+import pandas as pd
+import plotly.plotly as py
+import time
+import copy
+# from plotly.graph_objs import *
+import plotly.graph_objs as go
+import plotly.figure_factory as ff
+from collections import defaultdict
+from IPython.display import display,Image
+from .exceptions import CufflinksError
+from .colors import normalize,get_scales,colorgen,to_rgba,get_colorscale
+from .utils import check_kwargs, deep_update, kwargs_from_keyword
+from . import tools
+from . import offline
+from . import auth
+from . import ta
+
+
+__TA_KWARGS = ['min_period','center','freq','how','rsi_upper','rsi_lower','boll_std','fast_period',
+ 'slow_period','signal_period','initial','af','open','high','low','close']
+
+
+[docs]def iplot_to_dict(data):
+
d=defaultdict(dict)
+
for i in data:
+
for k,v in list(i.items()):
+
d[i['name']][k]=v
+
return d
+
+[docs]def dict_to_iplot(d):
+
l=[]
+
for v in list(d.values()):
+
l.append(v)
+
return go.Data(l)
+
+
+def _to_iplot(self,colors=None,colorscale=None,kind='scatter',mode='lines',interpolation='linear',symbol='dot',size='12',fill=False,
+ width=3,dash='solid',sortbars=False,keys=False,bestfit=False,bestfit_colors=None,
+ mean=False,mean_colors=None,asDates=False,asTimestamp=False,text=None,**kwargs):
+ """
+ Generates a plotly Data object
+
+ Parameters
+ ----------
+ colors : list or dict
+ {key:color} to specify the color for each column
+ [colors] to use the colors in the defined order
+ colorscale : str
+ Color scale name
+ Only valid if 'colors' is null
+ See cufflinks.colors.scales() for available scales
+ kind : string
+ Kind of chart
+ scatter
+ bar
+ mode : string
+ Plotting mode for scatter trace
+ lines
+ markers
+ lines+markers
+ lines+text
+ markers+text
+ lines+markers+text
+ interpolation : string
+ Positioning of the connecting lines
+ linear
+ spline
+ vhv
+ hvh
+ vh
+ hv
+ symbol : string
+ The symbol that is drawn on the plot for each marker
+ Valid only when mode includes markers
+ dot
+ cross
+ diamond
+ square
+ triangle-down
+ triangle-left
+ triangle-right
+ triangle-up
+ x
+ size : string or int
+ Size of marker
+ Valid only if marker in mode
+ fill : bool
+ Filled Traces
+ width : int
+ Line width
+ dash : string
+ Drawing style of lines
+ solid
+ dash
+ dashdot
+ dot
+ sortbars : bool
+ Sort bars in descending order
+ * Only valid when kind='bar'
+ keys : list of columns
+ List of columns to chart.
+ Also can be usded for custom sorting.
+ bestfit : boolean or list
+ If True then a best fit line will be generated for
+ all columns.
+ If list then a best fit line will be generated for
+ each key on the list.
+ bestfit_colors : list or dict
+ {key:color} to specify the color for each column
+ [colors] to use the colors in the defined order
+ asDates : bool
+ If true it forces truncates times from a DatetimeIndex
+
+ """
+ df=self.copy()
+
+ if asTimestamp:
+ x=[_ for _ in df.index]
+ elif df.index.__class__.__name__ in ('PeriodIndex','DatetimeIndex'):
+ if asDates:
+ df.index=df.index.date
+ x=df.index.format()
+ elif isinstance(df.index,pd.MultiIndex):
+ x=['({0})'.format(','.join([str(__) for __ in _])) for _ in df.index.values]
+ else:
+ x = df.index.values
+ lines={}
+ if type(df)==pd.core.series.Series:
+ df=pd.DataFrame({df.name:df})
+
+ if not keys:
+ if 'bar' in kind:
+ if sortbars:
+ keys=list(df.sum().sort_values(ascending=False).keys())
+ else:
+ keys=list(df.keys())
+ else:
+ keys=list(df.keys())
+
+ colors=get_colors(colors,colorscale,keys)
+ dash=get_items_as_list(dash,keys,'dash')
+ symbol=get_items_as_list(symbol,keys,'symbol')
+ mode=get_items_as_list(mode,keys,'mode')
+ interpolation=get_items_as_list(interpolation,keys,'interpolation')
+ width=get_items_as_list(width,keys,'width')
+ for key in keys:
+ lines[key]={}
+ lines[key]["x"]=x
+ lines[key]["y"]=df[key].fillna('').values
+ lines[key]["name"]=str(key)
+ if text is not None:
+ lines[key]["text"]=text
+ if 'bar' in kind:
+ lines[key]["marker"]={'color':to_rgba(colors[key],.6),'line':{'color':colors[key],'width':1}}
+ else:
+ lines[key]["line"]={'color':colors[key],'width':width[key],'dash':dash[key], 'shape':interpolation[key]}
+ lines[key]["mode"]=mode[key]
+ if 'marker' in mode[key]:
+ lines[key]["marker"]=go.Marker(symbol=symbol[key],size=size)
+ if fill:
+ lines[key]["fill"]='tonexty' if kind=='area' else 'tozeroy'
+ lines[key]["fillcolor"]=to_rgba(colors[key],kwargs['opacity'] if 'opacity' in kwargs else .3 )
+ if 'bar' in kind:
+ lines_plotly=[go.Bar(lines[key]) for key in keys]
+ else:
+ lines_plotly=[go.Scatter(lines[key]) for key in keys]
+ for trace in lines_plotly:
+ if isinstance(trace['name'],pd.Timestamp):
+ trace.update(name=str(trace['name']))
+
+ if bestfit:
+ if type(bestfit)==list:
+ keys=bestfit
+ d={}
+ for key in keys:
+ bestfit=df[key].bestfit()
+ d[bestfit.formula]=bestfit
+ bestfit_lines=pd.DataFrame(d).to_iplot(bestfit=False,colors=bestfit_colors,kind='scatter',asTimestamp=asTimestamp)
+ for line in bestfit_lines:
+ line['line']['dash']='dash'
+ if not bestfit_colors:
+ line['line']['color']=to_rgba(line['line']['color'],.6)
+ data=go.Data(lines_plotly)
+ data.extend(bestfit_lines)
+ return data
+
+ if mean:
+ if type(mean)==list:
+ keys=mean
+ d={}
+ for key in keys:
+ mean=df[key].mean()
+ d['MEAN({key})'.format(key=key)]=pd.Series([mean]*len(df[key]),index=df[key].index)
+ mean_lines=pd.DataFrame(d).to_iplot(mean=False,colors=mean_colors,kind='scatter',asTimestamp=asTimestamp)
+ for line in mean_lines:
+ line['line']['dash']='dash'
+ if not mean_colors:
+ line['line']['color']=to_rgba(line['line']['color'],.6)
+ data=go.Data(lines_plotly)
+ data.extend(mean_lines)
+ return data
+ return go.Data(lines_plotly)
+
+def _iplot(self,kind='scatter',data=None,layout=None,filename='',sharing=None,title='',xTitle='',yTitle='',zTitle='',theme=None,colors=None,colorscale=None,fill=False,width=None,
+ dash='solid',mode='lines',interpolation='linear',symbol='dot',size=12,barmode='',sortbars=False,bargap=None,bargroupgap=None,bins=None,histnorm='',
+ histfunc='count',orientation='v',boxpoints=False,annotations=None,keys=False,bestfit=False,
+ bestfit_colors=None,mean=False,mean_colors=None,categories='',x='',y='',z='',text='',gridcolor=None,
+ zerolinecolor=None,margin=None,labels=None,values=None,secondary_y='',secondary_y_title='',subplots=False,shape=None,error_x=None,
+ error_y=None,error_type='data',locations=None,lon=None,lat=None,asFrame=False,asDates=False,asFigure=False,
+ asImage=False,dimensions=None,asPlot=False,asUrl=False,online=None,**kwargs):
+ """
+ Returns a plotly chart either as inline chart, image of Figure object
+
+ Parameters:
+ -----------
+ kind : string
+ Kind of chart
+ scatter
+ bar
+ box
+ spread
+ ratio
+ heatmap
+ surface
+ histogram
+ bubble
+ bubble3d
+ scatter3d
+ scattergeo
+ ohlc
+ candle
+ pie
+ choroplet
+ data : Data
+ Plotly Data Object.
