My attempt to normalize and analyze data extracted from a Hacker News salary survey conducted on 3/21/16.
This was a side project. I was interested in seeing how much information could be gleaned from the survey dataset after the data had been cleaned and transformed.
I extracted the data and wrote the queries to cleanse and transform it.
Python scripts run SQL queries on a local PostgreSQL instance.
I used data cleansing and transformation techniques learned as a data engineer at Loot Crate. My original goal was to create D3 visualizations with some of the analyses I wrote but ran out of steam trying to comprehend D3's documentation.