def get_traces(trace, value, type, color=None, width=0.2, opacity=0.3):
if "percent" in type:
y_up = trace["y"] * (1 + value / 100.00)
y_down = trace["y"] * (1 - value / 100.00)
else:
y_up = trace["y"] + value
y_down = trace["y"] - value
y = trace["y"]
upper = Scatter(y=y_up, mode="lines", showlegend=False, line=Line(width=width), x=trace["x"])
if "yaxis" in trace:
upper["yaxis"] = trace["yaxis"]
if color:
color = normalize(color)
else:
if "color" in trace["line"]:
color = trace["line"]["color"]
else:
color = "charcoal"
upper["line"]["color"] = color
lower = upper.copy()
name = trace["name"] + "_" if "name" in trace else ""
upper.update(name=name + "upper")
color = to_rgba(normalize(color), opacity)
lower.update(fill="tonexty", fillcolor=color, name=name + "lower", y=y_down)
return upper, lower
def get_shape(
kind="line",
x=None,
y=None,
x0=None,
y0=None,
x1=None,
y1=None,
span=0,
color="red",
dash="solid",
width=1,
fillcolor=None,
fill=False,
opacity=1,
xref="x",
yref="y",
):
"""
Returns a plotly shape
Parameters:
-----------
kind : string
Shape kind
line
rect
circle
x : float
x values for the shape.
This assumes x0=x1
x0 : float
x0 value for the shape
x1 : float
x1 value for the shape
y : float
y values for the shape.
This assumes y0=y1
y0 : float
y0 value for the shape
y1 : float
y1 value for the shape
color : string
color for shape line
dash : string
line style
solid
dash
dashdot
dot
width : int
line width
fillcolor : string
shape fill color
fill : bool
If True then fill shape
If not fillcolor then the
line color will be used
opacity : float [0,1]
opacity of the fill
xref : string
Sets the x coordinate system
which this object refers to
'x'
'paper'
'x2' etc
yref : string
Sets the y coordinate system
which this object refers to
'y'
'paper'
'y2' etc
"""
if not x1:
if not x0:
if not x:
xref = "paper"
x0 = 0
x1 = 1
else:
x0 = x1 = x
else:
x1 = x0
if not y1:
if not y0:
if not y:
yref = "paper"
y0 = 0
y1 = 1
else:
y0 = y1 = y
else:
y1 = y0
shape = {
"x0": x0,
"y0": y0,
"x1": x1,
"y1": y1,
"line": {"color": normalize(color), "width": width, "dash": dash},
"xref": xref,
"yref": yref,
}
if kind == "line":
shape["type"] = "line"
elif kind == "circle":
shape["type"] = "circle"
elif kind == "rect":
shape["type"] = "rect"
else:
raise Exception("Invalid or unkown shape type : {0}".format(kind))
if (fill or fillcolor) and kind != "line":
fillcolor = color if not fillcolor else fillcolor
fillcolor = to_rgba(normalize(fillcolor), opacity)
shape["fillcolor"] = fillcolor
return shape
def _to_iplot(self,colors=None,colorscale=None,kind='scatter',mode='lines',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
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(_)) 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=df.sum().sort(inplace=False,ascending=False).keys()
else:
keys=df.keys()
else:
keys=df.keys()
colors=get_colors(colors,colorscale,keys)
for key in keys:
lines[key]={}
lines[key]["x"]=x
lines[key]["y"]=df[key].fillna('').values
lines[key]["name"]=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,'dash':dash}
lines[key]["mode"]=mode
if 'marker' in mode:
lines[key]["marker"]=Marker(symbol=symbol,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=[Bar(lines[key]) for key in keys]
else:
lines_plotly=[Scatter(lines[key]) for key in keys]
for trace in lines_plotly:
if isinstance(trace['name'],pd.tslib.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=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=Data(lines_plotly)
data.extend(mean_lines)
return data
return Data(lines_plotly)
def _to_iplot(self,colors=None,colorscale=None,kind='scatter',mode='lines',symbol='dot',size='12',fill=False,
width=3,sortbars=False,keys=False,bestfit=False,bestfit_colors=None,asDates=False,**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
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
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 df.index.__class__.__name__ in ('PeriodIndex','DatetimeIndex'):
if asDates:
df.index=df.index.date
x=df.index.format()
else:
x = df.index.values
lines={}
if type(df)==pd.core.series.Series:
df=pd.DataFrame({df.name:df})
if not keys:
if kind=='bar':
if sortbars:
keys=df.sum().sort(inplace=False,ascending=False).keys()
else:
keys=df.keys()
else:
keys=df.keys()
colors=get_colors(colors,colorscale,keys)
for key in keys:
lines[key]={}
lines[key]["x"]=x
lines[key]["y"]=df[key].fillna('').values
lines[key]["name"]=key
if kind=='bar':
lines[key]["marker"]={'color':to_rgba(colors[key],.6),'line':{'color':colors[key],'width':1}}
else:
lines[key]["line"]={'color':colors[key],'width':width}
lines[key]["mode"]=mode
if 'marker' in mode:
lines[key]["marker"]=Marker(symbol=symbol,size=size)
if fill:
lines[key]["fill"]='tozeroy'
lines[key]["fillcolor"]=to_rgba(colors[key],.3 )
for k,v in kwargs.items():
lines[key][k]=v
if kind=='bar':
lines_plotly=[Bar(lines[key]) for key in keys]
else:
lines_plotly=[lines[key] for key in keys]
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')
for line in bestfit_lines:
line['line']['dash']='dash'
if not bestfit_colors:
line['line']['color']=to_rgba(line['line']['color'],.6)
data=Data(lines_plotly)
data.extend(bestfit_lines)
return data
return Data(lines_plotly)