good_data</code> to <code>pca</code>.</li>
<li>Apply a PCA transformation of <code>log_samples</code> using <code>pca.transform</code>, and assign the results to <code>pca_samples</code>.</li>
</ul>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[202]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">sklearn.decomposition</span> <span class="k">import</span> <span class="n">PCA</span>

<span class="c1"># TODO: Apply PCA by fitting the good data with the same number of dimensions as features</span>
<span class="n">pca</span> <span class="o">=</span> <span class="n">PCA</span><span class="p">(</span><span class="n">n_components</span><span class="o">=</span><span class="nb">len</span><span class="p">(</span><span class="n">good_data</span><span class="o">.</span><span class="n">columns</span><span class="p">))</span>
<span class="n">pca</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">good_data</span><span class="p">)</span>
<span class="c1"># TODO: Transform log_samples using the PCA fit above</span>
<span class="n">pca_samples</span> <span class="o">=</span> <span class="n">pca</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">log_samples</span><span class="p">)</span>

<span class="c1"># Generate PCA results plot</span>
<span class="n">pca_results</span> <span class="o">=</span> <span class="n">vs</span><span class="o">.</span><span class="n">pca_results</span><span class="p">(</span><span class="n">good_data</span><span class="p">,</span> <span class="n">pca</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,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
"
>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="Question-5">Question 5<a class="anchor-link" href="#Question-5">&#182;</a></h3><ul>
<li>How much variance in the data is explained<em> <strong>in total</strong> </em>by the first and second principal component? </li>
<li>How much variance in the data is explained by the first four principal components? </li>
<li>Using the visualization provided above, talk about each dimension and the cumulative variance explained by each, stressing upon which features are well represented by each dimension(both in terms of positive and negative variance explained). Discuss what the first four dimensions best represent in terms of customer spending.</li>
</ul>
<p><strong>Hint:</strong> A positive increase in a specific dimension corresponds with an <em>increase</em> of the <em>positive-weighted</em> features and a <em>decrease</em> of the <em>negative-weighted</em> features. The rate of increase or decrease is based on the individual feature weights.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p><strong>Answer:</strong></p>
<p>The first and second features, in total, explain approx. 70.6% of the variance in our data.
The first four components explain the variance of 93.11%.</p>
<p>For Dimension 1, the important weight on Detergents_Paper has a significant negative weight on milk and groceries. We can assume that this customer should be a store.(Considering that most of the extremely high values are negative, I take the opposite view to see this value.)</p>
<p>For Dimension 2, customers spend more on Freshs and a lot on Frozen and Delicatessen. This may represent a restaurant.(Considering that all are negative, I assume that they are all absolute values.)</p>
<p>Dimension 3 has a high Delicatessen and Frozen, as well as the low weight of milk, but Fresh has a great weight and others have a negative weight. This dimension may represent a deli.</p>
