Merge pull request animator#1325 from Salma-Mamdoh/main

Subplots in Matplotlib

Author: ashitaprasad

contrib/plotting-visualization/images/Subplots.png

@@ -7,6 +7,7 @@
 - [Line Charts in Matplotlib](matplotlib-line-plots.md)
 - [Scatter Plots in Matplotlib](matplotlib-scatter-plot.md)
 - [Violin Plots in Matplotlib](matplotlib-violin-plots.md)
+- [subplots in Matplotlib](matplotlib-sub-plot.md)
 - [Introduction to Seaborn and Installation](seaborn-intro.md)
 - [Seaborn Plotting Functions](seaborn-plotting.md)
 - [Getting started with Seaborn](seaborn-basics.md)

contrib/plotting-visualization/index.md

@@ -0,0 +1,130 @@
+### 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**:
+ ```python
+ import matplotlib.pyplot as plt
+ import numpy as np
+ ```
+
+2. **Generate Sample Data**:
+ ```python
+ x = np.linspace(0, 10, 100)
+ y1 = np.sin(x)
+ y2 = np.cos(x)
+ y3 = np.tan(x)
+ ```
+
+3. **Create Subplots**:
+ ```python
+ 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**:
+ ```python
+ 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**:
+ ```python
+ plt.tight_layout()
+ plt.show()
+ ```
+
+#### Result
+
+The result will be a figure with three vertically stacked subplots.
+![subplot Chart](images/subplots.png)
+
+### 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**:
+ ```python
+ 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.
+
+![subplot Chart](images/subplots.png)
+
+### 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**:
+ ```python
+ from matplotlib.gridspec import GridSpec
+ 
+ fig = plt.figure(figsize=(8, 12))
+ gs = GridSpec(3, 1, figure=fig)
+ ```
+
+3. **Create Subplots**:
+ ```python
+ 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`. 
+
+![subplot Chart](images/subplots.png)
+
+### 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.