+ If not entered then the Data object will be automatically
+ generated from the DataFrame.
+ layout : Layout
+ Plotly layout Object
+ If not entered then the Layout objet will be automatically
+ generated from the DataFrame.
+ filename : string
+ Filename to be saved as in plotly account
+ sharing : string
+ Sets the sharing level permission
+ public - anyone can see this chart
+ private - only you can see this chart
+ secret - only people with the link can see the chart
+ title : string
+ Chart Title
+ xTitle : string
+ X Axis Title
+ yTitle : string
+ Y Axis Title
+ zTitle : string
+ zTitle : string
+ Z Axis Title
+ Applicable only for 3d charts
+ theme : string
+ Layout Theme
+ solar
+ pearl
+ white
+ see cufflinks.getThemes() for all
+ available themes
+ colors : dict, list or string
+ {key:color} to specify the color for each column
+ [colors] to use the colors in the defined order
+ colorscale : string
+ Color scale name
+ If the color name is preceded by a minus (-)
+ then the scale is inversed
+ Only valid if 'colors' is null
+ See cufflinks.colors.scales() for available scales
+ fill : bool
+ Filled Traces
+ width : dict, list or string
+ string : applies to all traces
+ list : applies to each trace in the order
+ specified
+ dict: {column:value} for each column in
+ the dataframe
+ Line width
+ dash : dict, list or string
+ string : applies to all traces
+ list : applies to each trace in the order
+ specified
+ dict: {column:value} for each column in
+ the dataframe
+ Drawing style of lines
+ solid
+ dash
+ dashdot
+ dot
+ mode : dict, list or string
+ string : applies to all traces
+ list : applies to each trace in the order
+ specified
+ dict: {column:value} for each column in
+ the dataframe
+ Plotting mode for scatter trace
+ lines
+ markers
+ lines+markers
+ lines+text
+ markers+text
+ lines+markers+text
+ interpolation : dict, list, or string
+ string : applies to all traces
+ list : applies to each trace in the order
+ specified
+ dict: {column:value} for each column in
+ the dataframe
+ Positioning of the connecting lines
+ linear
+ spline
+ vhv
+ hvh
+ vh
+ hv
+ symbol : dict, list or string
+ string : applies to all traces
+ list : applies to each trace in the order
+ specified
+ dict: {column:value} for each column in
+ the dataframe
+ The symbol that is drawn on the plot for each marker
+ Valid only when mode includes markers
+ dot
+ cross
+ diamond
+ square
+ triangle-down
+ triangle-left
+ triangle-right
+ triangle-up
+ x
+ size : string or int
+ Size of marker
+ Valid only if marker in mode
+ barmode : string
+ Mode when displaying bars
+ group
+ stack
+ overlay
+ * Only valid when kind='bar'
+ sortbars : bool
+ Sort bars in descending order
+ * Only valid when kind='bar'
+ bargap : float
+ Sets the gap between bars
+ [0,1)
+ * Only valid when kind is 'histogram' or 'bar'
+ bargroupgap : float
+ Set the gap between groups
+ [0,1)
+ * Only valid when kind is 'histogram' or 'bar'
+ bins : int or tuple
+ if int:
+ Specifies the number of bins
+ if tuple:
+ (start, end, size)
+ start : starting value
+ end: end value
+ size: bin size
+ * Only valid when kind='histogram'
+
+ histnorm : string
+ '' (frequency)
+ percent
+ probability
+ density
+ probability density
+ Sets the type of normalization for an histogram trace. By default
+ the height of each bar displays the frequency of occurrence, i.e.,
+ the number of times this value was found in the
+ corresponding bin. If set to 'percent', the height of each bar
+ displays the percentage of total occurrences found within the
+ corresponding bin. If set to 'probability', the height of each bar
+ displays the probability that an event will fall into the
+ corresponding bin. If set to 'density', the height of each bar is
+ equal to the number of occurrences in a bin divided by the size of
+ the bin interval such that summing the area of all bins will yield
+ the total number of occurrences. If set to 'probability density',
+ the height of each bar is equal to the number of probability that an
+ event will fall into the corresponding bin divided by the size of
+ the bin interval such that summing the area of all bins will yield
+ 1.
+ * Only valid when kind='histogram'
+ histfunc : string
+ count
+ sum
+ avg
+ min
+ max
+ Sets the binning function used for an histogram trace.
+ * Only valid when kind='histogram'
+ orientation : string
+ h
+ v
+ Sets the orientation of the bars. If set to 'v', the length of each
+ | bar will run vertically. If set to 'h', the length of each bar will
+ | run horizontally
+ * Only valid when kind is 'histogram','bar' or 'box'
+ boxpoints : string
+ Displays data points in a box plot
+ outliers
+ all
+ suspectedoutliers
+ False
+ annotations : dictionary
+ Dictionary of annotations
+ {x_point : text}
+ keys : list of columns
+ List of columns to chart.
+ Also can be usded for custom sorting.
+ bestfit : boolean or list
+ If True then a best fit line will be generated for
+ all columns.
+ If list then a best fit line will be generated for
+ each key on the list.
+ bestfit_colors : list or dict
+ {key:color} to specify the color for each column
+ [colors] to use the colors in the defined order
+ categories : string
+ Name of the column that contains the categories
+ x : string
+ Name of the column that contains the x axis values
+ y : string
+ Name of the column that contains the y axis values
+ z : string
+ Name of the column that contains the z axis values
+ text : string
+ Name of the column that contains the text values
+ gridcolor : string
+ Grid color
+ zerolinecolor : string
+ Zero line color
+ margin : dict or tuple
+ Dictionary (l,r,b,t) or
+ Tuple containing the left,
+ right, bottom and top margins
+ labels : string
+ Name of the column that contains the labels.
+ * Only valid when kind='pie'
+ values : string
+ Name of the column that contains the values.