<p>Dimension 4 has a very high demand for Frozen, Detergents_Paper and Groceries have positive weights, while Fresh and Deli have negative values. This special need may be a store that specializes in selling frozen foods.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="Observation">Observation<a class="anchor-link" href="#Observation">&#182;</a></h3><p>Run the code below to see how the log-transformed sample data has changed after having a PCA transformation applied to it in six dimensions. Observe the numerical value for the first four dimensions of the sample points. Consider if this is consistent with your initial interpretation of the sample points.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[203]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Display sample log-data after having a PCA transformation applied</span>
<span class="n">display</span><span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="n">pca_samples</span><span class="p">,</span> <span class="mi">4</span><span class="p">),</span> <span class="n">columns</span> <span class="o">=</span> <span class="n">pca_results</span><span class="o">.</span><span class="n">index</span><span class="o">.</span><span class="n">values</span><span class="p">))</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_html rendered_html output_subarea ">
<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>Dimension 1</th>
      <th>Dimension 2</th>
      <th>Dimension 3</th>
      <th>Dimension 4</th>
      <th>Dimension 5</th>
      <th>Dimension 6</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>-3.9321</td>
      <td>-0.8289</td>
      <td>0.2152</td>
      <td>0.9953</td>
      <td>0.3950</td>
      <td>-0.2858</td>
    </tr>
    <tr>
      <th>1</th>
      <td>-1.4462</td>
      <td>-2.7836</td>
      <td>1.1083</td>
      <td>-0.3929</td>
      <td>-1.6836</td>
      <td>1.5910</td>
    </tr>
    <tr>
      <th>2</th>
      <td>-5.3316</td>
      <td>-1.8845</td>
      <td>-0.6957</td>
      <td>-0.1972</td>
      <td>0.5461</td>
      <td>0.3802</td>
    </tr>
  </tbody>
</table>
</div>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="Implementation:-Dimensionality-Reduction">Implementation: Dimensionality Reduction<a class="anchor-link" href="#Implementation:-Dimensionality-Reduction">&#182;</a></h3><p>When using principal component analysis, one of the main goals is to reduce the dimensionality of the data — in effect, reducing the complexity of the problem. Dimensionality reduction comes at a cost: Fewer dimensions used implies less of the total variance in the data is being explained. Because of this, the <em>cumulative explained variance ratio</em> is extremely important for knowing how many dimensions are necessary for the problem. Additionally, if a signifiant amount of variance is explained by only two or three dimensions, the reduced data can be visualized afterwards.</p>
<p>In the code block below, you will need to implement the following:</p>
<ul>
<li>Assign the results of fitting PCA in two dimensions with <code>good_data</code> to <code>pca</code>.</li>
<li>Apply a PCA transformation of <code>good_data</code> using <code>pca.transform</code>, and assign the results to <code>reduced_data</code>.</li>
<li>Apply a PCA transformation of <code>log_samples</code> using <code>pca.transform</code>, and assign the results to <code>pca_samples</code>.</li>
</ul>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[204]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># TODO: Apply PCA by fitting the good data with only two dimensions</span>
<span class="n">pca</span> <span class="o">=</span> <span class="n">PCA</span><span class="p">(</span><span class="n">n_components</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span>
<span class="n">pca</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">good_data</span><span class="p">)</span>

