Transform SQL code in Pandas notation

Question

How do I transform this SQL code:

SELECT
   COUNT(DISTINCT DATEn) as count (*)
FROM weather_data
WHERE cast (rain as integer) = 1

using the Pandas notation, like this: df.groupby ('rain') DATEn.sum ()

Please read [how to make good reproducible pandas examples](http://stackoverflow.com/questions/20109391/how-to-make-good-reproducible-pandas-examples) and edit your post correspondingly. — MaxU - stand with Ukraine, Oct 18 '17 at 22:28

score 1 · Accepted Answer · answered Oct 18 '17 at 22:16

1

IIUC:

df.loc[pd.to_numeric(df['rain'], errors='coerce') == 1, 'DATEn'].nunique()

answered Oct 18 '17 at 22:16

Thanks for the help, it worked. I was trying to filter the df ['rain'] and then use the groupby function to group the records by day and count the number of days, but it did not work out very well. – Igor dias Oct 18 '17 at 22:22
@Igordias, i have converted your SQL to Pandas - you didn't use `GROUP BY` clause, so that SQL should return one number, so my solution. ;-) Maybe you should open a new question with a new SQL, including `GROUP BY`... – MaxU - stand with Ukraine Oct 18 '17 at 22:24

1 Answers1