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Getting started with Python

Jupyter notebook

Jupyter notebooks are interactive web-based applications that allow users to create and share documents containing live codes, equations, narrative texts, figures, interactive user interfaces, and other rich media. When combined with the Python kernel, Jupyter notebooks allow users to code in Python and display results in an interactive and convenient way. Jupyter notebooks are really wonderful tools for learning Python, data science, and coding in general.

We strongly recommend installing Python and Jupyter on your PC using the Anaconda distribution, which includes Python, the Jupyter Notebook, and other commonly used packages for scientific computing and data science.

Students enrolled in courses will also be provided with an account and access to a SUSTech server running Jupyter. However, this server can only be accessed from within the SUSTech network. You can use a SUSTech VPN from off-campus locations. Details will be given during the first lecture.

Python tutorials for beginners

There are many, many good tutorials for Python. We encourage you to try out a few yourself. A few examples are listed here, but there are many more on the web. After learning the basics, you should seek out examples particular to your application on your own.

Python for atmospheric and oceanic science

Python for data science

A list of Python resources for the eight statistics topics that you need to know to excel in data science

Python pandas tutorial

The pandas package is the most important tool at the disposal of Data Scientists and Analysts working in Python today.


Advanced techniques


  • Bokeh is a set of tools that allow you to make interactive visualizations in the browser. Some of the interactive demos in this course were made using this fun tool.
  • Making interactive visualizations with Python using Bokeh. This tutorial shows how to reproduce the famous Hans Rosling's The Health and Wealth of Nations plot using Bokeh.


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