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Learn more about Teams 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.

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).
                Are you sure that this will also synchronize the colors? The way I see it it only will plot the colormap for the first axis, but the colormap will not necessarily be compatible to the other axes.
– bayer
                Jan 25, 2016 at 13:22
                @Rotkiv, this is actually setting cbar as equal to i == 0, i.e. cbar = True if i == 0returns True.
– KevL
                Nov 9, 2017 at 16:19
                It would be nice to have a way to synchronise the colours automatically, for when you don't know the limits a priori (and e.g. want to use the robust option)
– oulenz
                Feb 7, 2021 at 12:15
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'})
        
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