Custom annotation of text in seaborn heatmap

Question

I want to assign different fontsizes for positive and negative values in the following heatmap plotted using seaborn.

    import seaborn as sns  # % matplotlib inline
    import matplotlib.pyplot as plt

    data = np.array([[0.000000, 0.000000], [-0.231049, 0.000000], [0.231049, 0.000000]])
    data = {0: [0.000000, 0.000000], 1: [2.31049, 0.000000], 2: [-0.231049, 0.000000]}
    df = pd.DataFrame.from_dict(data, orient='index')
    sns.heatmap(
        df, cmap='bwr', vmax=10, vmin=0, annot=True, fmt='f',
        linewidths=0.25, annot_kws={"fontsize": 16}, center=0, square=True
    )
    sns.heatmap(
        df, cmap='bwr', vmax=0, vmin=-10, annot=True, fmt='f',
        linewidths=0.25, annot_kws={"fontsize": 6}, center=0, square=True
    )
    plt.show()

I tried to specify the min and max and plot, in two steps but the colors and fonts aren't-displayed right.

Suggestions on how to fix this will be of great help.

JohanC · Accepted Answer · 2023-01-30T16:21:42.413

To make it easier to keep the properties in sync, the code below uses a for loop. For the positive part, the dataframe is filtered to only contain the positive values. (Internally, pandas fills in NaN for the values that get filtered away, and seaborn leaves those cells blank.)

vmin and vmax are set to the same values for both the negative and positive part of the loop. That way, the colorbar will show all values. To avoid drawing the colorbar twice, cbar=False once.

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

df = pd.DataFrame(np.random.randint(-10, 11, (12, 12)))
fig, ax = plt.subplots()
for posneg in ['pos', 'neg']:
    sns.heatmap(
        df[df > 0] if posneg == 'pos' else df[df < 0],
        cmap='bwr', vmin=-10, vmax=10, center=0, annot=True, fmt='.0f',
        annot_kws={"fontsize": 16 if posneg == 'pos' else 8},
        cbar=(posneg != 'pos'), cbar_kws={'ticks': range(-10, 11, 2)},
        linewidths=0.25, square=True, ax=ax
    )
plt.show()

PS: The code above uses if/else inside some of the arguments. Such a conditional expression can be handy when only something short is involved, or in a list comprehension.

An alternative would be to use a normal if test together with variables, e.g.:

for posneg in ['pos', 'neg']:
    if posneg == 'pos':
        df_filtered = df[df > 0]
        fontsize = 16
        fontweight = 'bold'
    else:
        df_filtered = df[df < 0]
        fontsize = 12
        fontweight = 'light'
    sns.heatmap(
        df_filtered,
        cmap='bwr', vmin=-10, vmax=10, center=0, annot=True, fmt='.0f',
        annot_kws={"fontweight": fontweight, "fontsize": fontsize},
        cbar=(posneg != 'pos'), cbar_kws={'ticks': range(-10, 11, 2)},
        linewidths=0.25, square=True, ax=ax
    )

Thanks so much. This works great! Can we change the font weights using annot_kws? — Natasha, Jan 30 '23 at 09:15
You mean like `annot_kws={"fontweight": 'bold' if posneg == 'pos' else 'light'}`? No problem. — JohanC, Jan 30 '23 at 11:25
If you don't like the `if`s inside the call, or when there are too many options to change, you can also add a normal if-test assigning options to variables. — JohanC, Jan 30 '23 at 11:58
Thanks for the suggestion. Could you please add a small example for that as an edit? — Natasha, Jan 30 '23 at 12:18

Custom annotation of text in seaborn heatmap

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