<span class="c1"># TODO: Transform the good data using the PCA fit above</span>
<span class="n">reduced_data</span> <span class="o">=</span> <span class="n">pca</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">good_data</span><span class="p">)</span>

<span class="c1"># TODO: Transform log_samples using the PCA fit above</span>
<span class="n">pca_samples</span> <span class="o">=</span> <span class="n">pca</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">log_samples</span><span class="p">)</span>

<span class="c1"># Create a DataFrame for the reduced data</span>
<span class="n">reduced_data</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">reduced_data</span><span class="p">,</span> <span class="n">columns</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;Dimension 1&#39;</span><span class="p">,</span> <span class="s1">&#39;Dimension 2&#39;</span><span class="p">])</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="Observation">Observation<a class="anchor-link" href="#Observation">&#182;</a></h3><p>Run the code below to see how the log-transformed sample data has changed after having a PCA transformation applied to it using only two dimensions. Observe how the values for the first two dimensions remains unchanged when compared to a PCA transformation in six dimensions.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[205]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Display sample log-data after applying PCA transformation in two dimensions</span>
<span class="n">display</span><span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="n">pca_samples</span><span class="p">,</span> <span class="mi">4</span><span class="p">),</span> <span class="n">columns</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;Dimension 1&#39;</span><span class="p">,</span> <span class="s1">&#39;Dimension 2&#39;</span><span class="p">]))</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_html rendered_html output_subarea ">
<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>Dimension 1</th>
      <th>Dimension 2</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>-3.9321</td>
      <td>-0.8289</td>
    </tr>
    <tr>
      <th>1</th>
      <td>-1.4462</td>
      <td>-2.7836</td>
    </tr>
    <tr>
      <th>2</th>
      <td>-5.3316</td>
      <td>-1.8845</td>
    </tr>
  </tbody>
</table>
</div>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h2 id="Visualizing-a-Biplot">Visualizing a Biplot<a class="anchor-link" href="#Visualizing-a-Biplot">&#182;</a></h2><p>A biplot is a scatterplot where each data point is represented by its scores along the principal components. The axes are the principal components (in this case <code>Dimension 1</code> and <code>Dimension 2</code>). In addition, the biplot shows the projection of the original features along the components. A biplot can help us interpret the reduced dimensions of the data, and discover relationships between the principal components and original features.</p>
<p>Run the code cell below to produce a biplot of the reduced-dimension data.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[206]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Create a biplot</span>
<span class="n">vs</span><span class="o">.</span><span class="n">biplot</span><span class="p">(</span><span class="n">good_data</span><span class="p">,</span> <span class="n">reduced_data</span><span class="p">,</span> <span class="n">pca</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt output_prompt">Out[206]:</div>


