For the final project, you will conduct your own data analysis and create a file to share that documents your findings. You should start by taking a look at your dataset and brainstorming what questions you could answer using it. Then you should use pandas and NumPy to answer the questions you are most interested in, and create a report sharing the answers. You will not be required to use inferential statistics or machine learning to complete this project, but you should make it clear in your communications that your findings are tentative. This project is open-ended in that we are not looking for one right answer.
A PDF or HTML file containing your analysis. This file should include: A note specifying which dataset you analyzed A statement of the question(s) you posed A description of what you did to investigate those questions Documentation of any data wrangling you did Summary statistics and plots communicating your final results Code you used to perform your analysis. If you used a Jupyter notebook, you can submit your .ipynb. Otherwise, you should submit the code separately in .py file(s). A list of Web sites, books, forums, blog posts, github repositories, etc. that you referred to or used in creating your submission (add N/A if you did not use any such resources).
If you used a Jupyter notebook on your computer to create your project, you can include all your code and analysis in the notebook and do not need to create additional files for your analysis. You will still need to export your work in a PDF or HTML format also (see point 1 above), and include this in your submission as well. To download your notebook as an HTML file, click on File -> Download.As -> HTML (.html) within the notebook. If you get an error about "No module name", then open a terminal and try installing the missing module using pip install <module_name> (don't include the "<" or ">" or any words following a period in the module name).