Visualizing the Gender Gap In College Degrees

Jupyter Notebook in Python using matplotlib for visualizing the gender gap in college degrees as part of Dataquest's Storytelling Through Data Visualization guided project.

Release History

01/01/19 - Version 1.0 - Initial release

Data Set

Job outcomes of students who graduated from college between 2010 and 2012. The original data on job outcomes was released by American Community Survey, which conducts surveys and aggregates the data. FiveThirtyEight cleaned the dataset and released it on their Github repo.

Column Definitions

• Rank - Rank by median earnings (the dataset is ordered by this column).
• Major_code - Major code.
• Major - Major description.
• Major_category - Category of major.
• Total - Total number of people with major.
• Sample_size - Sample size (unweighted) of full-time.
• Men - Male graduates.
• Women - Female graduates.
• ShareWomen - Women as share of total.
• Employed - Number employed.
• Median - Median salary of full-time, year-round workers.
• Low_wage_jobs - Number in low-wage service jobs.
• Full_time - Number employed 35 hours or more.
• Part_time - Number employed less than 35 hours.

Output

License

MIT License