<div class="output_text output_subarea output_execute_result">
<pre>&lt;matplotlib.axes._subplots.AxesSubplot at 0x23ca68f93c8&gt;</pre>
</div>

</div>

<div class="output_area">

<div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,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
"
>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="Observation">Observation<a class="anchor-link" href="#Observation">&#182;</a></h3><p>Once we have the original feature projections (in red), it is easier to interpret the relative position of each data point in the scatterplot. For instance, a point the lower right corner of the figure will likely correspond to a customer that spends a lot on <code>'Milk'</code>, <code>'Grocery'</code> and <code>'Detergents_Paper'</code>, but not so much on the other product categories.</p>
<p>From the biplot, which of the original features are most strongly correlated with the first component? What about those that are associated with the second component? Do these observations agree with the pca_results plot you obtained earlier?</p>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h2 id="Clustering">Clustering<a class="anchor-link" href="#Clustering">&#182;</a></h2><p>In this section, you will choose to use either a K-Means clustering algorithm or a Gaussian Mixture Model clustering algorithm to identify the various customer segments hidden in the data. You will then recover specific data points from the clusters to understand their significance by transforming them back into their original dimension and scale.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="Question-6">Question 6<a class="anchor-link" href="#Question-6">&#182;</a></h3><ul>
<li>What are the advantages to using a K-Means clustering algorithm? </li>
<li>What are the advantages to using a Gaussian Mixture Model clustering algorithm? </li>
<li>Given your observations about the wholesale customer data so far, which of the two algorithms will you use and why?</li>
</ul>
<p><strong> Hint: </strong> Think about the differences between hard clustering and soft clustering and which would be appropriate for our dataset.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p><strong>Answer:</strong></p>
<p>The advantages of K-Means clustering: simplifying its basic assumptions, making the algorithm robust, reliable and fast.</p>
<p>Advantages of Gaussian Mixture Model Clustering: It is more flexible in terms of cluster covariance and can accommodate mixed membership.</p>
<p>For this data result, I would choose to use Gaussian mixture model clustering instead of K-Means. Because only one cluster is assigned to each data point, we may miss some hidden information in the data. For example, let's take the example of a supermarket customer in our sample. When doing PCA, it has a similar and high positive weight for multiple dimensions, ie it does not belong to another dimension. Therefore, the supermarket may be a combination of fresh produce shops/grocers/freezers. We will choose GMM so that we will not miss these cases.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="Implementation:-Creating-Clusters">Implementation: Creating Clusters<a class="anchor-link" href="#Implementation:-Creating-Clusters">&#182;</a></h3><p>Depending on the problem, the number of clusters that you expect to be in the data may already be known. When the number of clusters is not known <em>a priori</em>, there is no guarantee that a given number of clusters best segments the data, since it is unclear what structure exists in the data — if any. However, we can quantify the "goodness" of a clustering by calculating each data point's <em>silhouette coefficient</em>. The <a href="http://scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html">silhouette coefficient</a> for a data point measures how similar it is to its assigned cluster from -1 (dissimilar) to 1 (similar). Calculating the <em>mean</em> silhouette coefficient provides for a simple scoring method of a given clustering.</p>
<p>In the code block below, you will need to implement the following:</p>
<ul>
<li>Fit a clustering algorithm to the <code>reduced_data</code> and assign it to <code>clusterer</code>.</li>
<li>Predict the cluster for each data point in <code>reduced_data</code> using <code>clusterer.predict</code> and assign them to <code>preds</code>.</li>
<li>Find the cluster centers using the algorithm's respective attribute and assign them to <code>centers</code>.</li>
<li>Predict the cluster for each sample data point in <code>pca_samples</code> and assign them <code>sample_preds</code>.</li>
<li>Import <code>sklearn.metrics.silhouette_score</code> and calculate the silhouette score of <code>reduced_data</code> against <code>preds</code>.<ul>
<li>Assign the silhouette score to <code>score</code> and print the result.</li>
</ul>
</li>
</ul>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[207]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">sklearn.cluster</span> <span class="k">import</span> <span class="n">KMeans</span>
<span class="kn">from</span> <span class="nn">sklearn.mixture</span> <span class="k">import</span> <span class="n">GaussianMixture</span>
<span class="kn">from</span> <span class="nn">sklearn.metrics</span> <span class="k">import</span> <span class="n">silhouette_score</span>

