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Matplotlib is a powerful plotting library in Python that allows you to create static, animated, and interactive visualizations. It’s widely used for representing data graphically, making it easier to analyze and understand.

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Matplotlib

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Welcome to the Matplotlib repository! This repo is dedicated to providing helpful resources, tutorials, and examples for using the Matplotlib library in Python.

Table of Contents

Roadmap

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Introduction

Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. It provides an object-oriented API for embedding plots into applications.

This repository aims to help users of all skill levels to better understand and utilize the Matplotlib library through comprehensive guides, code snippets, and example projects.

Installation

To install Matplotlib, you can use pip, the Python package installer. Ensure you have Python installed, then run:

pip install matplotlib

For more detailed installation instructions, please refer to the official Matplotlib installation guide.

Usage

Here are some basic examples to get you started with Matplotlib:

Basic Plot

import matplotlib.pyplot as plt

x = [1, 2, 3, 4, 5]
y = [10, 20, 25, 30, 35]

plt.plot(x, y)
plt.title('Basic Plot')
plt.xlabel('X-axis')
plt.ylabel('Y-axis')
plt.show()

Subplots

import matplotlib.pyplot as plt

x = [1, 2, 3, 4, 5]
y1 = [10, 20, 25, 30, 35]
y2 = [15, 25, 20, 30, 40]

fig, axs = plt.subplots(2)

axs[0].plot(x, y1, 'r')
axs[0].set_title('First Subplot')
axs[1].plot(x, y2, 'b')
axs[1].set_title('Second Subplot')

plt.tight_layout()
plt.show()

Customizing Plots

import matplotlib.pyplot as plt

x = [1, 2, 3, 4, 5]
y = [10, 20, 25, 30, 35]

plt.plot(x, y, marker='o', linestyle='--', color='g', label='Line with Markers')
plt.title('Customized Plot')
plt.xlabel('X-axis')
plt.ylabel('Y-axis')
plt.legend()
plt.grid(True)
plt.show()

3D Plotting

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import numpy as np

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')

x = np.linspace(-5, 5, 100)
y = np.linspace(-5, 5, 100)
X, Y = np.meshgrid(x, y)
Z = np.sin(np.sqrt(X**2 + Y**2))

ax.plot_surface(X, Y, Z, cmap='viridis')

plt.title('3D Surface Plot')
plt.show()

For more examples and detailed tutorials, please refer to the official Matplotlib documentation.

Features

  • Comprehensive library for creating static, animated, and interactive visualizations
  • Object-oriented API for embedding plots
  • Support for a wide range of plots and visualizations
  • Customization capabilities for plots

⚖ ➤ License

This project is licensed under the MIT License. See LICENSE for details.

❤️ Support

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➤ If you have questions or feedback, feel free to reach out!!!


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Matplotlib is a powerful plotting library in Python that allows you to create static, animated, and interactive visualizations. It’s widely used for representing data graphically, making it easier to analyze and understand.

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