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Matplotlib Tutorial
Matplotlib Tutorial Offer Expired

Matplotlib Tutorial

Plotting using Python's visualization tool.

Pie charts and Bar charts - Have you heard of them? If you have, you would be right at home with doing them in Python. This course is all about visualizing data using charts and plots with Python's most popular visualization package - Matplotlib.

Data visualization tools are used to analyse, format and publish the data. This data is used in statistical analysis, research, health care, social media analysis etc.,

Matplotlib is a data visualization library in Python on which other libraries like Seaborn are built.

Having a good understanding of Matplotlib helps you learning the other libraries quickly. And this tutorial presents you with various examples in order to get comfortable with the different forms of plots and interfaces of Matplotlib.

At the end of this course, you will be able to plot data using a variety of plotting tools like Pie chart, Bar chart, Histogram, Line plots, Scatter plots etc using Python's Matplotlib package.

Please feel free to ask questions on any issue that you may face while taking the course, our team would be glad to help you.

Who this course is for:

  • Anybody having a basic knowledge of Python Programming language and interested to learn Matplotlib can take up this course.
  • Software Programmers

Matplotlib Tutorial Features

What you'll learn

  • Explore Matplotlib's interfaces.
  • Apply the various techniques in Matplotlib for visualizing data.
  • Create various types of visualizations.

Requirements

  • Basics of Python programming language.
  • It is recommended to install Python with the required packages on your system. Installing the latest version of Python (3.7) from the Anaconda Distribution website automatically installs Matplotlib and Jupyter notebook along with Python.
  • All examples are demonstrated on the Jupyter Notebook, so it is suggested to use Jupyter notebook to follow along.
Buddhanagar
Kathmandu, Nepal
9818500185
Sun-Thurs 10:00am-6:00pm
[email protected]
24 X 7 online support