One colorbar for seaborn heatmaps in subplot

Question

Here is an example that shows a colorbar for each subplot:

import seaborn as sns import matplotlib.pyplot as plt import pandas as pd import numpy as np  df = pd.DataFrame(np.random.random((10,10,)))  fig,axn = plt.subplots(2, 2, sharex=True, sharey=True)  for ax in axn.flat:     sns.heatmap(df, ax=ax) 

How can I remove the colorbars for each subplot? I'd like to have only one colorbar that is either vertically or horizontally oriented. I know I have access to each colorbar axes via fig.get_axes()[:-4], but how can I remove it from them entirely from the plot? I don't think there is an option to opt out of drawing the colorbar when heatmap is called.

Answer 1

The cbar parameter controls whether a colorbar should be added, and the cbar_ax parameter can optionally specify the axes where the colorbar should go. So, you could do:

import seaborn as sns import matplotlib.pyplot as plt import pandas as pd import numpy as np  df = pd.DataFrame(np.random.random((10,10,)))  fig, axn = plt.subplots(2, 2, sharex=True, sharey=True) cbar_ax = fig.add_axes([.91, .3, .03, .4])  for i, ax in enumerate(axn.flat):     sns.heatmap(df, ax=ax,                 cbar=i == 0,                 vmin=0, vmax=1,                 cbar_ax=None if i else cbar_ax)  fig.tight_layout(rect=[0, 0, .9, 1]) 

(You'll get a warning about tight_layout here, but it actually is correct because we placed cbar_ax explicitly. If you don't like seeing the warning, you can also call tight_layout before plotting, but it won't be as tight).

Answer 2

It's actually not necessary to set cbar_ax to none for the first 3 subplots. You can set cbar_ax=cbar_ax for all 4 subplots and it will just paint the colorbar in the exact same spot 4 times, which dones't affect the look at all.

This works better for those using FacetGrid, e.g. given a dataframe df:

def draw_heatmap(*args, **kwargs):     data = kwargs.pop('data')     d = data.pivot(index=args[1], columns=args[0], values=args[2])     sns.heatmap(d, **kwargs)  g = sns.FacetGrid(df, col='col_name', col_wrap=2, margin_titles=True, sharey=True)  cbar_ax = g.fig.add_axes([.91, .15, .03, .7]) g = g.map_dataframe(draw_heatmap, 'col_col', 'index_col', 'val_col', annot=True,                      cmap='Spectral', cbar_ax=cbar_ax, cbar_kws={'label': 'color_bar_label'})