How to plot and annotate grouped bars-CodePudding

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.

CodePudding user response：

There is align option you can use:

# number of data points
num_data = len(labels)

bars1 = plt.bar(range(num_data), oct_data, color='#7f6d5f', 
                align='edge', width=-bar_width,    # align and negative width for left bars
                edgecolor='white', label='Month_1')
bars1 = plt.bar(range(num_data), nov_data, color='#557f2d', 
                align='edge', width=bar_width,     # align and positive width for right bars
                edgecolor='white', label='Month_2')

# set xticks
plt.xticks(range(num_data), labels)

For annotation, it's recommend to have an axis instance:

fig, ax = plt.subplots()
# other plot commands

for patch in ax.patches:
    ax.text(patch.get_x()   patch.get_width()/2,
            patch.get_height()/2,
            f'{patch.get_height()}',
            verticalalignment='center', horizontalalignment='center')

Output:

Update: All code:

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

fig, ax = plt.subplots()

# number of data points
num_data = len(labels)

bars1 = plt.bar(range(num_data), oct_data, color='#7f6d5f', 
                align='edge', width=-bar_width,    # align and negative width for left bars
                edgecolor='white', label='Month_1')
bars1 = plt.bar(range(num_data), nov_data, color='#557f2d', 
                align='edge', width=bar_width,     # align and positive width for right bars
                edgecolor='white', label='Month_2')

for patch in ax.patches:
    ax.text(patch.get_x()   patch.get_width()/2,
            patch.get_height()/2,
            f'{patch.get_height()}',
            verticalalignment='center', horizontalalignment='center')

# set xticks
plt.xticks(range(num_data), labels)
plt.ylabel('Cost ($)', fontsize=10)

plt.legend()
plt.show()

CodePudding user response：

The easiest solution is to use pandas. The 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