<span class="c1"># TODO: Apply your clustering algorithm of choice to the reduced data </span>
<span class="c1">#clusterer = GaussianMixture(n_components=2)</span>
<span class="c1">#clusterer = KMeans(n_clusters=2)</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">10</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="o">-</span><span class="mi">1</span><span class="p">):</span>
    
    <span class="n">clusterer</span> <span class="o">=</span> <span class="n">GaussianMixture</span><span class="p">(</span><span class="n">n_components</span> <span class="o">=</span> <span class="n">i</span><span class="p">)</span>
    <span class="n">clusterer</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">reduced_data</span><span class="p">)</span>

    <span class="c1"># TODO: Predict the cluster for each data point</span>
    <span class="n">preds</span> <span class="o">=</span> <span class="n">clusterer</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">reduced_data</span><span class="p">)</span>

    <span class="c1"># TODO: Find the cluster centers</span>
    <span class="n">centers</span> <span class="o">=</span> <span class="n">clusterer</span><span class="o">.</span><span class="n">means_</span>

    <span class="c1"># TODO: Predict the cluster for each transformed sample data point</span>
    <span class="n">sample_preds</span> <span class="o">=</span> <span class="n">clusterer</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">pca_samples</span><span class="p">)</span>

    <span class="c1"># TODO: Calculate the mean silhouette coefficient for the number of clusters chosen</span>
    <span class="n">score</span> <span class="o">=</span> <span class="n">silhouette_score</span><span class="p">(</span><span class="n">reduced_data</span><span class="p">,</span> <span class="n">preds</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;For &quot;</span><span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">i</span><span class="p">)</span><span class="o">+</span><span class="s2">&quot; clusters, The silhouette score is : &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">score</span><span class="p">))</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>For 10 clusters, The silhouette score is : 0.3048922914969708
For 9 clusters, The silhouette score is : 0.26749981613854273
For 8 clusters, The silhouette score is : 0.31970032008545307
For 7 clusters, The silhouette score is : 0.3331538462846119
For 6 clusters, The silhouette score is : 0.3261394504711576
For 5 clusters, The silhouette score is : 0.32464171783094564
For 4 clusters, The silhouette score is : 0.34131789405069596
For 3 clusters, The silhouette score is : 0.3742018475403217
For 2 clusters, The silhouette score is : 0.42191684646261485
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="Question-7">Question 7<a class="anchor-link" href="#Question-7">&#182;</a></h3><ul>
<li>Report the silhouette score for several cluster numbers you tried. </li>
<li>Of these, which number of clusters has the best silhouette score?</li>
</ul>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p><strong>Answer:</strong></p>
<p>For 10 clusters, The silhouette score is : 0.3048922914969708</p>
<p>For 9 clusters, The silhouette score is : 0.26749981613854273</p>
<p>For 8 clusters, The silhouette score is : 0.31970032008545307</p>
<p>For 7 clusters, The silhouette score is : 0.3331538462846119</p>
<p>For 6 clusters, The silhouette score is : 0.3261394504711576</p>
<p>For 5 clusters, The silhouette score is : 0.32464171783094564</p>
<p>For 4 clusters, The silhouette score is : 0.34131789405069596</p>
<p>For 3 clusters, The silhouette score is : 0.3742018475403217</p>
<p>For 2 clusters, The silhouette score is : 0.42191684646261485</p>
<p>The two clusters have the highest scores.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="Cluster-Visualization">Cluster Visualization<a class="anchor-link" href="#Cluster-Visualization">&#182;</a></h3><p>Once you've chosen the optimal number of clusters for your clustering algorithm using the scoring metric above, you can now visualize the results by executing the code block below. Note that, for experimentation purposes, you are welcome to adjust the number of clusters for your clustering algorithm to see various visualizations. The final visualization provided should, however, correspond with the optimal number of clusters.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[208]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Display the results of the clustering from implementation</span>
<span class="n">vs</span><span class="o">.</span><span class="n">cluster_results</span><span class="p">(</span><span class="n">reduced_data</span><span class="p">,</span> <span class="n">preds</span><span class="p">,</span> <span class="n">centers</span><span class="p">,</span> <span class="n">pca_samples</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,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
"
>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="Implementation:-Data-Recovery">Implementation: Data Recovery<a class="anchor-link" href="#Implementation:-Data-Recovery">&#182;</a></h3><p>Each cluster present in the visualization above has a central point. These centers (or means) are not specifically data points from the data, but rather the <em>averages</em> of all the data points predicted in the respective clusters. For the problem of creating customer segments, a cluster's center point corresponds to <em>the average customer of that segment</em>. Since the data is currently reduced in dimension and scaled by a logarithm, we can recover the representative customer spending from these data points by applying the inverse transformations.</p>
<p>In the code block below, you will need to implement the following:</p>
<ul>
<li>Apply the inverse transform to <code>centers</code> using <code>pca.inverse_transform</code> and assign the new centers to <code>log_centers</code>.</li>
<li>Apply the inverse function of <code>np.log</code> to <code>log_centers</code> using <code>np.exp</code> and assign the true centers to <code>true_centers</code>.</li>
</ul>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[209]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># TODO: Inverse transform the centers</span>
<span class="n">log_centers</span> <span class="o">=</span> <span class="n">pca</span><span class="o">.</span><span class="n">inverse_transform</span><span class="p">(</span><span class="n">centers</span><span class="p">)</span>

<span class="c1"># TODO: Exponentiate the centers</span>
<span class="n">true_centers</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">exp</span><span class="p">(</span><span class="n">log_centers</span><span class="p">)</span>

