This is not a comprehensive Python tutorial but instead is intended to highlight the parts of the language that will be most important for us. You can download python form the python.org. I recommend installing Anaconda distribution, which already includes most of the libraries that are need to do data science.
- Python is very slow when written badly.
- Translate C code into Python is often bad idea.
- Pythonic solution sometimes result in drastic performance improvement.
- Utilize libraries' capabilities more than you skill.
- Python Basic : Basic python syntax and concept
- Python Advance : Object Oriented Programming
- Numpy Basic : Simple Numpy Operation
- Pandas Basic : Simple Pandas Operation
- MatplotLib : Line, Point, Bar Graph, Pie Chart
- Scikit Learn : (Will be added later)
This tutorial is written in Python-3 (Numpy, Pandas, MatplotLib, Seaborn, Scikit-leanr). Anaconda already include all there libraries.
Happy to accept any pull requests if you want to add anything which can improve this tutorial.