Matplotlib: Stacked and Grouped Bar Plot

matplotlib_barplot.md

Stacked and Grouped Bar Plot

Oddly enough ggplot2 has no support for a stacked and grouped (position="dodge") bar plot. The seaborn python package, although excellent, also does not provide an alternative. However, I knew it was surely possible to make such a plot in regular matplotlib. Matplotlib, although sometimes clunky, gives you enough flexibility to precisely place plotting elements which is needed for a stacked and grouped bar plot.

Below is a working example of making a stacked and grouped bar plot.

import seaborn as sns
import matplotlib.pyplot as plt
import numpy as np

# make up some fake data
pos_mut_pcts = np.array([20, 10, 5, 7.5, 30, 50])
pos_cna_pcts = np.array([10, 0, 0, 7.5, 10, 0])
pos_both_pcts = np.array([10, 0, 0, 0, 0, 0])
neg_mut_pcts = np.array([10, 30, 5, 0, 10, 25])
neg_cna_pcts = np.array([5, 0, 7.5, 0, 0, 10])
neg_both_pcts = np.array([0, 0, 0, 0, 0, 10])
genes = ['PIK3CA', 'PTEN', 'CDKN2A', 'FBXW7', 'KRAS', 'TP53']

with sns.axes_style("white"):
    sns.set_style("ticks")
    sns.set_context("talk")
    
    # plot details
    bar_width = 0.35
    epsilon = .015
    line_width = 1
    opacity = 0.7
    pos_bar_positions = np.arange(len(pos_mut_pcts))
    neg_bar_positions = pos_bar_positions + bar_width

    # make bar plots
    hpv_pos_mut_bar = plt.bar(pos_bar_positions, pos_mut_pcts, bar_width,
                              color='#ED0020',
                              label='HPV+ Mutations')
    hpv_pos_cna_bar = plt.bar(pos_bar_positions, pos_cna_pcts, bar_width-epsilon,
                              bottom=pos_mut_pcts,
                              alpha=opacity,
                              color='white',
                              edgecolor='#ED0020',
                              linewidth=line_width,
                              hatch='//',
                              label='HPV+ CNA')
    hpv_pos_both_bar = plt.bar(pos_bar_positions, pos_both_pcts, bar_width-epsilon,
                               bottom=pos_cna_pcts+pos_mut_pcts,
                               alpha=opacity,
                               color='white',
                               edgecolor='#ED0020',
                               linewidth=line_width,
                               hatch='0',
                               label='HPV+ Both')
    hpv_neg_mut_bar = plt.bar(neg_bar_positions, neg_mut_pcts, bar_width,
                              color='#0000DD',
                              label='HPV- Mutations')
    hpv_neg_cna_bar = plt.bar(neg_bar_positions, neg_cna_pcts, bar_width-epsilon,
                              bottom=neg_mut_pcts,
                              color="white",
                              hatch='//',
                              edgecolor='#0000DD',
                              ecolor="#0000DD",
                              linewidth=line_width,
                              label='HPV- CNA')
    hpv_neg_both_bar = plt.bar(neg_bar_positions, neg_both_pcts, bar_width-epsilon,
                               bottom=neg_cna_pcts+neg_mut_pcts,
                               color="white",
                               hatch='0',
                               edgecolor='#0000DD',
                               ecolor="#0000DD",
                               linewidth=line_width,
                               label='HPV- Both')
    plt.xticks(neg_bar_positions, genes, rotation=45)
    plt.ylabel('Percentage of Samples')
    plt.legend(loc='best')
    sns.despine()