+ * Only valid when kind='pie'
+ secondary_y : string or list(string)
+ Name(s) of the column to be charted on the
+ right hand side axis
+ secondary_y_title : string
+ Title of the secondary axis
+ subplots : bool
+ If true then each trace is placed in
+ subplot layout
+ shape : (rows,cols)
+ Tuple indicating the size of rows and columns
+ If omitted then the layout is automatically set
+ * Only valid when subplots=True
+ error_x : int or float or [int or float]
+ error values for the x axis
+ error_y : int or float or [int or float]
+ error values for the y axis
+ error_type : string
+ type of error bars
+ 'data'
+ 'constant'
+ 'percent'
+ 'sqrt'
+ 'continuous'
+ 'continuous_percent'
+ asFrame : bool
+ If true then the data component of Figure will
+ be of Pandas form (Series) otherwise they will
+ be index values
+ asDates : bool
+ If true it truncates times from a DatetimeIndex
+ asFigure : bool
+ If True returns plotly Figure
+ asImage : bool
+ If True it returns an Image (png)
+ In ONLINE mode:
+ Image file is saved in the working directory
+ Accepts:
+ filename
+ dimensions
+ scale
+ display_image
+ In OFFLINE mode:
+ Image file is downloaded (downloads folder) and a
+ regular plotly chart is displayed in Jupyter
+ Accepts:
+ filename
+ dimensions
+ dimensions : tuple(int,int)
+ Dimensions for image / chart
+ (width,height)
+ asPlot : bool
+ If True the chart opens in browser
+ asUrl : bool
+ If True the chart url/path is returned. No chart is displayed.
+ If Online : the URL is returned
+ If Offline : the local path is returned
+ online : bool
+ If True then the chart/image is rendered on the server
+ even when running in offline mode.
+
+ Other Kwargs
+ ============
+ Line, Scatter
+ connectgaps : bool
+ If True, empty values are connected
+ Pie charts
+ sort : bool
+ If True it sorts the labels by value
+ pull : float [0-1]
+ Pulls the slices from the centre
+ hole : float [0-1]
+ Sets the size of the inner hole
+ linecolor : string
+ Sets the color for the contour line of the slices
+ linewidth : string
+ Sets the width for the contour line of the slices
+ textcolor : string
+ Sets the color for the text in the slices
+ textposition : string
+ Sets the position of the legends for each slice
+ outside
+ inner
+ textinfo : string
+ Sets the information to be displayed on
+ the legends
+ label
+ percent
+ value
+ * or ony combination of the above using
+ '+' between each item
+ ie 'label+percent'
+
+ Histogram
+ line_color : string
+ specifies the line color of the histogram
+
+ Heatmap and Surface
+ center_scale : float
+ Centers the colorscale at a specific value
+ Automatically sets the (zmin,zmax) values
+ zmin : float
+ Defines the minimum range for the z values.
+ This affects the range for the colorscale
+ zmax : float
+ Defines the maximum range for the z values.
+ This affects the range for the colorscale
+
+ Error Bars
+ error_trace : string
+ Name of the column for which error should be
+ plotted. If omitted then errors apply to all
+ traces.
+ error_values_minus : int or float or [int or float]
+ Values corresponding to the span of the error bars
+ below the trace coordinates
+ error_color : string
+ Color for error bars
+ error_thickness : float
+ Sets the line thickness of the error bars
+ error_width : float
+ Sets the width (in pixels) of the cross-bar at both
+ ends of the error bars
+ error_opacity : float [0,1]
+ Opacity for the error bars
+
+ Subplots
+ horizontal_spacing : float [0,1]
+ Space between subplot columns.
+ vertical_spacing : float [0,1]
+ Space between subplot rows.
+ subplot_titles : bool
+ If True, chart titles are plotted
+ at the top of each subplot
+ shared_xaxes : bool
+ Assign shared x axes.
+ If True, subplots in the same grid column have one common
+ shared x-axis at the bottom of the grid.
+ shared_yaxes : bool
+ Assign shared y axes.
+ If True, subplots in the same grid row have one common
+ shared y-axis on the left-hand side of the grid.
+
+ Shapes
+ hline : int, list or dict
+ Draws a horizontal line at the
+ indicated y position(s)
+ Extra parameters can be passed in
+ the form of a dictionary (see shapes)
+ vline : int, list or dict
+ Draws a vertical line at the
+ indicated x position(s)
+ Extra parameters can be passed in
+ the form of a dictionary (see shapes)
+ hpsan : (y0,y1)
+ Draws a horizontal rectangle at the
+ indicated (y0,y1) positions.
+ Extra parameters can be passed in
+ the form of a dictionary (see shapes)
+ vspan : (x0,x1)
+ Draws a vertical rectangle at the
+ indicated (x0,x1) positions.
+ Extra parameters can be passed in
+ the form of a dictionary (see shapes)
+ shapes : dict or list(dict)
+ List of dictionaries with the
+ specifications of a given shape.
+ See help(cufflinks.tools.get_shape)
+ for more information
+
+ Axis Ranges
+ xrange : [lower_bound,upper_bound]
+ Sets the range for the x axis
+ yrange : [lower_bound,upper_bound]
+ Sets the range for the y axis
+ zrange : [lower_bound,upper_bound]
+ Sets the range for the z axis
+
+ Explicit Layout Updates
+ layout_update : dict
+ The layout will be modified with all
+ the explicit values stated in the
+ dictionary.
+ It will not apply if layout is passed
+ as parameter.
+
+
+ Range Selector
+ rangeselector : dict
+ Defines a rangeselector object
+ see help(cf.tools.get_range_selector) for more information
+ Example:
+ {'steps':['1y','2 months','5 weeks','ytd','2mtd'],
+ 'axis':'xaxis1', 'bgcolor' : ('blue',.3),
+ 'x': 0.2 , 'y' : 0.9}
+
+ Range Slider
+ rangeslider : bool or dict
+ Defines if a rangeslider is displayed
+ If bool:
+ True : Makes it visible
+ if dict:
+ Rangeslider object
+ Example:
+ {'bgcolor':('blue',.3),'autorange':True}
+
+ Annotations
+ fontcolor : str
+ Text color for annotations
+ fontsize : int
+ Text size for annotations
+ textangle : int
+ Textt angle
+ See https://plot.ly/python/reference/#layout-annotations
+ for a complete list of valid parameters.
