How to plot and annotate a grouped bar chart

bar-chart, matplotlib, pandas, python

Solution

Imports and DataFrame

import pandas as pd
import matplotlib.pyplot as plt

# given the following code to create the dataframe
file = "https://s3-api.us-geo.objectstorage.softlayer.net/cf-courses-data/CognitiveClass/DV0101EN/labs/coursera/Topic_Survey_Assignment.csv"
df = pd.read_csv(file, index_col=0)

df.sort_values(by=['Very interested'], axis=0, ascending=False, inplace=True)

# all columns are being divided by 2233 so those lines can be replace with the following single line
df = df.div(2233)

# display(df)
                            Very interested  Somewhat interested  Not interested
Data Analysis / Statistics         0.755934             0.198836        0.026870
Machine Learning                   0.729512             0.213614        0.033139
Data Visualization                 0.600090             0.328706        0.045678
Big Data (Spark / Hadoop)          0.596507             0.326467        0.056874
Deep Learning                      0.565607             0.344828        0.060905
Data Journalism                    0.192118             0.484102        0.273175

Using since `matplotlib v3.4.2`

- Uses `matplotlib.pyplot.bar_label` and `pandas.DataFrame.plot`

- Some formatting can be done with the `fmt` parameter, but more sophisticated formatting should be done with the `labels` parameter, as show in How to add multiple annotations to a barplot.

- See How to add value labels on a bar chart for additional details and examples using `.bar_label`

- This answer shows how to use the `fmt=` or `label=` parameter filter out low values from the annotations.

# your colors
colors = ['#5cb85c', '#5bc0de', '#d9534f']

# plot with annotations is probably easier
ax = df.plot(kind='bar', color=colors, figsize=(20, 8), rot=0, ylabel='Percentage', title="The percentage of the respondents' interest in the different data science Area")

for c in ax.containers:
    ax.bar_label(c, fmt='%.2f', label_type='edge')

Using before `matplotlib v3.4.2`

- `w = 0.8 / 3` will resolve the issue, given the current code.

- However, generating the plot can be accomplished more easily with `pandas.DataFrame.plot`

# your colors
colors = ['#5cb85c', '#5bc0de', '#d9534f']

# plot with annotations is probably easier
ax = df.plot.bar(color=colors, figsize=(20, 8), ylabel='Percentage', title="The percentage of the respondents' interest in the different data science Area")
ax.set_xticklabels(ax.get_xticklabels(), rotation=0)

for p in ax.patches:
    ax.annotate(f'{p.get_height():0.2f}', (p.get_x() + p.get_width() / 2., p.get_height()), ha = 'center', va = 'center', xytext = (0, 10), textcoords = 'offset points')

If `file` is no longer available, replace `df = pd.read_csv(file, index_col=0)` with:

data = {'Very interested': [1332, 1688, 429, 1340, 1263, 1629], 'Somewhat interested': [729, 444, 1081, 734, 770, 477], 'Not interested': [127, 60, 610, 102, 136, 74]}
df = pd.DataFrame(data, index=['Big Data (Spark / Hadoop)', 'Data Analysis / Statistics', 'Data Journalism', 'Data Visualization', 'Deep Learning', 'Machine Learning'])

Problem

Original source

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