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# Matplotlib Cheatsheet

Matplotlib is a popular plotting library for Python. It provides a wide range of tools for creating static, animated, and interactive visualizations in Python. This cheatsheet provides a quick reference for some of Matplotlib's unique features, including code blocks for basic plots, subplots, customization, and more. Additionally, it includes a list of resources for further learning.

## Basic Plots

import matplotlib.pyplot as plt

import numpy as np

Create a simple line plot

x = np.linspace(0, 10, 100)

y = np.sin(x)

plt.plot(x, y)

plt.show()

Create a scatter plot

x = np.random.rand(100)

y = np.random.rand(100)

plt.scatter(x, y)

plt.show()

Create a histogram

x = np.random.normal(size=1000)

plt.hist(x, bins=30)

plt.show()


## Subplots

Create a figure with multiple subplots

fig, axs = plt.subplots(2, 2, figsize=(6, 6))

axs[0, 0].plot(x, y)

axs[0, 1].scatter(x, y)

axs[1, 0].hist(x, bins=30)

axs[1, 1].imshow(np.random.rand(100, 100))

plt.show()


## Customization

Add a title and axis labels

plt.plot(x, y)

plt.title('Sine Wave')

plt.xlabel('X')

plt.ylabel('Y')

plt.show()

Customize the style

plt.style.use('ggplot')

plt.plot(x, y)

plt.show()

Add a legend

plt.plot(x, np.sin(x), label='sin(x)')

plt.plot(x, np.cos(x), label='cos(x)')

plt.legend()

plt.show()


## Other Useful Features

Save a figure to a file

plt.plot(x, y)

plt.savefig('figure.png')

Clear the current figure

plt.clf()

Close all figures

plt.close('all')


## Resources

- [Matplotlib documentation](https://matplotlib.org/stable/contents.html)
- [Matplotlib tutorials](https://matplotlib.org/stable/tutorials/index.html)
- [Python Data Science Handbook](https://jakevdp.github.io/PythonDataScienceHandbook/index.html)