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pythonpandasmatplotlibdata-transform

How to plot a horizontal stacked bar with annotations


  • I used the example for Discrete distribution as horizontal bar chart example on matplotlib Discrete distribution as horizontal bar chart to create a chart showing share of the vote in Shropshire elections 2017.

  • However, because I did not know how to manipulate the data I had to manually enter my data in the program which is clearly down to my own ignorance.

  • I have the relevant data in a CSV file and can therefore load it as a dataframe.

    • The CSV has a row for each ward, of which there are 63 and columns for the % vote for each party (Tory, LD, Labour, Green, Indep) so 5 substantive columns.
  • I wanted advice as to how to change the form of the data so it resembles the input for this chart.

  • I am not sure what it is but seems possibly a dictionary type with key and value:

My data reads in part:

import pandas as pd
import matplotlib.pyplot as plt

category_names = ['Labour', 'LD', 'Indep', 'Green', 'Tory']
results = {'Abbey': [16, 56, 4,0, 24],
           'Albrighton': [0, 0, 32, 0, 68],
           'Alveley & Claverley': [0, 25, 0, 0, 75],
           'Bagley': [30, 30, 0, 0, 40],
           'Battlefield': [34, 0, 0, 9, 57],
           'Bayston Hill, Column & Sutton': [53, 4, 3, 7, 33],
           'Belle Vue': [43,28,0,5,24]}


# setup dataframe using the dict provided in the OP
df = pd.DataFrame(results, index=category_names)

# display(df)
        Abbey  Albrighton  Alveley & Claverley  Bagley  Battlefield  Bayston Hill, Column & Sutton  Belle Vue
Labour     16           0                    0      30           34                             53         43
LD         56           0                   25      30            0                              4         28
Indep       4          32                    0       0            0                              3          0
Green       0           0                    0       0            9                              7          5
Tory       24          68                   75      40           57                             33         24

  • I am trying to get the data to be formatted like this directly from the csv file when entered as a pandas dataframe.

  • Have tried the values method and the to_dict method and while they get data looking similar they are not quite correct.

    • I believe there is a need to divide the data into keys and values but that is where my knowledge hits its limits.

Solution

  • Option 1: 'Party' as the y-axis

    Using matplotlib from version 3.4.2

    • Use matplotlib.pyplot.bar_label
      • See this answer for additional details and examples with .bar_label.
    • See the matplotlib: Bar Label Demo page for additional formatting options.
    • Tested in pandas 1.3.2, python 3.81., and matplotlib 3.4.21.
      • 1. Minimum version required
      • labels = [f'{v.get_width():.0f}' if v.get_width() > 0 else '' for v in c ] without using the assignment expression (:=)
    • Use .get_height() for vertical bars.
    ax = df.plot.barh(stacked=True, cmap='tab10', figsize=(16, 10))
    
    for c in ax.containers:
    
        # format the number of decimal places and replace 0 with an empty string
        labels = [f'{w:.0f}' if (w := v.get_width()) > 0 else '' for v in c ]
        
        ax.bar_label(c, labels=labels, label_type='center')
    

    Using matplotlib before version 3.4.2

    • Extract the .patch components in a loop, and then only plot annotations for values greater than 0.
    # plot 
    ax = df.plot.barh(stacked=True, cmap='tab10', figsize=(16, 10))
    
    # annotations:
    for p in ax.patches:
        left, bottom, width, height = p.get_bbox().bounds
        if width > 0:
             ax.annotate(f'{width:0.0f}', xy=(left+width/2, bottom+height/2), ha='center', va='center')
    

    enter image description here

    Option 2: 'Ward' as the y-axis

    • Use pandas.DataFrame.T to swap the Index and Columns
      • 'Ward' will now be the index and 'Party' will be the columns
    # transpose df from the OP so Party is the in the columns and Ward is the index
    dft = df.T
    
    # display(dft)
                                   Labour  LD  Indep  Green  Tory
    Abbey                              16  56      4      0    24
    Albrighton                          0   0     32      0    68
    Alveley & Claverley                 0  25      0      0    75
    Bagley                             30  30      0      0    40
    Battlefield                        34   0      0      9    57
    Bayston Hill, Column & Sutton      53   4      3      7    33
    Belle Vue                          43  28      0      5    24
    

    Using matplotlib from version 3.4.2

    # plot
    ax = df.T.plot.barh(stacked=True, figsize=(16, 10))
    
    plt.legend(loc='center left', bbox_to_anchor=(1.0, 0.5))
    
    # annotations:
    for c in ax.containers:
        
        # format the number of decimal places and replace 0 with an empty string
        labels = [f'{w:.0f}' if (w := v.get_width()) > 0 else '' for v in c ]
        
        ax.bar_label(c, labels=labels, label_type='center')
    

    Using matplotlib before version 3.4.2

    # plot
    ax = dft.plot.barh(stacked=True, figsize=(16, 10))
    
    plt.legend(loc='center left', bbox_to_anchor=(1.0, 0.5))
    
    # annotations:
    for p in ax.patches:
        left, bottom, width, height = p.get_bbox().bounds
        if width > 0:
             ax.annotate(f'{width:0.0f}', xy=(left+width/2, bottom+height/2), ha='center', va='center')
    

    enter image description here