Dear dataquest community,
I just finished my second project on this platform : “Visualizing Earnings Based on College Majors”
Don’t hesitate to tell me what you’ve liked and what you did not when reading it, as well as new ways to improve it.
Visualizing Earnings Based On College Majors.ipynb (1.3 MB)
Click here to view the jupyter notebook file in a new tab
I really enjoyed your project. Here is my comments (for your consideration of course!). Most of my comments are more stylistic.
What I really liked:
- Very well laid out, and excellent use of headings and link embeds.
- I loved the hexbins. Never heard of this graph before haha!
- I loved the scatterplot matrices. Excellent choice to show
- I love the combination of tables and graphs to tell the narrative. You also used a variety of different graphically techniques that makes your project stand out. Very well thought out.
- This in combination with your Jupyter lab bolding in text (e.g., cell 29) is fantastic!
- I loved the summary and conclusion at the end. After a thorough analysis, I am glad to see you summarized it.
Dropping the null values. In the case of this project, there was only up to 4 distinct rows with null values. Depending where you are in DQ, you will learn about imputation. Going forward, you want to investigate why these null values are there. You may be able to determine the values based on other columns. You will also understand your data more because often times you will see some nuances you didn’t know before.
- On cell 29, I believe you meant to say “16.8% of the majors are predominantly female”.
- I believe there is some repetition between the findings in cell 29 and cell 32.
- For some of your graphs, you might want to make the axis labels and titles a bit bigger.
- You might want to include some text underneath the graphs. It becomes a bit challenging after seeing so many graphs to follow what is going on (e.g., the row of histograms, then saying “according to the histogram…” - which histograms for which conclusions?. I do recognize you have your comments at the bottom of each series of plots, which is great. But you might want to consider adding a few sentence summaries after the graphs to point out the trend (not always that obvious to the non data initiated!).
- I would never be afraid to do some additional research into why the trends I see are what they are and put the references into the notebook. For example, what are some reasons why some majors have more females than males?; Why does mathematics and computer science have some of the highest unemployment rates? Do these vary by gender? I am not saying conduct a thesis level of research, but don’t be shy to offer some explanation for some findings. Or why they make sense or don’t make sense. I realize this may be beyond the scope of the project, but it would add tremendous value to your analysis, and show off your research abilities.
- I found some typos throughout. You might want to consider copying and pasting into a Word document to do a quick spell check. Also I would try to avoid informal language such as “gonna”
Overall, really good job raduspaimoc. Very thorough. I look forward to your next project!
First of all, thanks for the review of the technical comment, and stylistic comments will make me improve a lot.
Currently, I’m doing the " Storytelling Through Data Visualization" part, I look forward to coming back to some projects when I’m done and improve them.
This Guided Project Review: Exploring Ebay Used Vehicles Data is my first project and I consider I made standing out analysis, If you want, it would be helpful If I receive feedback from you.