python - Stacked Bar Chart with Centered Labels

Question

I'm trying to "robustly" center the data labels in a stacked bar chart. A simple code example and the result are given below. As you can see, the data labels aren't really centered in all rectangles. What am I missing?

import numpy as np
import matplotlib.pyplot as plt

A = [45, 17, 47]
B = [91, 70, 72]

fig = plt.figure(facecolor="white")

ax = fig.add_subplot(1, 1, 1)
bar_width = 0.5
bar_l = np.arange(1, 4)
tick_pos = [i + (bar_width / 2) for i in bar_l]

ax1 = ax.bar(bar_l, A, width=bar_width, label="A", color="green")
ax2 = ax.bar(bar_l, B, bottom=A, width=bar_width, label="B", color="blue")
ax.set_ylabel("Count", fontsize=18)
ax.set_xlabel("Class", fontsize=18)
ax.legend(loc="best")
plt.xticks(tick_pos, ["C1", "C2", "C3"], fontsize=16)
plt.yticks(fontsize=16)

for r1, r2 in zip(ax1, ax2):
    h1 = r1.get_height()
    h2 = r2.get_height()
    plt.text(r1.get_x() + r1.get_width() / 2., h1 / 2., "%d" % h1, ha="center", va="bottom", color="white", fontsize=16, fontweight="bold")
    plt.text(r2.get_x() + r2.get_width() / 2., h1 + h2 / 2., "%d" % h2, ha="center", va="bottom", color="white", fontsize=16, fontweight="bold")

plt.show()

Answer 1

• The following method is more succinct, and more easily scales with more columns.
• Putting the data into a pandas.DataFrame is the easiest way to plot a stacked bar plot.
• Using pandas.DataFrame.plot.bar(stacked=True) is the easiest way to plot a stacked bar plot.
  • This method returns a matplotlib.axes.Axes or a numpy.ndarray of them.
• Since seaborn is just a high-level API for matplotlib, these solutions also work with seaborn plots, as shown in How to annotate a seaborn barplot with the aggregated value

Imports & Test DataFrame

import pandas as pd
import matplotlib.pyplot as plt

A = [45, 17, 47]
B = [91, 70, 72]
C = [68, 43, 13]

# pandas dataframe
df = pd.DataFrame(data={'A': A, 'B': B, 'C': C})
df.index = ['C1', 'C2', 'C3']

     A   B   C
C1  45  91  68
C2  17  70  43
C3  47  72  13

Updated for matplotlib v3.4.2

• Use matplotlib.pyplot.bar_label
  • Will automatically center the values in the bar.
  • See this answer for additional details about .bar_label()
• See the matplotlib: Bar Label Demo page for additional formatting options.
• Tested with pandas v1.2.4, which is using matplotlib as the plot engine.
• If some sections of the bar plot will be zero, see my answer, which shows how to customize the labels for .bar_label().
• ax.bar_label(c, fmt='%0.0f', label_type='center') will change the number format to show no decimal places, if needed.

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

    # Optional: if the segment is small or 0, customize the labels
    labels = [v.get_height() if v.get_height() > 0 else '' for v in c]
    
    # remove the labels parameter if it's not needed for customized labels
    ax.bar_label(c, labels=labels, label_type='center')

Annotation Resources - from matplotlib v3.4.2

• Adding value labels on a matplotlib bar chart
• How to annotate each segment of a stacked bar chart
• How to plot and annotate multiple data columns in a seaborn barplot
• How to annotate a seaborn barplot with the aggregated value
• stack bar plot in matplotlib and add label to each section
• How to add multiple annotations to a barplot
• How to plot and annotate a grouped bar chart

Original Answer

• Using the .patches method unpacks a list of matplotlib.patches.Rectangle objects, one for each of the sections of the stacked bar.
  • Each .Rectangle has methods for extracting the various values that define the rectangle.
  • Each .Rectangle is in order from left to right, and bottom to top, so all the .Rectangle objects, for each level, appear in order, when iterating through .patches.
• The labels are made using an f-string, label_text = f'{height}', so any additional text can be added as needed, such as label_text = f'{height}%'
  • label_text = f'{height:0.0f}' will display numbers with no decimal places.

Plot

plt.style.use('ggplot')

ax = df.plot(stacked=True, kind='bar', figsize=(12, 8), rot='horizontal')

# .patches is everything inside of the chart
for rect in ax.patches:
    # Find where everything is located
    height = rect.get_height()
    width = rect.get_width()
    x = rect.get_x()
    y = rect.get_y()
    
    # The height of the bar is the data value and can be used as the label
    label_text = f'{height}'  # f'{height:.2f}' to format decimal values
    
    # ax.text(x, y, text)
    label_x = x + width / 2
    label_y = y + height / 2

    # plot only when height is greater than specified value
    if height > 0:
        ax.text(label_x, label_y, label_text, ha='center', va='center', fontsize=8)
    
ax.legend(bbox_to_anchor=(1.05, 1), loc='upper left', borderaxespad=0.)    
ax.set_ylabel("Count", fontsize=18)
ax.set_xlabel("Class", fontsize=18)
plt.show()

• To plot a horizontal bar:
  • kind='barh'
  • label_text = f'{width}'
  • if width > 0:
• Attribution: jsoma/chart.py