+
+ Exports
+ display_image : bool
+ If True then the image if displayed after being saved
+ ** only valid if asImage=True
+ scale : integer
+ Increase the resolution of the image by `scale` amount
+ Only valid when asImage=True
+ """
+
+ # Valid Kwargs
+ valid_kwargs = ['color','opacity','column','columns','labels','text','world_readable','colorbar']
+ TRACE_KWARGS = ['hoverinfo','connectgaps']
+ HEATMAP_SURFACE_KWARGS = ['center_scale','zmin','zmax']
+ PIE_KWARGS=['sort','pull','hole','textposition','textinfo','linecolor','linewidth','textcolor']
+ OHLC_KWARGS=['up_color','down_color','open','high','low','close','volume','name','decreasing','increasing']
+ SUBPLOT_KWARGS=['horizontal_spacing', 'vertical_spacing',
+ 'specs', 'insets','start_cell','shared_xaxes','shared_yaxes','subplot_titles']
+ GEO_KWARGS=['locationmode','locationsrc','geo','lon','lat']
+ ERROR_KWARGS=['error_trace','error_values_minus','error_color','error_thickness',
+ 'error_width','error_opacity']
+ EXPORT_KWARGS=['display_image','scale']
+ kwargs_list = [tools.__LAYOUT_KWARGS,TRACE_KWARGS,
+ OHLC_KWARGS,PIE_KWARGS,HEATMAP_SURFACE_KWARGS,SUBPLOT_KWARGS,GEO_KWARGS,ERROR_KWARGS,EXPORT_KWARGS]
+ [valid_kwargs.extend(_) for _ in kwargs_list]
+
+ dict_modifiers_keys = ['line']
+ dict_modifiers={}
+
+ for k in dict_modifiers_keys:
+ dict_modifiers[k]=kwargs_from_keyword(kwargs,{},k,True)
+
+
+ for key in list(kwargs.keys()):
+ if key not in valid_kwargs:
+ raise Exception("Invalid keyword : '{0}'".format(key))
+
+ # Setting default values
+ if not colors:
+ colors=kwargs['color'] if 'color' in kwargs else colors
+ if isinstance(colors,str):
+ colors=[colors]
+ opacity=kwargs['opacity'] if 'opacity' in kwargs else 0.8
+ if not dimensions:
+ dimensions=auth.get_config_file()['dimensions']
+
+ # Get values from config theme
+ if theme is None:
+ theme = auth.get_config_file()['theme']
+ theme_config=tools.getTheme(theme)
+ if colorscale is None:
+ config_colorscale=auth.get_config_file()['colorscale']
+ if config_colorscale in ('dflt',None):
+ colorscale=theme_config['colorscale'] if 'colorscale' in theme_config else 'original'
+ else:
+ colorscale=config_colorscale
+ if width is None:
+ if kind != 'pie':
+ width=theme_config['linewidth'] if 'linewidth' in theme_config else 2
+ if margin is None:
+ margin=auth.get_config_file().get('margin',None)
+
+
+ # In case column was used instead of keys
+ if 'column' in kwargs:
+ keys=[kwargs['column']] if isinstance(kwargs['column'],str) else kwargs['column']
+ if 'columns' in kwargs:
+ keys=[kwargs['columns']] if isinstance(kwargs['columns'],str) else kwargs['columns']
+ kind='line' if kind=='lines' else kind
+
+ # Figure generators
+ def get_marker(marker={}):
+ if 'line' in dict_modifiers:
+ if 'color' not in dict_modifiers['line']:
+ if 'linecolor' in tools.getTheme(theme=theme):
+ linecolor=normalize(tools.getTheme(theme=theme)['linecolor'])
+ else:
+ linecolor=tools.getLayout(theme=theme)['xaxis1']['titlefont']['color']
+ dict_modifiers['line']['color']=linecolor
+ dict_modifiers['line']=tools.updateColors(dict_modifiers['line'])
+ marker['line']=deep_update(marker['line'],dict_modifiers['line'])
+ return marker
+
+ # We assume we are good citizens
+ validate=True
+
+
+ if not layout:
+ l_kwargs=dict([(k,kwargs[k]) for k in tools.__LAYOUT_KWARGS if k in kwargs])
+ if annotations:
+ ann_kwargs=check_kwargs(kwargs,tools.__ANN_KWARGS,clean_origin=True)
+ annotations=tools.getAnnotations(self.copy(),annotations,kind=kind,theme=theme,**ann_kwargs)
+
+
+ layout=tools.getLayout(kind=kind,theme=theme,xTitle=xTitle,yTitle=yTitle,zTitle=zTitle,title=title,barmode=barmode,
+ bargap=bargap,bargroupgap=bargroupgap,annotations=annotations,gridcolor=gridcolor,
+ dimensions=dimensions,
+ zerolinecolor=zerolinecolor,margin=margin,is3d='3d' in kind,**l_kwargs)
+
+ if not data:
+ if categories:
+ data=go.Data()
+ if 'bar' in kind:
+ df=self.copy()
+ df=df.set_index(categories)
+ fig=df.figure(kind=kind,colors=colors,colorscale=colorscale,fill=fill,width=width,sortbars=sortbars,
+ asDates=asDates,mode=mode,symbol=symbol,size=size,text=text,barmode=barmode,orientation=orientation)
+ data=fig['data']
+ else:
+ _keys=pd.unique(self[categories])
+ colors=get_colors(colors,colorscale,_keys)
+ mode='markers' if 'markers' not in mode else mode
+ for _ in _keys:
+ __=self[self[categories]==_].copy()
+ if text:
+ _text=__[text] if asFrame else __[text].values
+ _x=__[x] if asFrame else __[x].values
+ _y=__[y] if asFrame else __[y].values
+ if z:
+ _z=__[z] if asFrame else __[z].values
+ if 'bubble' in kind:
+ rg=__[size].values
+ rgo=self[size].values
+ _size=[int(100*(float(i)-rgo.min())/(rgo.max()-rgo.min()))+12 for i in rg]
+ else:
+ _size=size
+ _data=go.Scatter3d(x=_x,y=_y,mode=mode,name=_,
+ marker=go.Marker(color=colors[_],symbol=symbol,size=_size,opacity=opacity,
+ line=go.Line(width=width)),textfont=tools.getLayout(theme=theme)['xaxis1']['titlefont'])
+ if '3d' in kind:
+ _data=go.Scatter3d(x=_x,y=_y,z=_z,mode=mode,name=_,
+ marker=go.Marker(color=colors[_],symbol=symbol,size=_size,opacity=opacity,
+ line=go.Line(width=width)),textfont=tools.getLayout(theme=theme)['xaxis1']['titlefont'])
+ else:
+ _data=go.Scatter(x=_x,y=_y,mode=mode,name=_,
+ marker=go.Marker(color=colors[_],symbol=symbol,size=_size,opacity=opacity,
+ line=go.Line(width=width)),textfont=tools.getLayout(theme=theme)['xaxis1']['titlefont'])
+ if text:
+ _data.update(text=_text)
+ data.append(_data)
+ else:
+ if kind in ('scatter','spread','ratio','bar','barh','area','line'):
+ df=self.copy()
+ if type(df)==pd.core.series.Series:
+ df=pd.DataFrame({df.name:df})
+ if x:
+ df=df.set_index(x)
+ if y:
+ df=df[y]
+ if kind=='area':
+ df=df.transpose().fillna(0).cumsum().transpose()
+ if text:
+ if not isinstance(text,list):
+ text=self[text].values
+ data=df.to_iplot(colors=colors,colorscale=colorscale,kind=kind,interpolation=interpolation,fill=fill,width=width,dash=dash,sortbars=sortbars,keys=keys,
+ bestfit=bestfit,bestfit_colors=bestfit_colors,mean=mean,mean_colors=mean_colors,asDates=asDates,mode=mode,symbol=symbol,size=size,
+ text=text,**kwargs)
+ trace_kw=check_kwargs(kwargs,TRACE_KWARGS)
+ for trace in data:
+ trace.update(**trace_kw)
+
+ if kind in ('spread','ratio'):
+ if kind=='spread':
+ trace=self.apply(lambda x:x[0]-x[1],axis=1)
+ positive=trace.apply(lambda x:x if x>=0 else pd.np.nan)
+ negative=trace.apply(lambda x:x if x<0 else pd.np.nan)
+ trace=pd.DataFrame({'positive':positive,'negative':negative})
+ trace=trace.to_iplot(colors={'positive':'green','negative':'red'},width=0.5)
+ else:
+ trace=self.apply(lambda x:x[0]*1.0/x[1],axis=1).to_iplot(colors=['green'],width=1)
