Closed td928 closed 2 years ago
Hey @SashaWeinstein I think I was able to side step the join issue by setting the dataframe index to the geographies and then do pd.concat. I think it should handle the general case. Please let me know if this makes sense and happy to talk through if needed.
This looks good to me as well - I think we should try to settle on same naming conventions for our csv's similar to the way we write issues. happy to chat about this whenever
Hey @SashaWeinstein could you point to the file I made .csv.csv mistake. I don't think the final merged final has an extra csv extension
Ok sorry I was wrong. The files with the .csv.csv already had them I think? In the files changed I get a couple of ...rnal_review/area_historic_by_puma.csv.csv → ...uction/puma/area_historic_by_puma.csv.csv
and the same for citywide and borough
ok got it. I think this doesn't impact this work for now. Should we merge this in?
Ok I think I figured out the issue, it's the historic indicators that are saved as .csv.csv in the internal review folders that these read from. Can you rename these and then we merge? Also @mbh329 can you do an eyeball check that the numbers for your indicator are the same in the internal review and the external? As an additional set of eyes for quality just to be sure. Sorry if this is overkill, we have a couple minutes before standup and I feel like we might as well just use this time to clean and check
Eyeball checked housing production myself, it all looks good
The data for my indicator looks good, I checked it against a few pumas and boroughs
Uploaded to digital ocean, all looks good
Awesome, looks great
Haven’t checked digital ocean and but this all look good.
still need to wait for Max changes merged in to create the final combined external review files. Script ready to be reviewed.