statsmodels.graphics.plot_grids.scatter_ellipse

statsmodels.graphics.plot_grids.scatter_ellipse(data, level=0.9, varnames=None, ell_kwds=None, plot_kwds=None, add_titles=False, keep_ticks=False, fig=None)

Create a grid of scatter plots with confidence ellipses

Parameters:

dataarray_like

Input data.

levelfloat or list of float, optional

The confidence level(s) of the ellipses to draw. Default is 0.9.

varnameslist[str], optional

Variable names. Used for y-axis labels, and if add_titles is True also for titles. If not given, integers 1..data.shape[1] are used.

ell_kwdsdict, optional

Additional keyword arguments passed to the ellipse patches drawn on each subplot.

plot_kwdsdict, optional

Additional keyword arguments passed to the scatter points plotted on each subplot.

add_titlesbool, optional

Whether or not to add titles to each subplot. Default is False. Titles are constructed from varnames.

keep_ticksbool, optional

If False (default), remove all axis ticks.

figFigure, optional

If given, this figure is simply returned. Otherwise a new figure is created.

Returns:

Figure

If fig is None, the created figure. Otherwise fig itself.

Notes

Looks reasonable with 5 or 6 variables, becomes too crowded with 8 and too sparse with 1.

Examples

>>> import statsmodels.api as sm
>>> import matplotlib.pyplot as plt
>>> import numpy as np

>>> from statsmodels.graphics.plot_grids import scatter_ellipse
>>> data = sm.datasets.statecrime.load_pandas().data
>>> fig = plt.figure(figsize=(8,8))
>>> scatter_ellipse(data, varnames=data.columns, fig=fig)
>>> plt.show()

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