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# Plotting

Note

For an overview, see Chart visualization.

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

`andrews_curves`(frame, class_column[, ax, ...]) | Generate a matplotlib plot for visualizing 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, **kwargs) | Helper function to convert DataFrame and Series to matplotlib.table.