+ trace.update({'xaxis':'x2','yaxis':'y2','fill':'tozeroy',
+ 'name':kind.capitalize(),'connectgaps':False,'showlegend':False})
+ data.append(go.Scatter(trace[0]))
+ if kind=='spread':
+ data.append(go.Scatter(trace[1]))
+ layout['yaxis1'].update({'domain':[.3,1]})
+ layout['yaxis2']=copy.deepcopy(layout['yaxis1'])
+ layout['xaxis2']=copy.deepcopy(layout['xaxis1'])
+ layout['yaxis2'].update(domain=[0,.25],title=kind.capitalize())
+ layout['xaxis2'].update(anchor='y2',showticklabels=False)
+ layout['hovermode']='x'
+ if 'bar' in kind:
+ if 'stack' in barmode:
+ layout['legend'].update(traceorder='normal')
+ orientation = 'h' if kind=='barh' else orientation
+ for trace in data:
+ trace.update(orientation=orientation)
+ if kind=='barh':
+ trace['x'],trace['y']=trace['y'],trace['x']
+
+ elif kind=='bubble':
+ mode='markers' if 'markers' not in mode else mode
+ x=self[x].values.tolist()
+ y=self[y].values.tolist()
+ z=size if size else z
+ rg=self[z].values
+ if len(rg) > 1:
+ z=[int(100*(float(_)-rg.min())/(rg.max()-rg.min()))+12 for _ in rg]
+ else:
+ z=[12] if len(rg) else []
+ text=kwargs['labels'] if 'labels' in kwargs else text
+ labels=self[text].values.tolist() if text else ''
+ clrs=colors if colors else get_scales(colorscale)
+ clrs=[clrs] if not isinstance(clrs,list) else clrs
+ clrs=[clrs[0]]*len(x)
+ marker=go.Marker(color=clrs,size=z,symbol=symbol,
+ line=go.Line(width=width))
+ trace=go.Scatter(x=x,y=y,marker=marker,mode='markers',text=labels)
+ data=go.Data([trace])
+ elif kind in ('box','histogram','hist','violin'):
+ if isinstance(self,pd.core.series.Series):
+ df=pd.DataFrame({self.name:self})
+ else:
+ df=self.copy()
+ data=go.Data()
+ clrs=get_colors(colors,colorscale,df.columns)
+ if 'hist' in kind:
+ barmode = 'overlay' if barmode=='' else barmode
+ layout.update(barmode=barmode)
+ columns=keys if keys else df.columns
+ for _ in columns:
+ if kind=='box':
+ __=go.Box(y=df[_].values.tolist(),marker=go.Marker(color=clrs[_]),name=_,
+ line=go.Line(width=width),boxpoints=boxpoints)
+ elif kind=='violin':
+ figure = ff.create_violin(df.melt(), data_header='value', group_header='variable',
+ theme=theme,xTitle=xTitle,yTitle=yTitle,zTitle=zTitle,title=title)
+ if asFigure:
+ return figure
+ else:
+ return iplot(figure,validate=validate,sharing=sharing,filename=filename,
+ online=online,asImage=asImage,asUrl=asUrl,asPlot=asPlot,
+ dimensions=dimensions,display_image=kwargs.get('display_image',True))
+
+ else:
+ __=go.Histogram(x=df[_].values.tolist(),name=_,
+ marker=go.Marker(color=clrs[_], line=go.Line(width=width)),
+ orientation=orientation,
+ opacity=kwargs['opacity'] if 'opacity' in kwargs else .8, histfunc=histfunc,
+ histnorm=histnorm)
+
+ __['marker']=get_marker(__['marker'])
+
+ if orientation=='h':
+ __['y']=__['x']
+ del __['x']
+ if bins:
+ if type(bins) in (tuple,list):
+ try:
+ _bins={'start':bins[0],'end':bins[1],'size':bins[2]}
+ if orientation=='h':
+ __.update(ybins=_bins,autobiny=False)
+ else:
+ __.update(xbins=_bins,autobinx=False)
+ except:
+ print("Invalid format for bins generation")
+ else:
+ if orientation=='h':
+ __.update(nbinsy=bins)
+ else:
+ __.update(nbinsx=bins)
+ data.append(__)
+
+ elif kind in ('heatmap','surface'):
+ if x:
+ x=self[x].values.tolist()
+ else:
+ if self.index.__class__.__name__ in ('PeriodIndex','DatetimeIndex'):
+ x=self.index.format()
+ else:
+ x=self.index.values.tolist()
+ y=self[y].values.tolist() if y else self.columns.values.tolist()
+ z=self[z].values.tolist() if z else self.values.transpose()
+ scale=get_scales('rdbu') if not colorscale else get_scales(colorscale)
+ colorscale=[[float(_)/(len(scale)-1),scale[_]] for _ in range(len(scale))]
+ center_scale = kwargs.get('center_scale',None)
+ zmin=z.min()
+ zmax=z.max()
+ if center_scale is not None:
+ if center_scale<=zmin+(zmax-zmin)/2:
+ zmin=center_scale*2-zmax
+ else:
+ zmax=center_scale*2-zmin
+ zmin=kwargs.get('zmin',zmin)
+ zmax=kwargs.get('zmax',zmax)
+ if kind=='heatmap':
+ data=go.Data([go.Heatmap(z=z,x=x,y=y,zmin=zmin,zmax=zmax,colorscale=colorscale)])
+ else:
+ data=go.Data([go.Surface(z=z,x=x,y=y,zmin=zmin,zmax=zmax,colorscale=colorscale)])
+
+ elif kind in ('scatter3d','bubble3d'):
+ data=go.Data()
+ keys=self[text].values if text else list(range(len(self)))
+ colors=get_colors(colors,colorscale,keys,asList=True)
+ mode='markers' if 'markers' not in mode else mode
+ df=self.copy()
+ df['index']=keys
+ if kind=='bubble3d':
+ rg=self[size].values
+ size=[int(100*(float(_)-rg.min())/(rg.max()-rg.min()))+12 for _ in rg]
+ else:
+ size=[size for _ in range(len(keys))]
+
+ _data=go.Scatter3d(x=df[x].values.tolist(),y=df[y].values.tolist(),z=df[z].values.tolist(),mode=mode,name=keys,
+ marker=go.Marker(color=colors,symbol=symbol,size=size,opacity=.8))
+ if text:
+ _data.update(text=keys)
+ data.append(_data)
+
+ elif kind=='pie':
+ if not labels:
+ raise CufflinksError('Missing: labels')
+ if not values:
+ raise CufflinksError('Missing: values')
+ labels=self[labels].values.tolist()
+ values=self[values].values.tolist()
+ marker=go.Marker(colors=get_colors(colors,colorscale,labels,asList=True))
+ marker.update(line=go.Line(color=kwargs.pop('linecolor',None),width=kwargs.pop('linewidth',width)))
+ pie=go.Pie(values=values,labels=labels,name='',marker=marker)
+
+ kw=check_kwargs(kwargs,PIE_KWARGS)
+ kw['textfont']={'color':kw.pop('textcolor',None)}
+ pie.update(kw)
+ data=go.Data()
+ del layout['xaxis1']
+ del layout['yaxis1']
+ data.append(pie)
+ validate=False
+
+ elif kind in ('old_candle','old_ohlc'):
+ d=ta._ohlc_dict(self)
+ if len(list(d.keys()))!=4:
+ raise Exception("OHLC type of charts require an Open, High, Low and Close column")
+ ohlc_kwargs=check_kwargs(kwargs,OHLC_KWARGS)
+ if kind=='old_candle':
+ fig=tools.get_candle(self,theme=theme,layout=layout,**ohlc_kwargs)
+ else:
+ fig=tools.get_ohlc(self,theme=theme,layout=layout,**ohlc_kwargs)
+ if bestfit:
+ df=self.copy()
+ bf=_to_iplot(self[d['close']],bestfit=True,bestfit_colors=bestfit_colors,asTimestamp=True)
+ fig['data'].append(bf[1])
+ data=fig['data']
+ layout=fig['layout']
+
+ elif kind in ('candle','ohlc','candlestick'):
+ kind='candlestick' if kind=='candle' else kind
+ kw=check_kwargs(kwargs,OHLC_KWARGS)
+ d=ta._ohlc_dict(self,validate='ohlc',**kw)
+ _d=dict(type=kind,
+ open=self[d['open']].values,
+ high=self[d['high']].values,
+ low=self[d['low']].values,
+ close=self[d['close']].values,
+ x=self.index
+ )
+ if 'name' in kw:
+ _d['name']=kw['name']
+
+ showlegend=False
+ if 'showlegend' in kwargs:
+ showlegend=kwargs['showlegend']
+ else:
+ if 'legend' in kwargs:
