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 easily scales.
• Putting the data into a pandas.DataFrame is the easiest way to plot a stacked bar plot.
• Using pandas.DataFrame.plot.bar(stacked=True), or pandas.DataFrame.plot(kind='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 - Contains a list of many .bar_label examples
• 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

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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