In this repository are all the files needed to complete the 4-week Python section of new member education for Cornell Data Journal.
All resources, unless otherwise specified, are created by Nikhil Chinchalkar.
Each of the workbooks goes into a fundamental data science concept. Here's a short description of the content in each workbook:
- Workbook 1: an introduction to Python, including working with lists, libraries, loops, and dataframes
- Workbook 2: the basics of SQL, including filtering (with NaNs), grouping, and merging
- Workbook 3: creating visualizations, including scatterplots, histograms, and bar charts
- Workbook 4: the fundamentals of linear regressions, including correlations, train/test splits, evaluation metrics, and significance tests
The data sources can be found below: