This workshop serves as an introduction to the fundamentals of the Python programming language as well as an overview of the different tools available for data science (numpy, pandas, matplotlib, scikit-learn). The only pre-requisite skill is proficiency in the R programming language.

Included is an application of analyzing party affiliation, ideology, and coalitions in the 1984 House of Representatives using machine learning on roll call vote data.

Note: in order for the Jupyter notebooks (.ipynb) to properly render, please download this repository and locally serve the notebooks. It is possible that they will not display properly on this GitHub repo itself.

• setup.pdf - Detailed instructions on technical set up for this workshop.
• slides.pdf - Lecture slides.
• fundamentals.ipynb - Jupyter notebook on Python fundamentals.
• fundamentals.sol.ipynb - Jupyter notebook on Python fundamentals with solutions to exercises.
• datasci.ipynb - Jupyter notebook introducing the Python data science toolkit.
• datasci.sol.ipynb - Jupyter notebook introducing the Python data science toolkit with solutions to exercises.
• congress-analysis.py - Python script analyzing the 1984 H. of R. using machine learning.
• /data - Data used by Python code in this repo.