This repository of Python tutorials is primarily aimed at Life Science scientists starting to peek into bioinformatics.
I routinely use Python for a variety of tasks, that can be boiled down to:
- Managing very large data tables (cool way to say that: data wrangling)
- Automating custom data workflows
- Performing statistical analyses
- Plotting data
- Learning new stuff
In my notebooks, I try to cover the implementation details of each topic and overcome the typical limitations I find in tutorials around here, generally more fit to a developer's mind. Usually:
- No logical connection is skipped
- Code is commented. What the code is supposed to do is talked about, and the reasons why are talked about
- How data is transformed, why it is transformed and what the transformed data looks like is discussed
An intermediate knowledge of the Python 3 programming language is required. In addition, you should have an idea of what Pandas, Numpy, Matplotlib and Seaborn libraries are and do.