README.md

PythonISYA

Basic Python at ISYA

Lecture 1. Basic Python I

00 Binder. Python interpreter. Jupyterlab.
01 Numbers and basic math.
02 Lists.
03 Dictionaries.
04 Iteration.

Lecture 2. Basic Python II

01 Control structures.
02 Functions.
03 Objects.
04 Modules.

Lecture 3. Numpy and Matplotlib

01 Numpy arrays. Slicing.
02 Reading and writing files.
03 Random Numbers.
04 Fast Fourier Transform.
05 Plotting in 1D, 2D.

Lecture 4. Astropy

01 Constants and units.
02 Time and dates.
03 Coordinates.
04 Working with FITS files.
05 Cosmological calculations.
06 Virtual Observatory Access.

Lecture 5. Pandas

01 Reading data with pandas.
02 Visualization.
03 Adding/deleting columns.
04 Stack/Unstack/Transpose.
05 Slicing Pandas Data Frames.
06 Groupby/aggregate.

Lecture 6. (Optional) Reproducible Science.

00 Why reproducible science?
01 Makefiles.
02 Git and Github. 03 Building a reproducible data processing workflow.

References

• https://github.com/PythonBootcampUniandes/notas-de-clase
• https://github.com/ComputoCienciasUniandes/python-bootcamp
• https://github.com/astro4dev/OAD-Data-Science-Toolkit
• https://github.com/saint-germain/astropy