This project was a recreation of the book Effective Pandas by Matt Harrison. Matt conducted a class with my work team, and this process for applying the Pandas library was eye opening. It inspired me to get the book and work through the code myself.
The objective for my effort was to recreate the code in the book and complete the offered Psets to test for knowledge. Each of the Jupyter Notebooks covers a range of chapters depending on the density of the materials. While much more informed on his methodology, I fully expect to return to the book as a reference in future efforts to conduct pandas data analysis.
Below are direct links to the Notebooks in the repository. Originally I was not going to publish the project, but I wanted to allow others to review the materials. In some instances I have deviated from Matt's code due to differences in the libraries. Unfortunately, I did not freeze the versions during my recreation. Pandas 2.0 was released during my efforts, and this resulted in some syntax changes versus Matt's versions in the book. In addition, I only caught this toward the tail end of my journey. It forced me to update a number of libraries to run notebooks in the latter part of the book. This means some of the earlier notebook may not run with pandas 2.0 implemented as my requirements document indicates. You may need to do some testing if there is any instance in reusing or the notebooks.
- Eff Pandas Ch1 - Ch9
- Eff Pandas Ch10 - Ch13
- Eff Pandas Ch14 - Ch15
- Eff Pandas Ch16 - Ch21
- Eff Pandas Ch22 - Ch24
- Eff Pandas Ch25 - Ch30
- Eff Pandas Ch31 - Ch33
- Eff Pandas Ch34 - Ch35
NOTE: Final Chapter on debugging was not included in the final notebook. It has excellent materials on how to navigate debugging chainning, Matt's preferred methodology for pandas code execution.