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## Where do I start with Python?
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* TOC
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## The goal
We have to start somewhere. Why not with an overview?
Questions to [David Rotermund](mailto:davrot@uni-bremen.de)
## [Python](https://www.python.org/)
> Python is a programming language that lets you work quickly and integrate systems more effectively.
* There is an offical [Python Tutorial](https://docs.python.org/3/tutorial/)
* YouTube: Socratica Channel [Python Programming Tutorials](https://www.youtube.com/watch?v=bY6m6_IIN94&list=PLi01XoE8jYohWFPpC17Z-wWhPOSuh8Er-)
## [VS code](https://code.visualstudio.com/)
You need an editor for writing Python code. We suggest to use [VS code](https://code.visualstudio.com/) as an editor. It supports many operations systems.
> Code editing. Redefined. Free. Built on open source. Runs everywhere.
* [Getting Started with Python in VS Code](https://code.visualstudio.com/docs/python/python-tutorial)
## [Numpy](https://numpy.org/doc/stable/index.html)
[What is NumPy?](https://numpy.org/doc/stable/user/whatisnumpy.html)
> NumPy is the fundamental package for scientific computing in Python. It is a Python library that provides a multidimensional array object, various derived objects (such as masked arrays and matrices), and an assortment of routines for fast operations on arrays, including mathematical, logical, shape manipulation, sorting, selecting, I/O, discrete Fourier transforms, basic linear algebra, basic statistical operations, random simulation and much more.
* [NumPy quickstart](https://numpy.org/doc/stable/user/quickstart.html)
* [NumPy: the absolute basics for beginners](https://numpy.org/doc/stable/user/absolute_beginners.html)
* [NumPy fundamentals](https://numpy.org/doc/stable/user/basics.html)
* [NumPy for MATLAB users](https://numpy.org/doc/stable/user/numpy-for-matlab-users.html) (if you are a Matlab user)
## [Matplotlib](https://matplotlib.org/stable/index.html)
> Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python.
* [Pyplot tutorial](https://matplotlib.org/stable/tutorials/introductory/pyplot.html)
## [Pandas](https://pandas.pydata.org/)
> pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language.
[10 minutes to pandas](https://pandas.pydata.org/docs/user_guide/10min.html)