calour.plotting.plot_stacked_bar¶

calour.plotting.plot_stacked_bar(exp: calour.experiment.Experiment, field=None, sample_color_bars=None, color_bar_label=True, barx_label_kwargs=None, barx_width=0.3, barx_colors=None, title=None, figsize=(12, 8), legend_size='small', xtick=False, cmap='Paired')[source]¶

Plot the stacked bar for feature abundances.

Note

This function is also available as a class method Experiment.plot_stacked_bar()

Parameters:	exp (Experiment) – Input experiment object. field (str, or None) – a column name in feature metadata. the values in the column will be used as the legend labels sample_color_bars (list, optional) – list of column names in the sample metadata. It plots a color bar for each unique column to indicate sample group. It doesn’t plot color bars by default (None) color_bar_label (bool) – whether to show the label on the color bars barx_label_kwargs (dict, optional) – keyword arguments to pass in for matplotlib.axes.Axes.annotate() for labels on the X-axis bar barx_width (float, optional) – the width of the color bar barx_colors (dict, optional) – the colors for each unique value in the values list. if it is None, it will use Dark2 discrete color map in a cycling way. title (str) – figure title figsize (tuple of numeric) – figure size passed to figsize in plt.figure legend_size (str or int) – passed to fontsize in ax.legend() xtick (str, False, or None) – how to draw ticks and tick labels on x axis. str: use a column name in sample metadata; None: use sample IDs; False: do not draw ticks. cmap (string) – matplotlib qualitative colormap
Returns:	The Figure object containing the plot.
Return type:	matplotlib.figure.Figure