Subplots components Matplotlib

 Subplots components Matplotlib

• In Matplotlib, subplots are used to create multiple plots within the same figure.
• The `plt.subplots()` function is commonly used to create a grid of subplots, and it returns a figure and an array of subplot axes.
• key components and methods related to creating subplots in Matplotlib:

1. Creating Subplots:

   - `plt.subplots(nrows, ncols, ...)`: Creates a grid of subplots.

     fig, axes = plt.subplots(nrows=2, ncols=2, figsize=(10, 8))

   - `nrows` and `ncols`: The number of rows and columns in the subplot grid.

   - `figsize`: The size of the entire figure.

 

2. Accessing Subplots:

•    - Subplots are accessed using the `axes` array returned by `plt.subplots()`. 
•        You can access a specific subplot using array indexing.

      ax1 = axes[0, 0]  # Accessing the top-left subplot

 

3. Data Plotting in Subplots:

   - You can plot data on each subplot individually using the methods available on the subplot axes.

     ax1.plot(x1, y1)

     ax2.scatter(x2, y2)

 

4. Title and Labels for Subplots:

   - You can add a title to the entire figure and individual titles to each subplot.

     fig.suptitle('Main Title')

     ax1.set_title('Subplot 1 Title')

 

   - Axis labels are set similarly:

     ax1.set_xlabel('X-axis')

     ax1.set_ylabel('Y-axis')

    

5. Sharing Axes:

   - You can share the x or y axes between subplots.

       plt.subplots(nrows=2, ncols=2, sharex=True, sharey=True)

 

6. Adjusting Layout:

   - `plt.tight_layout()`: Automatically adjusts the subplot parameters to fit the figure area.

       plt.tight_layout()

 

7. Saving and Displaying the Plot:

   - Save (`plt.savefig()`): Saves the plot to a file.
   - Show (`plt.show()`): Displays the plot on the screen.

     plt.show()

 

example:- creating subplots in Matplotlib:

 import matplotlib.pyplot as plt

import numpy as np

 # Generate data

x = np.linspace(0, 2 * np.pi, 100)

y1 = np.sin(x)

y2 = np.cos(x)

y3 = np.tan(x)

 # Create subplots

fig, axes = plt.subplots(nrows=3, ncols=1, figsize=(8, 12))

 # Plot on each subplot

axes[0].plot(x, y1, label='sin(x)', color='blue')

axes[0].set_title('Sine Function')

axes[1].plot(x, y2, label='cos(x)', color='green')

axes[1].set_title('Cosine Function')

axes[2].plot(x, y3, label='tan(x)', color='red')

axes[2].set_title('Tangent Function')

# Add a common x-axis label

axes[-1].set_xlabel('x')

 # Adjust layout for better spacing

plt.tight_layout()

 # Show the plot

plt.show()

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