Matplotlib & Python Basics Cheat Sheet

1. Installation

pip install matplotlib  

or for Jupyter Notebooks:

pip install notebook matplotlib  

2. Import Matplotlib

import matplotlib.pyplot as plt  

For inline plots in Jupyter Notebooks:

%matplotlib inline  

3. Basic Plot

import matplotlib.pyplot as plt

x = [1, 2, 3, 4, 5]  
y = [10, 15, 25, 30, 40]  

plt.plot(x, y)  
plt.title('Basic Line Plot')  
plt.xlabel('X Axis')  
plt.ylabel('Y Axis')  
plt.show()  

4. Plot Types

Line Plot:

plt.plot(x, y)  

Bar Chart:

plt.bar(x, y)  

Histogram:

plt.hist(y, bins=5)  

Scatter Plot:

plt.scatter(x, y)  

Pie Chart:

plt.pie(y, labels=x)  

5. Customizing Plots

• Change Line Style & Color:

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

• Add Grid:

  plt.grid(True)  
  

• Add Legend:

  plt.legend(['Data'])  
  

• Adjust Axis Limits:

  plt.xlim(0, 10)  
  plt.ylim(0, 50)  
  

• Figure Size:

  plt.figure(figsize=(8, 5))  
  

6. Subplots

plt.figure(figsize=(10, 5))  

plt.subplot(1, 2, 1)  
plt.plot(x, y)  
plt.title('Plot 1')  

plt.subplot(1, 2, 2)  
plt.bar(x, y)  
plt.title('Plot 2')  

plt.tight_layout()  
plt.show()  

7. Adding Text and Annotations

plt.plot(x, y)  
plt.text(3, 25, 'Peak Value')  
plt.annotate('Max Point', xy=(5, 40), xytext=(3, 30),  
             arrowprops=dict(facecolor='blue', shrink=0.05))  

8. Saving Plots

plt.savefig('plot.png')  

• File Formats: PNG, PDF, SVG, JPG

9. Working with Multiple Lines

plt.plot(x, y, label='Line 1')  
plt.plot(x, [15, 20, 35, 40, 50], label='Line 2')  
plt.legend()  

10. Common Customizations

• Line Width:

  plt.plot(x, y, linewidth=2)  
  

• Alpha (Transparency):

  plt.bar(x, y, alpha=0.7)  
  

• Color Maps (Heatmaps/Scatter):

  plt.scatter(x, y, c=y, cmap='viridis')  
  plt.colorbar()  
  

11. Histogram Example

data = [5, 15, 25, 35, 45, 55, 65, 75]  
plt.hist(data, bins=5, edgecolor='black')  
plt.title('Histogram Example')  
plt.show()  

12. Pie Chart Example

sizes = [30, 20, 40, 10]  
labels = ['A', 'B', 'C', 'D']  

plt.pie(sizes, labels=labels, autopct='%1.1f%%', startangle=140)  
plt.title('Pie Chart Example')  
plt.show()  

13. Advanced Plot – Multiple Axes

fig, ax1 = plt.subplots()  

ax2 = ax1.twinx()  
ax1.plot(x, y, 'g-')  
ax2.plot(x, [10, 20, 30, 40, 50], 'b--')  

ax1.set_xlabel('X Data')  
ax1.set_ylabel('Primary Axis', color='g')  
ax2.set_ylabel('Secondary Axis', color='b')  

plt.show()  

14. Scatter Plot with Regression Line

import numpy as np

x = np.linspace(0, 10, 50)  
y = 3 * x + np.random.randn(50)  

plt.scatter(x, y)  
plt.plot(x, 3 * x, color='red')  
plt.title('Scatter Plot with Regression Line')  
plt.show()  

15. Common Matplotlib Commands

Example: Complete Dashboard

plt.figure(figsize=(12, 6))  

plt.subplot(2, 2, 1)  
plt.plot(x, y)  
plt.title('Line Plot')  

plt.subplot(2, 2, 2)  
plt.bar(x, y)  
plt.title('Bar Chart')  

plt.subplot(2, 2, 3)  
plt.scatter(x, y)  
plt.title('Scatter Plot')  

plt.subplot(2, 2, 4)  
plt.hist(y, bins=5)  
plt.title('Histogram')  

plt.tight_layout()  
plt.show()