statsmodels.graphics.factorplots.interaction_plot

statsmodels.graphics.factorplots.interaction_plot(x, trace, response, func=<function mean>, ax=None, plottype='b', xlabel=None, ylabel=None, colors=None, markers=None, linestyles=None, legendloc='best', legendtitle=None, **kwargs)[source]

Interaction plot for factor level statistics.

Note. If categorial factors are supplied levels will be internally recoded to integers. This ensures matplotlib compatibility. Uses a DataFrame to calculate an aggregate statistic for each level of the factor or group given by trace.

Parameters:
xarray_like

The x factor levels constitute the x-axis. If a pandas.Series is given its name will be used in xlabel if xlabel is None.

tracearray_like

The trace factor levels will be drawn as lines in the plot. If trace is a pandas.Series its name will be used as the legendtitle if legendtitle is None.

responsearray_like

The reponse or dependent variable. If a pandas.Series is given its name will be used in ylabel if ylabel is None.

funcfunction

Anything accepted by pandas.DataFrame.aggregate. This is applied to the response variable grouped by the trace levels.

axaxes, optional

Matplotlib axes instance

plottypestr {‘line’, ‘scatter’, ‘both’}, optional

The type of plot to return. Can be ‘l’, ‘s’, or ‘b’

xlabelstr, optional

Label to use for x. Default is ‘X’. If x is a pandas.Series it will use the series names.

ylabelstr, optional

Label to use for response. Default is ‘func of response’. If response is a pandas.Series it will use the series names.

colorslist, optional

If given, must have length == number of levels in trace.

markerslist, optional

If given, must have length == number of levels in trace

linestyleslist, optional

If given, must have length == number of levels in trace.

legendloc{None, str, int}

Location passed to the legend command.

legendtitle{None, str}

Title of the legend.

**kwargs

These will be passed to the plot command used either plot or scatter. If you want to control the overall plotting options, use kwargs.

Returns:
Figure

The figure given by ax.figure or a new instance.

Examples

>>> import numpy as np
>>> np.random.seed(12345)
>>> weight = np.random.randint(1,4,size=60)
>>> duration = np.random.randint(1,3,size=60)
>>> days = np.log(np.random.randint(1,30, size=60))
>>> fig = interaction_plot(weight, duration, days,
...             colors=['red','blue'], markers=['D','^'], ms=10)
>>> import matplotlib.pyplot as plt
>>> plt.show()

(Source code, png, hires.png, pdf)

../_images/statsmodels-graphics-factorplots-interaction_plot-1.png