stack bar plot in matplotlib and add label to each section

Question

I am trying to replicate the following image in matplotlib and it seems barh is my only option. Though it appears that you can\'t stack barh graphs

Answer 1

• The easies way to plot a horizontal or vertical stacked bar, is to load the data into a pandas.DataFrame
  • This will plot, and annotate correctly, even when all categories ('People'), don't have all segments (e.g. some value is 0 or NaN)
• Once the data is in the dataframe:
  1. It's easier to manipulate and analyze
  2. It can be plotted with the matplotlib engine, using:
     • pandas.DataFrame.plot.barh
       • label_text = f'{width}' for annotations
     • pandas.DataFrame.plot.bar
       • label_text = f'{height}' for annotations
       • SO: Vertical Stacked Bar Chart with Centered Labels
• These methods return a matplotlib.axes.Axes or a numpy.ndarray of them.
• 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 the 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'{width:.2f}%', so any additional text can be added as needed.

Create a DataFrame

import pandas as pd
import numpy as np

# create sample data as shown in the OP
np.random.seed(365)
people = ('A','B','C','D','E','F','G','H')
bottomdata = 3 + 10 * np.random.rand(len(people))
topdata = 3 + 10 * np.random.rand(len(people))

# create the dataframe
df = pd.DataFrame({'Female': bottomdata, 'Male': topdata}, index=people)

# display(df)
   Female   Male
A   12.41   7.42
B    9.42   4.10
C    9.85   7.38
D    8.89  10.53
E    8.44   5.92
F    6.68  11.86
G   10.67  12.97
H    6.05   7.87

Plot and Annotate

• Plotting the bar, is 1 line, the remainder is annotating the rectangles

# plot the dataframe with 1 line
ax = df.plot.barh(stacked=True, figsize=(8, 6))

# .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'{width:.2f}%'  # f'{width:.2f}' to format decimal values
    
    # ax.text(x, y, text)
    label_x = x + width / 2
    label_y = y + height / 2
    
    # only plot labels greater than given width
    if width > 0:
        ax.text(label_x, label_y, label_text, ha='center', va='center', fontsize=8)

# move the legend
ax.legend(bbox_to_anchor=(1.05, 1), loc='upper left', borderaxespad=0.)

# add labels
ax.set_ylabel("People", fontsize=18)
ax.set_xlabel("Percent", fontsize=18)
plt.show()

Example with Missing Segment

# set one of the dataframe values to 0
df.iloc[4, 1] = 0

• Note the annotations are all in the correct location from df.