Project Visualizing Earnings Base on College Majors

https://app.dataquest.io/m/146/guided-project%3A-visualizing-earnings-based-on-college-majors/6/next-steps

Visualizing_Earnings_Base_on_College_Majors.ipynb (609.8 KB)

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Hi @fh8888!

Thank you for sharing your project. Great job on the code – I had really similar workflow. I have just a few notes:

  • In line[4], you do not need to use the recent_grads.index, you can simply use recent_grads with the len() function
  • In line[14], you do not need to use
    fig = plt.figure()
    ax1 = fig.add_subplot(111)
    you can abbreviate the code to…
    fig, ax = plt.subplots()
    …since you are creating just the one graph in one plot

The graph from line[14] (Men & Women vs. Median Income) was my favorite and I incorporated something similar into my own project.

I hope this helps. Thank you again for sharing your work. Happy learning!

3 Likes

Hi @fh8888,

Congratulations on finishing your project!

I agree with @tetyana about the code cell [14], it was a great idea to combine these 2 plots.

Some comments from my side. I would definitely recommend you to add a title, introduction and conclusion, to divide the project into sections with corresponding subheadings. And also explanation of your findings in markdown cells below the plots. In the code cell [2], it’s better write recent_grads.head() and recent_grads.tail(), without print(), to visualize the datase in a form of table, that will be easier to read. Then the code cell [18] and its output is a little bit confusing, and probably needs some explanations (its purpose and its message). Well, as I told, adding explanatory markdown cells in general will be great.

Happy coding!