<span class="c1"># Display the true centers</span>
<span class="n">segments</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;Segment </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">i</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="mi">0</span><span class="p">,</span><span class="nb">len</span><span class="p">(</span><span class="n">centers</span><span class="p">))]</span>
<span class="n">true_centers</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">np</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="n">true_centers</span><span class="p">),</span> <span class="n">columns</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span>
<span class="n">true_centers</span><span class="o">.</span><span class="n">index</span> <span class="o">=</span> <span class="n">segments</span>
<span class="n">display</span><span class="p">(</span><span class="n">true_centers</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_html rendered_html output_subarea ">
<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>Fresh</th>
      <th>Milk</th>
      <th>Grocery</th>
      <th>Frozen</th>
      <th>Detergents_Paper</th>
      <th>Delicatessen</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>Segment 0</th>
      <td>8953.0</td>
      <td>2114.0</td>
      <td>2765.0</td>
      <td>2075.0</td>
      <td>353.0</td>
      <td>732.0</td>
    </tr>
    <tr>
      <th>Segment 1</th>
      <td>3552.0</td>
      <td>7837.0</td>
      <td>12219.0</td>
      <td>870.0</td>
      <td>4696.0</td>
      <td>962.0</td>
    </tr>
  </tbody>
</table>
</div>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="Question-8">Question 8<a class="anchor-link" href="#Question-8">&#182;</a></h3><ul>
<li>Consider the total purchase cost of each product category for the representative data points above, and reference the statistical description of the dataset at the beginning of this project(specifically looking at the mean values for the various feature points). What set of establishments could each of the customer segments represent?</li>
</ul>
<p><strong>Hint:</strong> A customer who is assigned to <code>'Cluster X'</code> should best identify with the establishments represented by the feature set of <code>'Segment X'</code>. Think about what each segment represents in terms their values for the feature points chosen. Reference these values with the mean values to get some perspective into what kind of establishment they represent.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p><strong>Answer:</strong></p>
<p>Segment 0 assigned to Cluster 0 is likely to represent a fresh supermarket. This can be inferred based on its consistent purchase cost in the milk, grocery and frozen product categories and Fresh above the average purchase cost.</p>
<p>Segment 1 assigned to Cluster 1 is most likely to represent a restaurant because they spend an average on the average cost of groceries and milk as well as detergent paper.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="Question-9">Question 9<a class="anchor-link" href="#Question-9">&#182;</a></h3><ul>
<li>For each sample point, which customer segment from<em> <strong>Question 8</strong> </em>best represents it? </li>
<li>Are the predictions for each sample point consistent with this?*</li>
</ul>
<p>Run the code block below to find which cluster each sample point is predicted to be.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[210]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Display the predictions</span>
<span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">pred</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">sample_preds</span><span class="p">):</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Sample point&quot;</span><span class="p">,</span> <span class="n">i</span><span class="p">,</span> <span class="s2">&quot;predicted to be in Cluster&quot;</span><span class="p">,</span> <span class="n">pred</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>Sample point 0 predicted to be in Cluster 1
Sample point 1 predicted to be in Cluster 1
Sample point 2 predicted to be in Cluster 1
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p><strong>Answer:</strong></p>
<p>My guesses about sample points 0, 1 and 2 are cafes, deli and supermarkets. It seems that our prediction of sample point 1 is very close but not quite correct, and our predictions for sample point 0 and sample point 2 are incorrect. Looking at the visualization of our cluster in the previous section, you can know that the deli is closer to the center, more like a restaurant, but the other two are not the same as I predicted, or it may be because my country culture is different.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h2 id="Conclusion">Conclusion<a class="anchor-link" href="#Conclusion">&#182;</a></h2>
</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>In this final section, you will investigate ways that you can make use of the clustered data. First, you will consider how the different groups of customers, the <strong><em>customer segments</em></strong>, may be affected differently by a specific delivery scheme. Next, you will consider how giving a label to each customer (which <em>segment</em> that customer belongs to) can provide for additional features about the customer data. Finally, you will compare the <strong><em>customer segments</em></strong> to a hidden variable present in the data, to see whether the clustering identified certain relationships.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="Question-10">Question 10<a class="anchor-link" href="#Question-10">&#182;</a></h3><p>Companies will often run <a href="https://en.wikipedia.org/wiki/A/B_testing">A/B tests</a> when making small changes to their products or services to determine whether making that change will affect its customers positively or negatively. The wholesale distributor is considering changing its delivery service from currently 5 days a week to 3 days a week. However, the distributor will only make this change in delivery service for customers that react positively.</p>
<ul>
<li>How can the wholesale distributor use the customer segments to determine which customers, if any, would react positively to the change in delivery service?*</li>
</ul>
<p><strong>Hint:</strong> Can we assume the change affects all customers equally? How can we determine which group of customers it affects the most?</p>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p><strong>Answer:</strong></p>
