Four Types of Bar Charts in Python - Based on Array Data

Luca Liu - Mar 14 - - Dev Community

Simple bar chart based on an array in Python

import matplotlib.pyplot as plt
import numpy as np

x = np.array(['A', 'B', 'C', 'D', 'E'])
y = np.array([50, 30, 70, 80, 60])

plt.bar(x, y, align='center', width=0.5, color='b', label='data')
plt.xlabel('X axis')
plt.ylabel('Y axis')
plt.title('Bar chart')
plt.legend()
plt.show()
Enter fullscreen mode Exit fullscreen mode

Image description

Stacked bar chart based on arrays in Python

import matplotlib.pyplot as plt
import numpy as np
x = np.array(['A', 'B', 'C', 'D', 'E'])
y1 = np.array([50, 30, 70, 80, 60])
y2 = np.array([20, 40, 10, 50, 30])

plt.bar(x, y1, align='center', width=0.5, color='b', label='Series 1')
plt.bar(x, y2, bottom=y1, align='center', width=0.5, color='g', label='Series 2')
plt.xlabel('X axis')
plt.ylabel('Y axis')
plt.title('Stacked Bar Chart')
plt.legend()
plt.show()
Enter fullscreen mode Exit fullscreen mode

Image description

Grouped bar chart based on arrays in Python

import matplotlib.pyplot as plt
import numpy as np

# Prepare the data
N = 5
men_means = (20, 35, 30, 35, 27)
women_means = (25, 32, 34, 20, 25)
ind = np.arange(N)  # x-axis position
width = 0.35  # width of each bar

# Plot the bar chart
fig, ax = plt.subplots()
rects1 = ax.bar(ind, men_means, width, color='r')
rects2 = ax.bar(ind + width, women_means, width, color='y')

# Add labels, legend, and axis labels
ax.set_xticks(ind + width / 2)
ax.set_xticklabels(('G1', 'G2', 'G3', 'G4', 'G5'))
ax.legend((rects1[0], rects2[0]), ('Men', 'Women'))
ax.set_xlabel('Groups')
ax.set_ylabel('Scores')

# Display the plot
plt.show()

Enter fullscreen mode Exit fullscreen mode

Image description

Percent stacked bar chart based on arrays in Python

import matplotlib.pyplot as plt
import numpy as np

# Prepare the data
x = ['Group 1', 'Group 2', 'Group 3', 'Group 4', 'Group 5']
y = np.array([[10, 20, 30],
              [20, 25, 30],
              [15, 30, 25],
              [25, 15, 20],
              [30, 20, 10]])

# calculate percentage
y_percent = y / np.sum(y, axis=1, keepdims=True) * 100

# Plot the chart
fig, ax = plt.subplots()
ax.bar(x, y_percent[:, 0], label='Series 1', color='r')
ax.bar(x, y_percent[:, 1], bottom=y_percent[:, 0], label='Series 2', color='g')
ax.bar(x, y_percent[:, 2], bottom=y_percent[:, 0] + y_percent[:, 1], label='Series 3', color='b')

# Display the plot
plt.show()
Enter fullscreen mode Exit fullscreen mode

Image description


Explore more

Thank you for taking the time to explore data-related insights with me. I appreciate your engagement.

πŸš€ Connect with me on LinkedIn

πŸŽƒ Connect with me on X

🌍 Connect with me on Instagram

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Terabox Video Player