I scraped 1.3 million grades across 3,700 professors at my…
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I scraped 1.3 million grades across 3,700 professors at my school to find easier classes, here’s what I found
Quick backstory. I pulled together publicly available grade data from my university to help pick out classes, and ended up with a dataset of about 1.3 million grades across roughly 3,700 professors.
While exploring it, I found some interesting trends. The chart here shows that the university has lost 500+ instructors over the past 6 years, and overall enrollments have dropped by about 30% in that same time period.
Data source: publicly released university grade reports
Method: cleaned and aggregated the raw data, then tracked instructor counts and enrollment over time
Tools: Python
You can explore the dataset and more visualizations here: sfsu.pages.dev/trends http://sfsu.pages.dev/trends nd on the about page as well for more background/data
Would love any feedback as well!
#education
source a
Quick backstory. I pulled together publicly available grade data from my university to help pick out classes, and ended up with a dataset of about 1.3 million grades across roughly 3,700 professors.
While exploring it, I found some interesting trends. The chart here shows that the university has lost 500+ instructors over the past 6 years, and overall enrollments have dropped by about 30% in that same time period.
Data source: publicly released university grade reports
Method: cleaned and aggregated the raw data, then tracked instructor counts and enrollment over time
Tools: Python
You can explore the dataset and more visualizations here: sfsu.pages.dev/trends http://sfsu.pages.dev/trends nd on the about page as well for more background/data
Would love any feedback as well!
#education
source a
| 4,000 mlx | |
| 7 | |
| 0 |