<p>Through our data analysis above to identify the underlying types of customer segments, clustering wholesalers will be able to draw more meaningful assumptions about the expected behavior of customers in each segment before performing A/B testing. These hypotheses can then be tested on each subdivision separately to find more meaningful conclusions and to understand the impact of each individual customer segment. For example, by observing the definition of these two customer groups, wholesalers can come up with the initial assumption that “market/convenience store” customers (ie cluster 0) and “restaurant” customers (ie cluster 1) will make a difference Reaction. quantity of delivery. Restaurants may react negatively because they are more concerned with providing customers with fresh products. Reducing the delivery quantity to 3 days will force them to increase inventory levels (if possible) and maintain longer products, which may increase the corruption of certain products and may reduce the quality of the food they serve customers. On the other hand, wholesalers can come up with the assumption that “market/convenience store customers” may respond positively to the new timeline because they are more likely to have more inventory space to store the necessary inventory to supply their customers. They also don't pay attention to the "freshness" of their products like restaurants. These assumptions are then tested in different customer sample groups for each market segment to arrive at a final conclusion about the impact on each market segment.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="Question-11">Question 11<a class="anchor-link" href="#Question-11">&#182;</a></h3><p>Additional structure is derived from originally unlabeled data when using clustering techniques. Since each customer has a <strong><em>customer segment</em></strong> it best identifies with (depending on the clustering algorithm applied), we can consider <em>'customer segment'</em> as an <strong>engineered feature</strong> for the data. Assume the wholesale distributor recently acquired ten new customers and each provided estimates for anticipated annual spending of each product category. Knowing these estimates, the wholesale distributor wants to classify each new customer to a <strong><em>customer segment</em></strong> to determine the most appropriate delivery service.</p>
<ul>
<li>How can the wholesale distributor label the new customers using only their estimated product spending and the <strong>customer segment</strong> data?</li>
</ul>
<p><strong>Hint:</strong> A supervised learner could be used to train on the original customers. What would be the target variable?</p>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p><strong>Answer:</strong></p>
<p>As long as we have new engineering features to show how we can judge "delivery 5 days a week" or "delivery 3 days a week", we can use it as a target variable for supervised learning algorithms.
As long as there is a well-labeled data set, we can train supervised learning algorithms such as SVC, decision tree classifiers, etc. on it. Then classify ten new customers into one of the market segments.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="Visualizing-Underlying-Distributions">Visualizing Underlying Distributions<a class="anchor-link" href="#Visualizing-Underlying-Distributions">&#182;</a></h3><p>At the beginning of this project, it was discussed that the <code>'Channel'</code> and <code>'Region'</code> features would be excluded from the dataset so that the customer product categories were emphasized in the analysis. By reintroducing the <code>'Channel'</code> feature to the dataset, an interesting structure emerges when considering the same PCA dimensionality reduction applied earlier to the original dataset.</p>
<p>Run the code block below to see how each data point is labeled either <code>'HoReCa'</code> (Hotel/Restaurant/Cafe) or <code>'Retail'</code> the reduced space. In addition, you will find the sample points are circled in the plot, which will identify their labeling.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[211]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Display the clustering results based on &#39;Channel&#39; data</span>
<span class="n">vs</span><span class="o">.</span><span class="n">channel_results</span><span class="p">(</span><span class="n">reduced_data</span><span class="p">,</span> <span class="n">outliers</span><span class="p">,</span> <span class="n">pca_samples</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,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
"
>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="Question-12">Question 12<a class="anchor-link" href="#Question-12">&#182;</a></h3><ul>
<li>How well does the clustering algorithm and number of clusters you've chosen compare to this underlying distribution of Hotel/Restaurant/Cafe customers to Retailer customers? </li>
<li>Are there customer segments that would be classified as purely 'Retailers' or 'Hotels/Restaurants/Cafes' by this distribution? </li>
<li>Would you consider these classifications as consistent with your previous definition of the customer segments?</li>
</ul>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p><strong>Answer:</strong></p>
<p>Both the GMM algorithm and the number of clusters selected (2) are very similar to the base distribution shown in the previous figure.</p>
<p>Dimension 1 customers with less than -3 are classified as "Retailers" and customers with Dimension greater than 2 are classified as "Hotels/Restaurants/Cafes".</p>
<p>The customer base classified here matches the customer base that I previously defined in question 8 for the market and the red dot for the restaurant.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<blockquote><p><strong>Note</strong>: Once you have completed all of the code implementations and successfully answered each question above, you may finalize your work by exporting the iPython Notebook as an HTML document. You can do this by using the menu above and navigating to<br>
<strong>File -&gt; Download as -&gt; HTML (.html)</strong>. Include the finished document along with this notebook as your submission.</p>
</blockquote>

</div>
</div>
</div>
    </div>
  </div>
</body>

 
</html>