bootstrap_plot(series, fig=None, size=50, samples=500, **kwds)
The bootstrap plot is used to estimate the uncertainty of a statistic by relaying on random sampling with replacement . This function will generate bootstrapping plots for mean, median and mid-range statistics for the given number of samples of the given size.
<Unimplemented 'footnote' '.. [1] "Bootstrapping (statistics)" in https://en.wikipedia.org/wiki/Bootstrapping_%28statistics%29'>
Series from where to get the samplings for the bootstrapping.
If given, it will use the :None:None:`fig` reference for plotting instead of creating a new one with default parameters.
Number of data points to consider during each sampling. It must be less than or equal to the length of the series
.
Number of times the bootstrap procedure is performed.
Options to pass to matplotlib plotting method.
Matplotlib figure.
Bootstrap plot on mean, median and mid-range statistics.
DataFrame.plot
Basic plotting for DataFrame objects.
Series.plot
Basic plotting for Series objects.
This example draws a basic bootstrap plot for a Series.
.. plot::
('context', 'close-figs')
See :>>> s = pd.Series(np.random.uniform(size=100)) >>> pd.plotting.bootstrap_plot(s) <Figure size 640x480 with 6 Axes>
Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.
Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)
SVG is more flexible but power hungry; and does not scale well to 50 + nodes.
All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them