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|Matplotlib 3.1 cheat sheet.|
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|A site that displays up to date COVID-19 stats, powered by fastpages.|
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|🧇 Make Waffle Charts in Python.|
What Is Python Matplotlib? matplotlib.pyplot is a plotting library used for 2D graphics in python programming language. It can be used in python scripts, shell, web application servers and other graphical user interface toolkits.
What is Matplotlib used for? Matploitlib is a Python Library used for plotting, this python library provides and objected-oriented APIs for integrating plots into applications.
Is Matplotlib Included in Python? Matplotlib is not a part of the Standard Libraries which is installed by default when Python, there are several toolkits which are available that extend python matplotlib functionality. Some of them are separate downloads, others can be shipped with the matplotlib source code but have external dependencies.
|04||Matplotlib Cheat Sheet Plotting in Python.pdf|
These are online read-only versions. However you can
Run all the codes online by clicking here
Open your Prompt and type and run the following command (individually):
pip install matplotlib
Once Installed now we can import it inside our python code.
You can and Starring and Forking is free for you, but it tells me and other people that it was helpful and you like this tutorial.
here if you aren't here already and click
Fork button in the top right corner. You'll be asked to create a GitHub account if you don't already have one.
here and click the big green
Code button in the top right of the page, then click
Extract the ZIP and open it. Unfortunately I don't have any more specific instructions because how exactly this is done depends on which operating system you run.
Launch ipython notebook from the folder which contains the notebooks. Open each one of them
Kernel > Restart & Clear Output
This will clear all the outputs and now you can understand each statement and learn interactively.
If you have git and you know how to use it, you can also clone the repository instead of downloading a zip and extracting it. An advantage with doing it this way is that you don't need to download the whole tutorial again to get the latest version of it, all you need to do is to pull with git and run ipython notebook again.
I'm Dr. Milaan Parmar and I have written this tutorial. If you think you can add/correct/edit and enhance this tutorial you are most welcome
See github's contributors page for details.
If you have trouble with this tutorial please tell me about it by Create an issue on GitHub. and I'll make this tutorial better. This is probably the best choice if you had trouble following the tutorial, and something in it should be explained better. You will be asked to create a GitHub account if you don't already have one.
If you like this tutorial, please give it a star.
You may use this tutorial freely at your own risk. See LICENSE.