GP: Visualizing Earnings Based On College Majors

Hello, Please review my guided project.

Please provide me feedback to help me improve.

The link of my project :

Hello @biadboze! Could you upload your notebook on GitHub or Jupyter Nbviewer?


I did, it’s on Github

Hello @biadboze!

Here is some feedback:

  • Name your sections with more descriptive titles: like what is “Using scatter plots”? What did you do in that section?
  • Improve your plots by providing more descriptive axes labels’ names, for example: “Median salary ($)” and then adding a $ symbol to the top number like this: 100000$).
  • Give a description to all plots. They should provide some useful information.
  • When you answer the question Do students in more popular majors make more money? to which plot do you refer? The one above the question? If so, it has no title so we don’t know what you mean.
  • Name all your plots.
  • When you write This plot is for:… you don’t answer the question.
  • When you plot histograms it’s absolutely not clear what they refer too. As before they lack titles and axes labels. The grid on histograms distracts the reader’s attention.
  • You can also remove the top and left spines from your plot. Try to improve your data-ink ratio when necessary.
  • It’s better to import all libraries at the beginning of the project.
  • You plot in the first 4th section (you have two 4th sections) has no meaning. The reader will not see anything useful (even if you provide the answer). Try to reduce the number of majors and present the data more effectively.
  • In the section 4- Others questions your grouped bar plot is full of clutter. It’s too long, has a lot of useless information, has no title and x-axis label. You also didn’t give any explanation to that plot (but it will be useless since the plot is too cluttered).
  • What do the last two plots represent? You didn’t explain them, they have no title, no axes labels.

That’s all for me! Your main problem is data visualization. I would recommend you to read “Storytelling with Data: A Data Visualization Guide for Business Professionals” by Cole Knaflic. It will help you to make your chart more beautiful and informative.

Happy coding!

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