MATPLOTLIB

Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. It provides a wide range of plotting functions and customization options to create high-quality plots for data analysis and presentation.

Here’s an overview of plotting in Matplotlib:

1. Basic Plotting: Matplotlib’s `pyplot` module provides a simple interface for creating basic plots such as line plots, scatter plots, bar plots, histograms, and more.

2. Figure and Axes: Plots in Matplotlib are organized into a hierarchy of `Figure` and `Axes` objects. The `Figure` object represents the entire figure or window, while the `Axes` object represents a specific plot within the figure.

3. Plotting Functions: Matplotlib provides various functions for different types of plots. For example, `plot()` is used for line plots, `scatter()` for scatter plots, `bar()` for bar plots, `hist()` for histograms, and so on.

4. Customization: Matplotlib allows you to customize almost every aspect of your plot, including the plot style, colors, markers, labels, axes limits, grid lines, and more. You can use various parameters and functions to tailor your plot according to your preferences.

5. Multiple Plots: You can create multiple plots within the same figure using Matplotlib’s subplots feature. This allows you to compare different datasets or visualize multiple aspects of the same dataset side by side.

6. Saving Plots: Matplotlib allows you to save your plots in various formats such as PNG, PDF, SVG, and more. You can use the `savefig()` function to save your plot to a file.

7. Integration with Pandas: Matplotlib works seamlessly with Pandas, a popular data manipulation library in Python. You can directly plot Pandas DataFrame and Series objects using Matplotlib’s plotting functions.