Easy Matplotlib Cheat Sheet

Welcome to the Matplotlib Cheat Sheet! This guide includes examples of basic and advanced plotting techniques to help you create stunning visualizations.

1. Import Matplotlib

import matplotlib.pyplot as plt

2. Create a Basic Plot

x = [1, 2, 3, 4]
y = [10, 20, 25, 30]
plt.plot(x, y)
plt.title('Basic Plot')
plt.xlabel('X-axis')
plt.ylabel('Y-axis')
plt.show()

3. Customize Line Style and Markers

plt.plot(x, y, linestyle='--', marker='o', color='r')
plt.show()

4. Create a Figure and Subplots

fig, ax = plt.subplots(2, 2)  # 2x2 grid of subplots
ax[0, 0].plot(x, y)
ax[0, 0].set_title('Top Left')
plt.tight_layout()
plt.show()

5. Adjust Axes Properties

fig, ax = plt.subplots()
ax.plot(x, y)
ax.set_xlim(0, 5)
ax.set_ylim(0, 35)
ax.set_xticks([1, 2, 3, 4])
ax.set_yticks([10, 20, 30])
ax.set_xticklabels(['A', 'B', 'C', 'D'])
plt.show()

6. Add a Colorbar

import numpy as np
data = np.random.rand(10, 10)
plt.imshow(data, cmap='viridis')
plt.colorbar(label='Intensity')
plt.show()

7. Fancy Colorbar with Ticks

data = np.random.rand(10, 10)
cax = plt.imshow(data, cmap='coolwarm')
cbar = plt.colorbar(cax, ticks=[0, 0.5, 1])
cbar.ax.set_yticklabels(['Low', 'Medium', 'High'])
plt.show()

8. Box Plot

data = [7, 8, 5, 6, 9, 10, 15]
plt.boxplot(data)
plt.title('Box Plot')
plt.show()

9. Bar Plot

categories = ['A', 'B', 'C']
values = [10, 20, 15]
plt.bar(categories, values, color='skyblue')
plt.title('Bar Plot')
plt.show()

10. Horizontal Bar Plot

plt.barh(categories, values, color='lightgreen')
plt.title('Horizontal Bar Plot')
plt.show()

11. Line Plot with Multiple Lines

y2 = [15, 25, 20, 35]
plt.plot(x, y, label='Line 1')
plt.plot(x, y2, label='Line 2', linestyle='--')
plt.legend()
plt.show()

12. Scatter Plot

plt.scatter(x, y, color='red', label='Data Points')
plt.legend()
plt.show()

13. Shaded Region

plt.plot(x, y)
plt.fill_between(x, y, color='yellow', alpha=0.3)
plt.show()

14. Histogram

data = np.random.randn(1000)
plt.hist(data, bins=30, color='purple', alpha=0.7)
plt.title('Histogram')
plt.show()

15. Pie Chart

sizes = [15, 30, 45, 10]
labels = ['A', 'B', 'C', 'D']
plt.pie(sizes, labels=labels, autopct='%1.1f%%')
plt.title('Pie Chart')
plt.show()

16. Adding Grid

plt.plot(x, y)
plt.grid(color='gray', linestyle='--', linewidth=0.5)
plt.show()

17. Logarithmic Scale

plt.plot(x, y)
plt.yscale('log')
plt.title('Logarithmic Scale')
plt.show()

18. Annotate Points

plt.plot(x, y)
plt.annotate('Peak', xy=(3, 25), xytext=(2, 30),
             arrowprops=dict(facecolor='black', arrowstyle='->'))
plt.show()

19. Save Figure

plt.plot(x, y)
plt.savefig('plot.png', dpi=300, bbox_inches='tight')

20. Display Multiple Figures

plt.figure(1)
plt.plot(x, y)
plt.figure(2)
plt.plot(y, x)
plt.show()