+ if type(kwargs['legend'])==bool:
+ showlegend=kwargs['legend']
+
+ _d['increasing']=dict(line=dict(color=kw['up_color']) if 'up_color' in kw else dict(),showlegend=showlegend)
+ _d['decreasing']=dict(line=dict(color=kw['down_color']) if 'down_color' in kw else dict(),showlegend=showlegend)
+ for k in ('increasing','decreasing'):
+ if k in kw:
+ _d[k]=deep_update(_d[k],kw[k])
+
+ _d['yaxis']='y2'
+ data=[_d]
+
+
+
+ elif kind in ('choropleth','scattergeo'):
+ kw=check_kwargs(kwargs,GEO_KWARGS)
+ if kind=='choropleth':
+ if not all([x!=None for x in (locations,z)]):
+ raise Exception("Choropleth maps require a 'location' and 'z' column names specified")
+ geo_data={'type':'choropleth','locations':self[locations],'z':self[z],
+ 'colorscale':get_colorscale(colorscale),
+ 'marker':get_marker(go.Marker(line=go.Line(width=width)))}
+ elif kind=='scattergeo':
+ if not all([x!=None for x in (lon,lat)]):
+ raise Exception("Scattergeo maps require a 'lon' and 'lat' column names specified")
+ geo_data={'type':'scattergeo','lat':self[lat],'lon':self[lon],
+ 'marker':get_marker(go.Marker(line=go.Line(width=width),
+ symbol=symbol,colorscale=get_colorscale(colorscale),
+ color=self[z] if z else None))}
+ if 'colorbar' in kwargs:
+ geo_data['colorbar']=kwargs['colorbar']
+ geo_data.update(kw)
+ if text:
+ geo_data.update(text=self[text])
+ validate=False
+ data=go.Data()
+ data.append(geo_data)
+
+## Sharing Values
+ if all(['world_readable' in kwargs,sharing is None]):
+ sharing=kwargs['world_readable']
+ if isinstance(sharing,bool):
+ if sharing:
+ sharing='public'
+ else:
+ sharing='private'
+ if sharing is None:
+ sharing=auth.get_config_file()['sharing']
+
+ if not filename:
+ if title:
+ filename=title
+ else:
+ filename='Plotly Playground {0}'.format(time.strftime("%Y-%m-%d %H:%M:%S"))
+
+
+
+## Figure defintion
+ figure=go.Figure()
+ figure['data']=data
+ figure['layout']=layout
+
+## Check secondary axis
+ if secondary_y:
+ figure=figure.set_axis(secondary_y,side='right')
+ if secondary_y_title:
+ figure.layout.yaxis2.title=secondary_y_title
+
+## Error Bars
+ if kind in ('scatter','bar','barh','lines'):
+ if any([error_x,error_y]):
+ def set_error(axis,**kwargs):
+ return tools.set_errors(figure,axis=axis,**kwargs)
+ kw=check_kwargs(kwargs,ERROR_KWARGS)
+ kw=dict([(k.replace('error_',''),v) for k,v in list(kw.items())])
+ kw['type']=error_type
+ if error_x:
+ kw['values']=error_x
+ figure=set_error('x',**kw)
+ if error_y:
+ kw['values']=error_y
+ figure=set_error('y',**kw)
+## Subplots
+
+ if subplots:
+ fig=tools.strip_figures(figure)
+ kw=check_kwargs(kwargs,SUBPLOT_KWARGS)
+ if 'subplot_titles' in kwargs:
+ if kwargs['subplot_titles']==True:
+ kw['subplot_titles']=[d['name'] for d in data]
+ else:
+ kw['subplot_titles']=kwargs['subplot_titles']
+ figure=tools.subplots(fig,shape,base_layout=layout,theme=theme,**kw)
+
+
+## Exports
+ validate = False if 'shapes' in layout else validate
+
+ if asFigure:
+ return figure
+ else:
+ return iplot(figure,validate=validate,sharing=sharing,filename=filename,
+ online=online,asImage=asImage,asUrl=asUrl,asPlot=asPlot,
+ dimensions=dimensions,display_image=kwargs.get('display_image',True))
+
+
+[docs]def get_colors(colors,colorscale,keys,asList=False):
+
if type(colors)!=dict:
+
if not colors:
+
if colorscale:
+
colors=get_scales(colorscale,len(keys))
+
clrgen=colorgen(colors,len(keys))
+
if asList:
+
colors=[next(clrgen) for _ in keys]
+
else:
+
colors={}
+
for key in keys:
+
colors[key]=next(clrgen)
+
return colors
+
+[docs]def get_items_as_list(items,keys,items_names='styles'):
+
"""
+
Returns a dict with an item per key
+
+
Parameters:
+
-----------
+
items : string, list or dict
+
Items (ie line styles)
+
keys: list
+
List of keys
+
items_names : string
+
Name of items
+
"""
+
if type(items)!=dict:
+
if type(items)==list:
+
if len(items)!=len(keys):
+
raise Exception('List of {0} is not the same length as keys'.format(items_names))
+
else:
+
items=dict(zip(keys,items))
+
else:
+
items=dict(zip(keys,[items]*len(keys)))
+
return items
+
+
+def _scatter_matrix(self,theme=None,bins=10,color='grey',size=2, asFigure=False, **iplot_kwargs):
+ """
+ Displays a matrix with scatter plot for each pair of
+ Series in the DataFrame.
+ The diagonal shows a histogram for each of the Series
+
+ Parameters:
+ -----------
+ df : DataFrame
+ Pandas DataFrame
+ theme : string
+ Theme to be used (if not the default)
+ bins : int
+ Number of bins to use for histogram
+ color : string
+ Color to be used for each scatter plot
+ size : int
+ Size for each marker on the scatter plot
+ iplot_kwargs : key-value pairs
+ Keyword arguments to pass through to `iplot`
+ """
+ sm=tools.scatter_matrix(self,theme=theme,bins=bins,color=color,size=size)
+ if asFigure:
+ return sm
+ else:
+ return iplot(sm,**iplot_kwargs)
+
+def _figure(self,**kwargs):
+ """
+ Generates a Plotly figure for the given DataFrame
+
+ Parameters:
+ -----------
+ All properties avaialbe can be seen with
+ help(cufflinks.pd.DataFrame.iplot)
+ """
+ kwargs['asFigure']=True
+ return self.iplot(**kwargs)
+
+def _layout(self,**kwargs):
+ """
+ Generates a Plotly layout for the given DataFrame
+
+ Parameters:
+ -----------
+ All properties avaialbe can be seen with
+ help(cufflinks.pd.DataFrame.iplot)
+ """
+ kwargs['asFigure']=True
+ return self.iplot(**kwargs)['layout']
+
+
+# ONLINE
+# py.iplot(filename,fileopt,sharing,world_readable)
+# py.plot(filename,fileopt,auto_open,sharing,world_readable)
+# py.image.ishow(figure,format,width,height,scale)
+# py.image.save_as(figure,filename,format,width,height,scale)
+
+# OFFLINE
+# py_offline.iplot(figure,show_link,link_text,validate,image,filename,image_width,image_height,config)
+# py_offline.plot(figure,show_link,link_text,validate,output_type,include_plotlyjs,filename,auto_open,image,image_filename,image_width,image_height,config)
+
+
+[docs]def iplot(figure,validate=True,sharing=None,filename='',
+
online=None,asImage=False,asUrl=False,asPlot=False,
+
dimensions=None,display_image=True,**kwargs):
+
"""
+
Plots a figure in IPython, creates an HTML or generates an Image
+
+
figure : figure
+
Plotly figure to be charted
+
validate : bool
+
If True then all values are validated before
+
it is charted
+
sharing : string
+
Sets the sharing level permission
+
public - anyone can see this chart
+
private - only you can see this chart
+
secret - only people with the link can see the chart
+
filename : string
+
Name to be used to save the file in the server, or as an image
+
online : bool
+
If True then the chart/image is rendered on the server
+
even when running in offline mode.
