# Course Outline

This course is divided in three parts:
1. Installation, Jupyter and Python Basics
2. Numpy and Matplotlib
3. Pandas, Seaborn and Matplotlib

## 0. Material
All material is available on gitlab.

Go to [https://git.cs.upb.de/chthiel/python-tutorial](https://git.cs.upb.de/chthiel/python-tutorial) to get the material or better use git to clone the repository:
```
git clone https://git.cs.upb.de/chthiel/python-tutorial.git
```
Note: The material is not finished. We will update it.

## 1. Installation and Python Basics
In this section we will set up your development environment and get familiar with very basic Python commands.
Please follow the Installation Manual for your OS: [Windows](install_windows.html), [Linux](install_linux.html).

#### Material
1. Relevant Notebooks: [03_python.ipynb][03_python.ipynb]
2. Relevant CheatSheet: [beginners_python_cheat_sheet_pcc_all][beginners_python_cheat_sheet_pcc_all]

## 2. Numpy and Matplotlib
1. Introduction: [Numpy/SciPy](numpy.html)
2. Relevant CheatSheet: [Numpy_Python_Cheat_Sheet][Numpy_Python_Cheat_Sheet]
3. Relevant Exercises: `gertingold-numpy-tutorial-exercises.ipynb`

## 3. Pandas, Numpy, Scipy, Seaborn and Matplotlib
Pandas is a very import package to manipulate and work with taublar data. In this section we will learn how to use the basic pandas datastructure called the `DataFrame`.

#### Material
1. Relevant Notebooks: `05_matplotlib.ipynb`, `07_pandas.ipynb`, `07-01_pandas-apply.ipynb`
2. Relevant CheatSheet: [Pandas_Cheat_Sheet.pdf][Pandas_Cheat_Sheet.pdf]
3. Relevant Exercises Pandas: `03-01_Pandas_Task.ipynb`
4. Relevant Exercises Numpy, Scipy and Plots: `03-02_Signal_Analysis_Task.ipynb`


[03_python.ipynb]: https://git.cs.upb.de/chthiel/python-tutorial/blob/master/notebooks/03_python.ipynb
[beginners_python_cheat_sheet_pcc_all]: https://git.cs.upb.de/chthiel/python-tutorial/blob/master/cheat_sheets/beginners_python_cheat_sheet_pcc_all.pdf
[Numpy_Python_Cheat_Sheet]: https://git.cs.upb.de/chthiel/python-tutorial/blob/master/cheat_sheets/Numpy_Python_Cheat_Sheet.pdf
[Pandas_Cheat_Sheet.pdf]: https://git.cs.upb.de/chthiel/python-tutorial/blob/master/cheat_sheets/Pandas_Cheat_Sheet.pdf