Bar labels in matplotlib/Seaborn

Question

In version 3.4, matplotlib added automatic Bar labels: https://matplotlib.org/stable/users/whats_new.html#new-automatic-labeling-for-bar-charts

I'm trying to use this on a bar plot generated by Seaborn.

fig, axs = plt.subplots(
        nrows=2,
    )        

for i, col in enumerate(['col_1', 'col_2']):
        ax = axs[i]
        sns.barplot(
            x="class",
            y=col,
            hue="hue_col",
            data=data_df,
            edgecolor=".3",
            linewidth=0.5,
            ax=ax
        )


        ax.bar_label(ax.containers[i]) # Doesn't work

What do I need to do to make this work? example plot

user_12046409 · Answer

You can loop through the containers and call ax.bar_label(...) for each of them. Note that seaborn creates one set of bars for each hue value.

The following example uses the titanic dataset and sets ci=None to avoid the error bars overlapping with the text (if error bars are needed, one could set a lighter color, e.g. errcolor='gold').

import seaborn as sns
import matplotlib.pyplot as plt

titanic = sns.load_dataset('titanic')
fig, axs = plt.subplots(ncols=2, figsize=(12, 4))

for ax, col in zip(axs, ['age', 'fare']):
    sns.barplot(
        x='sex',
        y=col,
        hue="class",
        data=titanic,
        edgecolor=".3",
        linewidth=0.5,
        ci=None,
        ax=ax
    )
    ax.set_title('mean ' + col)
    ax.margins(y=0.1) # make room for the labels
    for bars in ax.containers:
        ax.bar_label(bars, fmt='%.1f')
plt.tight_layout()
plt.show()

Bar labels in matplotlib/Seaborn

1 Answers