In this video, I cover some strategies for aggregating and merging rows that are similar or near-duplicates in a Python pandas dataframe into a single row. This is helpful for situations where the information could easily be captured in a single row and you want to preserve the information but decrease the amount of rows. I used this recently when working with a set of Twitter data from Kaggle. I also cover how to simply drop the true duplicates, or drop similar rows if that is the preferred solution in your case.