+
asImage : bool
+
If True it returns an Image (png)
+
In ONLINE mode:
+
Image file is saved in the working directory
+
Accepts:
+
filename
+
dimensions
+
scale
+
display_image
+
In OFFLINE mode:
+
Image file is downloaded (downloads folder) and a
+
regular plotly chart is displayed in Jupyter
+
Accepts:
+
filename
+
dimensions
+
asUrl : bool
+
If True the chart url/path is returned. No chart is displayed.
+
If Online : the URL is returned
+
If Offline : the local path is returned
+
asPlot : bool
+
If True the chart opens in browser
+
dimensions : tuple(int,int)
+
Dimensions for image
+
(width,height)
+
display_image : bool
+
If true, then the image is displayed after it has been saved
+
Requires Jupyter Notebook
+
Only valid when asImage=True
+
+
Other Kwargs
+
============
+
legend : bool
+
If False then the legend will not be shown
+
scale : integer
+
Increase the resolution of the image by `scale` amount
+
Only valid when asImage=True
+
"""
+
valid_kwargs=['world_readable','legend','scale']
+
+
for key in list(kwargs.keys()):
+
if key not in valid_kwargs:
+
raise Exception("Invalid keyword : '{0}'".format(key))
+
+
if 'legend' in kwargs:
+
if 'layout' in figure:
+
figure['layout'].update(showlegend=kwargs['legend'])
+
+
## Sharing Values
+
if all(['world_readable' in kwargs,sharing is None]):
+
sharing=kwargs['world_readable']
+
if isinstance(sharing,bool):
+
if sharing:
+
sharing='public'
+
else:
+
sharing='private'
+
if sharing is None:
+
sharing=auth.get_config_file()['sharing']
+
+
## Filename Handling
+
if not filename:
+
if figure['layout']['title']:
+
filename=figure['layout']['title']
+
else:
+
filename='Plotly Playground {0}'.format(time.strftime("%Y-%m-%d %H:%M:%S"))
+
+
## Dimensions
+
if not dimensions:
+
dimensions=(800,500) if not auth.get_config_file()['dimensions'] else auth.get_config_file()['dimensions']
+
+
## Offline Links
+
show_link = auth.get_config_file()['offline_show_link']
+
link_text = auth.get_config_file()['offline_link_text']
+
+
## Remove validation if shapes are present
+
if 'layout' in figure:
+
validate = False if 'shapes' in figure['layout'] else validate
+
+
## asURL
+
auto_open=True
+
if asUrl:
+
asPlot=True
+
auto_open=False
+
+
## Exports
+
if asImage:
+
if offline.is_offline() and not online:
+
return offline.py_offline.iplot(figure,validate=validate, filename=filename, show_link=show_link,link_text=link_text,
+
image='png',image_width=dimensions[0],image_height=dimensions[1])
+
else:
+
try:
+
py.image.save_as(figure,filename='img/'+filename,format='png',
+
width=dimensions[0],height=dimensions[1],scale=kwargs.get('scale',None))
+
path='img/'+filename+'.png'
+
except:
+
py.image.save_as(figure,filename=filename,format='png',
+
width=dimensions[0],height=dimensions[1],scale=kwargs.get('scale',None))
+
path=filename+'.png'
+
if display_image:
+
return display(Image(path))
+
else:
+
print('Image saved : {0}'.format(path))
+
return None
+
+
## asPlot and asUrl
+
if asPlot:
+
filename+='.html'
+
if offline.is_offline() and not online:
+
return offline.py_offline.plot(figure, filename=filename, validate=validate,
+
show_link=show_link,link_text=link_text,auto_open=auto_open)
+
else:
+
return py.plot(figure, sharing=sharing, filename=filename, validate=validate,
+
auto_open=auto_open)
+
+
## iplot
+
if offline.is_offline() and not online:
+
return offline.py_offline.iplot(figure,validate=validate, filename=filename, show_link=show_link,link_text=link_text)
+
else:
+
return py.iplot(figure,validate=validate,sharing=sharing,
+
filename=filename)
+
+
+
+def _ta_figure(self,**kwargs):
+ """
+ Generates a Plotly figure for the given DataFrame
+
+ Parameters:
+ -----------
+ All properties avaialbe can be seen with
+ help(cufflinks.pd.DataFrame.iplot)
+ """
+ kwargs['asFigure']=True
+ return self.ta_plot(**kwargs)
+
+
+def _ta_plot(self,study,periods=14,column=None,include=True,str='{name}({period})',detail=False,
+ theme=None,sharing=None,filename='',asFigure=False,**iplot_kwargs):
+ """
+ Generates a Technical Study Chart
+
+ Parameters:
+ -----------
+ study : string
+ Technical Study to be charted
+ sma - 'Simple Moving Average'
+ rsi - 'R Strength Indicator'
+ periods : int
+ Number of periods
+ column : string
+ Name of the column on which the
+ study will be done
+ include : bool
+ Indicates if the input column(s)
+ should be included in the chart
+ str : string
+ Label factory for studies
+ The following wildcards can be used:
+ {name} : Name of the column
+ {study} : Name of the study
+ {period} : Period used
+ Examples:
+ 'study: {study} - period: {period}'
+ detail : bool
+ If True the supporting data/calculations
+ are included in the chart
+ study_colors : string or [string]
+ Colors to be used for the studies
+
+ Study Specific Parameters
+ -------------------------
+ RSI
+ rsi_upper : int (0,100]
+ Level for the upper rsi band
+ default : 70
+ rsi_lower : int (0,100]
+ Level for the lower rsi band
+ default : 30
+ CCI
+ cci_upper : int
+ Level for the upper cci band
+ default : 100
+ cci_lower : int
+ Level for the lower cci band
+ default : -100
+ BOLL
+ boll_std : int or float
+ Number of standard deviations
+ MACD
+ fast_period : int
+ Number of periods for the fast moving average
+ slow_period : int
+ Number of periods for the slow moving average
+ signal_period : int
+ Number of periods for the signal
+ CORREL
+ how : string
+ Method for the correlation calculation
+ values
+ pct_cht
+ diff
+
+ """
+
+ if 'columns' in iplot_kwargs:
+ column=iplot_kwargs.pop('columns')
+
+ if 'period' in iplot_kwargs:
+ periods=iplot_kwargs.pop('period')
+
+ if 'world_readable' in iplot_kwargs:
