How to Center Data Labels in a Matplotlib Stacked Bar Chart?

Stacked Bar Chart with Centered Labels: An Improved Solution Using bar_label

In matplotlib, a refined method for accurately centering data labels in a stacked bar chart is available using the bar_label function. Here's how it's done:

1. Import necessary modules: Begin by importing the essential libraries.

import pandas as pd
import matplotlib.pyplot as plt

2. Create and populate your DataFrame: To create a stacked bar chart, it's recommended to use a pandas DataFrame. Here's an example DataFrame with three columns: 'A', 'B', and 'C'.

# sample DataFrame
df = pd.DataFrame({'A': [45, 17, 47], 'B': [91, 70, 72], 'C': [68, 43, 13]})

3. Plot the stacked bar chart: Utilize the DataFrame to plot the stacked bar chart.

ax = df.plot(kind='bar', stacked=True, figsize=(8, 6), rot=0, xlabel='Class', ylabel='Count')

4. Label the bars: Now, let's label the bars while ensuring they are centered. Use bar_label to accomplish this.

for c in ax.containers:
    ax.bar_label(c, label_type='center')

Optional Customization

• Zero or small labels: For segments with zero or small values, adjust the label visibility as needed. For example, display the values only when they exceed a certain threshold or use the label_type='edge' option.

labels = [v.get_height() if v.get_height() > 0 else '' for v in c]  # for segments with small or zero values

• Custom format: Modify the label format to meet your requirements.

ax.bar_label(c, fmt=lambda x: f'{x:.0f}' if x > 0 else '', label_type='center')  # to show no decimal places

Seaborn Alternative

If you prefer working with seaborn, you can also create a stacked bar chart and label the bars.

1. Prepare the DataFrame: Similar to matplotlib, create a pandas DataFrame with the data.
2. Convert DataFrame to long form: seaborn requires the DataFrame to be in a long form, which can be achieved using melt.
3. Plot the chart and label the bars: Plot the stacked bar chart and apply bar_label as in matplotlib.

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