- Use Pandas to clean and format datasets.
- Create a Jupyter Notebook describing the data exploration and cleanup process.
- Create a Jupyter Notebook illustrating the final analysis.
- Use
PyViz
,GeoViews
, andHvplot
to create 6-8 visualizations of the data (ideally, at least two per "question"). - Include exported PNG files in
README.md
and presentation. - Optional: Use at least one API.
- Use one new Python library that hasn't been covered in class.
README.md
should include:- Summary of major findings
- Questions as headings
- Short descriptions of findings and relevant plots
- Questions you found interesting and what motivated you to answer them.
- Where, and how, the data was to found to answer these questions.
- The data exploration and cleanup process (accompanied by your Jupyter Notebook).
- The analysis process (accompanied by your Jupyter Notebook).
- Your conclusions, which should include a numerical summary and visualizations of the summary.
- The implications of your findings: What do the findings mean? How do they impact finance?
- Sufficiently large
- Consistent format
- Ideally, contain more data than required
- Well documented