+ sharing=iplot_kwargs.pop('world_readable')
+
+ if 'study_color' in iplot_kwargs:
+ iplot_kwargs['study_colors']=iplot_kwargs.pop('study_color')
+
+ if sharing is None:
+ sharing = auth.get_config_file()['sharing']
+ if isinstance(sharing,bool):
+ if sharing:
+ sharing='public'
+ else:
+ sharing='private'
+ iplot_kwargs['sharing']=sharing
+ if theme is None:
+ theme = iplot_kwargs.pop('study_theme',auth.get_config_file()['theme'])
+
+ if not filename:
+ if 'title' in iplot_kwargs:
+ filename=iplot_kwargs['title']
+ else:
+ filename='Plotly Playground {0}'.format(time.strftime("%Y-%m-%d %H:%M:%S"))
+
+ def get_subplots(figures):
+ shape=(len(figures),1)
+ layout=tools.get_base_layout(figures)
+ subplots=tools.subplots(figures,shape=shape,shared_xaxes=True,base_layout=layout)
+ if len(figures)==2:
+ subplots['layout']['yaxis1']['domain']=[.27,1.0]
+ subplots['layout']['yaxis2']['domain']=[0,.25]
+ return subplots
+
+ def get_study(df,func,iplot_kwargs,iplot_study_kwargs,str=None,include=False,column=None,inset=False):
+ df=df.copy()
+ if inset:
+ if not column:
+ if isinstance(df,pd.DataFrame):
+ column=df.keys().tolist()
+ else:
+ df=pd.DataFrame(df)
+ column=df.keys().tolist()
+ if 'legend' in iplot_kwargs:
+ iplot_study_kwargs['legend']=iplot_kwargs['legend']
+ fig_0=df.figure(**iplot_kwargs)
+ df_ta=func(df,column=column,include=False,str=str,**study_kwargs)
+ kind=iplot_kwargs['kind'] if 'kind' in iplot_kwargs else ''
+ iplot_study_kwargs['kind']='scatter'
+ iplot_study_kwargs['colors']=iplot_study_kwargs.get('colors',['blue','green','red'] if study=='dmi' else 'blue')
+ fig_1=df_ta.figure(theme=theme,**iplot_study_kwargs)
+ if kind in ['candle','ohlc']:
+ for i in fig_1['data']:
+ i['x']=[pd.Timestamp(_) for _ in i['x']]
+ if inset:
+ figure=tools.merge_figures([fig_0,fig_1]) if include else fig_1
+ else:
+ figure=get_subplots([fig_0,fig_1]) if include else fig_1
+ return figure
+
+ study_kwargs={}
+ iplot_study_kwargs={}
+
+ study_kwargs=check_kwargs(iplot_kwargs,__TA_KWARGS,{},clean_origin=True)
+ iplot_study_kwargs=kwargs_from_keyword(iplot_kwargs,{},'study')
+
+ study_kwargs.update({'periods':periods})
+
+ ta_func = eval('ta.{0}'.format(study))
+
+ inset=study in ('sma','boll','ema','atr','ptps')
+ figure=get_study(self,ta_func,iplot_kwargs,iplot_study_kwargs,include=include,
+ column=column,str=str,inset=inset)
+
+ ## Add Bands
+ if study in ('rsi','cci'):
+ bands= {'rsi':(30,70),
+ 'cci':(-100,100)}
+ _upper=study_kwargs.get('{0}_upper'.format(study),bands[study][0])
+ _lower=study_kwargs.get('{0}_lower'.format(study),bands[study][1])
+ yref='y2' if include else 'y1'
+ shapes=[tools.get_shape(y=i,yref=yref,color=j,dash='dash') for (i,j) in [(_lower,'green'),(_upper,'red')]]
+ figure['layout']['shapes']=shapes
+
+ # if study=='rsi':
+ # rsi_upper=study_kwargs.get('rsi_upper',70)
+ # rsi_lower=study_kwargs.get('rsi_lower',30)
+ # yref='y2' if include else 'y1'
+ # shapes=[tools.get_shape(y=i,yref=yref,color=j,dash='dash') for (i,j) in [(rsi_lower,'green'),(rsi_upper,'red')]]
+ # figure['layout']['shapes']=shapes
+
+ # if study=='cci':
+ # cci_upper=study_kwargs.get('cci_upper',100)
+ # cci_lower=study_kwargs.get('cci_lower',-100)
+ # yref='y2' if include else 'y1'
+ # shapes=[tools.get_shape(y=i,yref=yref,color=j,dash='dash') for (i,j) in [(cci_lower,'green'),(cci_upper,'red')]]
+ # figure['layout']['shapes']=shapes
+
+ ## Exports
+
+ if asFigure:
+ return figure
+ else:
+ return iplot(figure,sharing=sharing,filename=filename)
+
+def _fig_iplot(self,validate=True,sharing=None,filename='',
+ online=None,asImage=False,asUrl=False,asPlot=False,
+ dimensions=None,display_image=True,**kwargs):
+ """
+ Plots a figure in IPython
+
+ figure : figure
+ Plotly figure to be charted
+ validate : bool
+ If True then all values are validated before
+ it is charted
+ sharing : string
+ Sets the sharing level permission
+ public - anyone can see this chart
+ private - only you can see this chart
+ secret - only people with the link can see the chart
+ filename : string
+ Name to be used to save the file in the server, or as an image
+ online : bool
+ If True then the chart is rendered on the server
+ even when running in offline mode.
+ asImage : bool
+ If True it returns an Image (png)
+ In ONLINE mode:
+ Image file is saved in the working directory
+ Accepts:
+ filename
+ dimensions
+ scale
+ display_image
+ In OFFLINE mode:
+ Image file is downloaded (downloads folder) and a
+ regular plotly chart is displayed in Jupyter
+ Accepts:
+ filename
+ dimensions
+ asUrl : bool
+ If True the chart url/path is returned. No chart is displayed.
+ If Online : the URL is returned
+ If Offline : the local path is returned
+ asPlot : bool
+ If True the chart opens in browser
+ dimensions : tuple(int,int)
+ Dimensions for image
+ (width,height)
+ display_image : bool
+ If true, then the image is displayed after it has been saved
+ Requires Jupyter Notebook
+ onlh valide when asImage=True
+
+ Other Kwargs
+ ============
+
+ legend : bool
+ If False then the legend will not be shown
+ """
+ return iplot(self,validate=validate,sharing=sharing,filename=filename,
+ online=online,asImage=asImage,asUrl=asUrl,asPlot=asPlot,
+ dimensions=dimensions,display_image=display_image,**kwargs)
+
+
+pd.DataFrame.to_iplot=_to_iplot
+pd.DataFrame.scatter_matrix=_scatter_matrix
+pd.DataFrame.figure=_figure
+pd.DataFrame.layout=_layout
+pd.DataFrame.ta_plot=_ta_plot
+pd.DataFrame.iplot=_iplot
+pd.DataFrame.ta_figure=_ta_figure
+pd.Series.ta_figure=_ta_figure
+pd.Series.ta_plot=_ta_plot
+pd.Series.figure=_figure
+pd.Series.to_iplot=_to_iplot
+pd.Series.iplot=_iplot
+go.Figure.iplot=_fig_iplot
+
+
+