learn-python/contrib/plotting-visualization/matplotlib-sub-plot.md

1. Using plt.subplots()

The plt.subplots() function is a versatile and easy way to create a grid of subplots. It returns a figure and an array of Axes objects.

Code Explanation

1. Import Libraries:

   import matplotlib.pyplot as plt
   import numpy as np
   

2. Generate Sample Data:

   x = np.linspace(0, 10, 100)
   y1 = np.sin(x)
   y2 = np.cos(x)
   y3 = np.tan(x)
   

3. Create Subplots:

   fig, axs = plt.subplots(3, 1, figsize=(8, 12))
   

   • 3, 1 indicates a 3-row, 1-column grid.
   • figsize specifies the overall size of the figure.

4. Plot Data:

   axs[0].plot(x, y1, 'r')
   axs[0].set_title('Sine Function')
   
   axs[1].plot(x, y2, 'g')
   axs[1].set_title('Cosine Function')
   
   axs[2].plot(x, y3, 'b')
   axs[2].set_title('Tangent Function')
   

5. Adjust Layout and Show Plot:

   plt.tight_layout()
   plt.show()
   

Result

The result will be a figure with three vertically stacked subplots.

2. Using plt.subplot()

The plt.subplot() function allows you to add a single subplot at a time to a figure.

Code Explanation

1. Import Libraries and Generate Data (same as above).

2. Create Figure and Subplots:

   plt.figure(figsize=(8, 12))
   
   plt.subplot(3, 1, 1)
   plt.plot(x, y1, 'r')
   plt.title('Sine Function')
   
   plt.subplot(3, 1, 2)
   plt.plot(x, y2, 'g')
   plt.title('Cosine Function')
   
   plt.subplot(3, 1, 3)
   plt.plot(x, y3, 'b')
   plt.title('Tangent Function')
   

3. Adjust Layout and Show Plot (same as above).

Result

The result will be similar to the first method but created using individual subplot commands.

3. Using GridSpec

GridSpec allows for more complex subplot layouts.

Code Explanation

1. Import Libraries and Generate Data (same as above).

2. Create Figure and GridSpec:

   from matplotlib.gridspec import GridSpec
   
   fig = plt.figure(figsize=(8, 12))
   gs = GridSpec(3, 1, figure=fig)
   

3. Create Subplots:

   ax1 = fig.add_subplot(gs[0, 0])
   ax1.plot(x, y1, 'r')
   ax1.set_title('Sine Function')
   
   ax2 = fig.add_subplot(gs[1, 0])
   ax2.plot(x, y2, 'g')
   ax2.set_title('Cosine Function')
   
   ax3 = fig.add_subplot(gs[2, 0])
   ax3.plot(x, y3, 'b')
   ax3.set_title('Tangent Function')
   

4. Adjust Layout and Show Plot (same as above).

Result

The result will again be three subplots in a vertical stack, created using the flexible GridSpec.

Summary

• plt.subplots(): Creates a grid of subplots with shared axes.
• plt.subplot(): Adds individual subplots in a figure.
• GridSpec: Allows for complex and custom subplot layouts.

By mastering these techniques, you can create detailed and organized visualizations, enhancing the clarity and comprehension of your data presentations.