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https://github.com/mseri/intro_to_python

8hrs intro to python for mathematicians (Reading University, Enhancement Week)
https://github.com/mseri/intro_to_python

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8hrs intro to python for mathematicians (Reading University, Enhancement Week)

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# Introduction to Python

[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/mseri/intro_to_python/master)

This repository contains the interactive (ipython) lecture notes that I've used for a very brief introduction to python programming for scientists, held at Reading University during the enhancement week.
Due to time constraints there are many topics that were not covered, but overall I believe it should provide enough informations to start doing something and understand how and where to look for more.

Note that the lecture notes are not self-contained, during the course I was adding examples and additional explanations here and there to integrate the content.

- [Lecture 0](https://github.com/mseri/intro_to_python/blob/master/Lecture%200.ipynb) contains informations on the tools used during the coruse and additional references.
- [Lecture 1](https://github.com/mseri/intro_to_python/blob/master/Lecture%201.ipynb) is an introduction to Python data structures.
- [Lecture 2](https://github.com/mseri/intro_to_python/blob/master/Lecture%202.ipynb) gives a brief overview of Python control structures, modules and functions.
- [Exercises 1](https://github.com/mseri/intro_to_python/blob/master/Exercises%201.ipynb) has some exercises that could be approached with what has been done in the first two lectures.
- [Lecture 3](https://github.com/mseri/intro_to_python/blob/master/Lecture%203.ipynb) is an introduction to matplotlib.
- [Lecture 4](https://github.com/mseri/intro_to_python/blob/master/Lecture%204.ipynb) is an introduction to scipy and numpy.

Online there are many many good resources, with many more details. I tried to link the ones I know and liked, and sometimes overlooked while preparing these notes.
If something is missing pleas let me know and I will integrate the comments and the links.
You can click on the binder badge to directly run online an interactive version of these notebooks.

## Update (17.02.2021)
Lots of very good material has kept appearing since I wrote these. Have a look at:
- [Python Programming And Numerical Methods: A Guide For Engineers And Scientists¶](https://pythonnumericalmethods.berkeley.edu/notebooks/Index.html)
- [Learning Scientific Programming with Python](https://scipython.com/)