pandas.plotting.bootstrap_plot

pandas.plotting.bootstrap_plot(series, fig=None, size=50, samples=500, **kwds)[source]

Bootstrap plot on mean, median and mid-range statistics.

The bootstrap plot is used to estimate the uncertainty of a statistic by relying on random sampling with replacement [1]. This function will generate bootstrapping plots for mean, median and mid-range statistics for the given number of samples of the given size.

[1]

“Bootstrapping (statistics)” in https://en.wikipedia.org/wiki/Bootstrapping_%28statistics%29

Parameters:

series:pandas.Series

Series from where to get the samplings for the bootstrapping.

fig:matplotlib.figure.Figure, default None

If given, it will use the fig reference for plotting instead of creating a new one with default parameters.

size:int, default 50

Number of data points to consider during each sampling. It must be less than or equal to the length of the series.

samples:int, default 500

Number of times the bootstrap procedure is performed.

**kwds

Options to pass to matplotlib plotting method.

Returns:

matplotlib.figure.Figure

Matplotlib figure.

See also

pandas.DataFrame.plot

Basic plotting for DataFrame objects.

pandas.Series.plot

Basic plotting for Series objects.

Examples

This example draws a basic bootstrap plot for a Series.

>>> s = pd.Series(np.random.uniform(size=100))
>>> pd.plotting.bootstrap_plot(s)  
<Figure size 640x480 with 6 Axes>