statsmodels.graphics.factorplots.interaction_plot

statsmodels.graphics.factorplots.interaction_plot(x, trace, response, func='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:

  • x (array_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.

  • trace (array_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.

  • response (array_like) – The reponse or dependent variable. If a pandas.Series is given its name will be used in ylabel if ylabel is None.

  • func (function) – Anything accepted by pandas.DataFrame.aggregate. This is applied to the response variable grouped by the trace levels.

  • ax (axes, optional) – Matplotlib axes instance

  • plottype (str {'line', 'scatter', 'both'}, optional) – The type of plot to return. Can be ‘l’, ‘s’, or ‘b’

  • xlabel (str, optional) – Label to use for x. Default is ‘X’. If x is a pandas.Series it will use the series names.

  • ylabel (str, optional) – Label to use for response. Default is ‘func of response’. If response is a pandas.Series it will use the series names.

  • colors (list, optional) – If given, must have length == number of levels in trace.

  • markers (list, optional) – If given, must have length == number of levels in trace

  • linestyles (list, 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:

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

Return type:

Figure

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