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Summary Matplotlib Comprehensive Notes, Cheat Sheets, and Study Guide
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  • Course
  • CS8501
  • Institution
  • Anna University,CEG,chennai-600025

Master data visualization in Python with this comprehensive set of Matplotlib notes. Covering key topics such as plotting line charts, bar graphs, histograms, and scatter plots, these notes are designed for both beginners and advanced users. With cheat sheets, quick references, and code examples, t...

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Document information

  • September 30, 2024
  • 3
  • 2024/2025
  • Summary

Subjects

  • matplotlib notes
  • matplotlib cheat sheet
  • matplotlib quick guide
  • matplotlib basics
  • matplotlib revision notes
  • matplotlib essentials
  • matplotlib for beginners
  • matplotlib code sni
  • matplotlib developer notes

Written for

  • Anna University,CEG,chennai-600025
  • CS8501
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Matplotlib Overview
1. Introduction to Matplotlib

What is Matplotlib: Matplotlib is a comprehensive library in Python for creating static, animated, and

interactive visualizations.

History of Matplotlib: Matplotlib was created by John D. Hunter in 2003 and has become one of the

most widely used plotting libraries in Python.

Key Features: Matplotlib provides tools for creating line plots, bar charts, scatter plots, histograms,

pie charts, and more with high customization.

2. Basic Plotting with Matplotlib

Creating a Plot: A basic plot in Matplotlib can be created using the plot() function, with x and y data

points passed as arguments.

Labels and Titles: The xlabel(), ylabel(), and title() functions are used to add axis labels and titles to

the plot.

Showing and Saving Plots: Plots can be displayed using the show() function or saved to a file with

savefig().

3. Customizing Plots

Line Styles and Colors: Matplotlib allows customizing the appearance of plots with different line

styles (e.g., dashed, dotted) and colors.

Markers: Data points can be marked with different marker styles like circles, squares, and triangles

for better visualization.

Legends: The legend() function is used to add a legend to the plot, helping identify different lines or

markers in the plot.

4. Subplots in Matplotlib

Creating Subplots: Matplotlib's subplot() function allows for creating multiple plots (subplots) within a

single figure.

Grid of Subplots: The subplots() function creates a grid of subplots, where each subplot can have its

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