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Stacked Percentage Bar Plot In MatPlotLib

• Difficulty Level : Hard
• Last Updated : 01 Oct, 2020

A Stacked Percentage Bar Chart is a simple bar chart in the stacked form with a percentage of each subgroup in a group. Stacked bar plots represent different groups on the top of one another. The height of the bar depends on the resulting height of the combination of the results of the groups. It goes from the bottom to the value instead of going from zero to value. A percent stacked bar chart is almost the same as a stacked barchart. Subgroups are displayed on top of each other, but data are normalized to make in a sort that the sum of every subgroup is the same as the total for each one.

The dataset used in the following examples is shown below :

The dataset can be downloaded from here.

Procedure: The procedure to draw Stacked Percentage Bar Chart is the following steps which are described below with examples :

1. Draw a stacked bar chart using data (dataset, dictionary, etc.).

Python3

 # importing packages import pandas as pd import matplotlib.pyplot as plt    # load dataset df = pd.read_excel("Hours.xlsx")    # view dataset print(df)    # plot a Stacked Bar Chart using matplotlib df.plot(     x = 'Name',     kind = 'barh',     stacked = True,     title = 'Stacked Bar Graph',     mark_right = True)

Output:

Name   Studied     Slept      Other
0    Ram  4.855064  9.639962   9.504974
1   Yash  8.625440  0.058927  15.315634
2  Alpha  3.828192  0.723199  19.448609
3   Deep  7.150955  3.899420  12.949625
4   Alex  6.477900  8.198181   9.323919
5   Jack  1.922270  1.331427  20.746303
6  Sufia  8.978216  0.993438  14.028347

2. Add Percentage on subgroups of each group.

Python3

 # importing packages import pandas as pd import numpy as np import matplotlib.pyplot as plt    # load dataset df = pd.read_excel("Hours.xlsx")    # view dataset print(df)    # plot a Stacked Bar Chart using matplotlib df.plot(   x = 'Name',    kind = 'barh',    stacked = True,    title = 'Percentage Stacked Bar Graph',    mark_right = True)    df_total = df["Studied"] + df["Slept"] + df["Other"] df_rel = df[df.columns[1:]].div(df_total, 0)*100    for n in df_rel:     for i, (cs, ab, pc) in enumerate(zip(df.iloc[:, 1:].cumsum(1)[n],                                           df[n], df_rel[n])):         plt.text(cs - ab / 2, i, str(np.round(pc, 1)) + '%',                   va = 'center', ha = 'center')

Output:

Name   Studied     Slept      Other
0    Ram  4.855064  9.639962   9.504974
1   Yash  8.625440  0.058927  15.315634
2  Alpha  3.828192  0.723199  19.448609
3   Deep  7.150955  3.899420  12.949625
4   Alex  6.477900  8.198181   9.323919
5   Jack  1.922270  1.331427  20.746303
6  Sufia  8.978216  0.993438  14.028347

Python3

 # importing packages import pandas as pd import numpy as np import matplotlib.pyplot as plt    # load dataset df = pd.read_xlsx("Hours.xlsx")    # view dataset print(df)    # plot a Stacked Bar Chart using matplotlib df.plot(   x = 'Name',    kind = 'barh',    stacked = True,    title = 'Percentage Stacked Bar Graph',    mark_right = True)    df_total = df["Studied"] + df["Slept"] + df["Other"] df_rel = df[df.columns[1:]].div(df_total, 0) * 100    for n in df_rel:     for i, (cs, ab, pc) in enumerate(zip(df.iloc[:, 1:].cumsum(1)[n],                                           df[n], df_rel[n])):         plt.text(cs - ab / 2, i, str(np.round(pc, 1)) + '%',                   va = 'center', ha = 'center', rotation = 20, fontsize = 8)

Output:

Name   Studied     Slept      Other
0    Ram  4.855064  9.639962   9.504974
1   Yash  8.625440  0.058927  15.315634
2  Alpha  3.828192  0.723199  19.448609
3   Deep  7.150955  3.899420  12.949625
4   Alex  6.477900  8.198181   9.323919
5   Jack  1.922270  1.331427  20.746303
6  Sufia  8.978216  0.993438  14.028347

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