• 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 pdimport matplotlib.pyplot as pltA = [45, 17, 47]B = [91, 70, 72]C = [68, 43, 13]# pandas dataframedf = pd.DataFrame(data={'A': A, 'B': B, 'C': C})df.index = ['C1', 'C2', 'C3']     A   B   CC1  45  91  68C2  17  70  43C3  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 chartfor 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

Why you wrote va="bottom"? You have to use va="center".