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Getting Stared with Matplotlib - Introduction to Matplotlib

Matplotlib is one of the most popular Python packages used for data visualization. It is a plotting library for the Python programming language and its numerical mathematics extension NumPy. It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK+.

Matplotlib was originally written by John D. Hunter.

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Several toolkits are available which extend Matplotlib functionality. Some are separate downloads, others ship with the Matplotlib source code but have external dependencies:

  • Basemap: This is a great tool for creating maps using python in a simple way.
  • Cartopy: It is a Python package designed for geospatial data processing in order to produce maps and other geospatial data analyses.
  • Excel tools: These are utilities for exchanging data with Microsoft Excel.
  • GTK tools: This is an interface to the GTK+ library
  • Qt interface: This is used for creating GUIs.
  • Mplot3d: Used for creating 3-D plots.
  • Natgrid: This is an interface to the natgrid library for gridding irregularly spaced data.
  • matplotlib2tikz: An export to Pgfplots for smooth integration into LaTeX documents.

In this hands-on tutorial, we will show you how you can use various features of Matplotlib for Machine Learning, Deep Learning, or other purposes.

  • IMPORTANT: Please run the following command on a web console before starting off with the project, or if you are getting a 404: Not found error on the right side:

    rsync -avz --ignore-existing /cxldata/cloudxlab_jupyter_notebooks/ /home/$USER/cloudxlab_jupyter_notebooks/
    

Let us begin!


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