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SUBMIT YOUR IDEAI saw that too, Dave! I have to correct those spelling errors, haha.
Fairly simple prep and blend.
How do you suggest we address the partially missing/corrupt data? For example the input dataset is missing values for what I am inferring to be 9_bj. In its place we get a row of nulls, but mixed in with the nulls we appear to get a rating, rating_count and ingredients. I recommend we go back to the original dataset to address import errors for 9_bj, 5_hd, 10_hd, 49_hd, 50_hd, 51_hd, 60_hd, 68_hd, and all the _breyers data.
Thoughts?
I viewed it as data we should ignore, based on the target output files -- a test of your data cleaning skills.
I also saw two coconut cream non-allergen ice creams that were not in the target output.