Subplots with Different Visualizations

import matplotlib.pyplot as plt
from sklearn.datasets import load_iris
import numpy as np

def iris_subplots():
    iris = load_iris()
    fig, ax = plt.subplots(2, 2, figsize=(10, 8))
    
    # Top-left: Histogram of sepal length
    ax[0, 0].hist(iris.data[:, 0], color='blue', bins=20)
    ax[0, 0].set_title("Histogram of Sepal Length")
    
    # Top-right: Scatter plot of sepal width against petal width
    ax[0, 1].scatter(iris.data[:, 1], iris.data[:, 3], color='green')
    ax[0, 1].set_title("Scatter plot: Sepal Width vs. Petal Width")
    
    # Bottom-left: Box plot of petal lengths by species
    data_to_plot = [iris.data[iris.target == i][:, 2] for i in range(3)]
    ax[1, 0].boxplot(data_to_plot)
    ax[1, 0].set_xticks([1, 2, 3])
    ax[1, 0].set_xticklabels(iris.target_names)
    ax[1, 0].set_title("Boxplot of Petal Lengths by Species")
    
    # Bottom-right: Pie chart of species distribution
    species_counts = np.bincount(iris.target)
    ax[1, 1].pie(species_counts, labels=iris.target_names, autopct='%1.1f%%')
    ax[1, 1].set_title("Species Distribution in Iris Dataset")
    
    plt.tight_layout()
    plt.show()

# Example usage
iris_subplots()