How to plot and annotate grouped bars

Question

I have the following code

import numpy as np
import matplotlib.pyplot as plt

oct_data = [10, 24, 25, 30]
nov_data = [12, 42, 21, 78]

labels = ['Account_1', 'Account_2', 'Account_3', 'Account_4']
bar_width = 0.4

rect_1 = np.arange(0, len(oct_data)*2 ,2) 
rect_2 = [x + bar_width for x in rect_1]

plt.bar(rect_1, oct_data, color='#7f6d5f', width=bar_width, edgecolor='white', label='Month_1')
plt.bar(rect_2, nov_data, color='#557f2d', width=bar_width, edgecolor='white', label='Month_2')

plt.ylabel('Cost ($)', fontsize=10)

plt.legend()
plt.show()

Which gives me the following figure:

As you can see, my xticks (Account_1, Account_2, ...) are not centered. As I understand, this command should do the job, but it doesn't.

plt.xticks([r + bar_width for r in range(0, len(oct_data)*2, 2)], labels)

I also would like to add the value of the heigh inside the bar. Usually, this is how I do it with a "single bar" graph:

  for i in range(len(labels)):
    plt.text(i, oct_data[i]//2, oct_data[i], ha = 'center', color = 'black')

But that does not work here.

Any help would be greatly appreciated. I am a total beginner with Matplotlib.

Answer 1

• The easiest solution is to use pandas. This puts the data in an object which easily facilitates further analysis, and the plot API properly manages the spacing of grouped bars.
  • This implementation uses only 6 lines of code, compared to 18 lines.
• Use pandas.DataFrame.plot, which uses matplotlib as the default plotting backend. Columns are plotted as the bar groups and the index is the independent axis.
• From matplotlib 3.4.2, .bar_label should be used for annotations on bars.
• See How to add value labels on a bar chart for addition information and examples about using .bar_label, and How to plot and annotate a grouped bar chart for an additional example of grouped bars.
• Tested in python 3.9.7, pandas 1.3.4, matplotlib 3.4.3

import pandas as pd
import matplotlib.pyplot as plt

# create a dict with the data
data = {'October': oct_data, 'November': nov_data}

# create the dataframe with the labels as the index
df = pd.DataFrame(data, index=labels)

# display(df)
           October  November
Account_1       10        12
Account_2       24        42
Account_3       25        21
Account_4       30        78

# plot the dataframe
ax = df.plot(kind='bar', figsize=(10, 6), rot=0, ylabel='Cost ($)', color=['#7f6d5f', '#557f2d'])

# iterate through each group of container (bar) objects
for c in ax.containers:

    # annotate the container group
    ax.bar_label(c, label_type='center')

plt.show()