Plotting

The following functions are contained in the pandas.plotting module.

`andrews_curves`(frame, class_column[, ax, ...])	Generate a matplotlib plot of Andrews curves, for visualising clusters of multivariate data.
`autocorrelation_plot`(series[, ax])	Autocorrelation plot for time series.
`bootstrap_plot`(series[, fig, size, samples])	Bootstrap plot on mean, median and mid-range statistics.
`boxplot`(data[, column, by, ax, fontsize, ...])	Make a box plot from DataFrame columns.
`deregister_matplotlib_converters`()	Remove pandas formatters and converters.
`lag_plot`(series[, lag, ax])	Lag plot for time series.
`parallel_coordinates`(frame, class_column[, ...])	Parallel coordinates plotting.
`plot_params`	Stores pandas plotting options.
`radviz`(frame, class_column[, ax, color, ...])	Plot a multidimensional dataset in 2D.
`register_matplotlib_converters`()	Register pandas formatters and converters with matplotlib.
`scatter_matrix`(frame[, alpha, figsize, ax, ...])	Draw a matrix of scatter plots.
`table`(ax, data[, rowLabels, colLabels])	Helper function to convert DataFrame and Series to matplotlib.table.

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Licensed under the 3-clause BSD License.
https://pandas.pydata.org/pandas-docs/version/1.3.4/reference/plotting.html