Guided Project: Graph Visualization For Gender Gap in College Degrees

All feedback and comments are welcome.

Gender+Gap+in+College+Degrees.ipynb (825.6 KB)

Click here to view the jupyter notebook file in a new tab

1 Like

Hi Bruce,

Thanks for sharing your project! Well-commented code, easy-to-follow storytelling flow, and interesting observations. Good job!

Here are some comments from my side:

  • To make the project more concise, you can consider gathering all the code cells starting from [3] into one code cell. Then you can put all the technical details for each part of that giant cell as short code comments before each corresponding piece of code. Practically, only the code cell [7] will remain afterwards, probably with more comments added to it.
  • It’s better to remove the numbering from the subheadings names (especially numbers with 0, like 1.0, looks a bit weird).
  • A good practice is to follow a uniform style for quote marks for the string data: or only single, or only double.
  • You might consider re-phrasing a bit the introduction and conclusion. Instead of mentioning that the goal was to practice visualizations and that there were no specific questions to be answered, you can say that the scope was to analyze the data available to understand if there was/is a gender gap for different study fields, if the situation has been recently changing or not, etc. I know that it’s just a project for studying, but you can imagine that it’s a real working project.
  • It’s better to remove the text in red from the project and put it as a question in Q/A section of the Community. By the way, I don’t know the answer :slightly_smiling_face: But at least this line plt.savefig('biology_degrees.png') worked correctly? Have you found the file in the same folder as your project notebook?

Hope my suggestions were useful. Happy learning!

Thank you Elena for your great and very helpful feedback!
I appreciate it.
The *.csv file was saved in the notebook location. I just couldn’t find a way to create a picture of it and show it in the Markdown section of Jupyter.

Happy Guiding!

1 Like