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Matplotlib is a Multiplatform visualization library for data that is built on NumPy Arrays. This Library is designed to work with the broader SciPy stack, which includes different modules of Python used for machine learning and data science.

Matplotlib is the default(sort of) Python Data Visualization Package and is being used extensively in the market for creating plots, charts, and graphs for datasets for better data analysis and visualization.

In this tutorial on Matplotlib, we will start with the basics of Matplotlib and will cover all the different types of Plots available in Matplotlib.

You can use Matplotlib for creating charts and graphs. You can visualize data using Matplolib library in Python.

Why Learn Matplotlib?

  • Matplotlib is a powerful library in Python that is used for data visualization.

  • It Allows you to create visually appealing and informative plots and charts.

  • Matplotlib is widely used in data analysis, scientific research, and industry to explore and communicate data effectively.

  • By learning Matplotlib, you can enhance your data analysis skills which will make your data-driven insights more impactful.

How to Learn Matplotlib?

  • Get familiar with the basics from our free Matplotlib tutorial: Start by understanding the fundamental concepts of Matplotlib, such as figures, axes, and plotting functions.

  • Learn with the help of Official documentation of Matplotlib.

  • Experiment and customize: Play with different parameters, styles, colors, and layouts to create unique visualizations on your own.

Use of Matplotlib:

  • Data Visualization: Matplotlib is widely used for visualizing data in various formats, such as line plots, scatter plots, bar charts, histograms, and more.

  • Exploratory Data Analysis: Matplotlib enables you to explore datasets, and identify patterns through interactive visualizations.