I have a data set in the following form:
Product | Date 123 | 2019-01-01 456 | 2019-01-01 123 | 2019-01-02 123 | 2019-01-03 456 | 2019-01-03 123 | 2019-01-04 456 | 2019-01-04 789 | 2019-01-04
This is just a simplified version. The full set has ~300 products and four months of data. I want to understand how the product set changed over time. It's obviously easy to calculate the count per day and see that I lost one product on Jan 2nd and gained one on Jan4th, but then I don't know what product it was.
Is there a more systematic way of going about this? Ideally the output would show me a list of days and what products dropped out / were added that day. I thought about min(date), max(date) by product before, but products can drop and be added repeatedly and I wouldn't capture this back and forth this way.
Available environments are Python, SQL, and Excel.