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  1. Matplotlib is a powerful Python library for creating static, animated, and interactive visualizations. It supports a wide range of plots such as line charts, bar charts, scatter plots, histograms, pie charts, and more. It integrates seamlessly with NumPy and Pandas, making it a go-to tool for data analysis and scientific research.

    It offers two main interfaces:

    • Pyplot API (matplotlib.pyplot): A MATLAB-like interface for quick plotting.

    • Object-Oriented API: Provides more control and customization over figures and axes.

    Basic Example – Line Plot

    import matplotlib.pyplot as plt
    import numpy as np

    # Data
    x = np.linspace(0, 2 * np.pi, 200)
    y = np.sin(x)

    # Create plot
    fig, ax = plt.subplots(figsize=(7, 4))
    ax.set_title('Sine Wave')
    ax.plot(x, y, label='sin(x)', color='blue')

    # Add labels and legend
    ax.set_xlabel('X-axis')
    ax.set_ylabel('Y-axis')
    ax.legend()

    # Display
    plt.show()
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  3. Matplotlib Tutorial - GeeksforGeeks

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  8. Python Matplotlib Tutorials - Comprehensive Guide for Data Visualization

    Explore Python Matplotlib with tutorials on line graphs, scatter plots, bar charts, and pie charts. Perfect for data visualization in analysis and machine learning.

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