I have DataFrame in Python Pandas like below: ID U1 U2 U3 CP CH 111 1 1 0 10-20 1 222 1 0 1 10-20 1 333 0 1 0 20-30 0 444 0 1 1 40-50 0 555 1 0 0 10-20 0 And I need to create column with percent of ‘1’ in column ‘CH’ per combination for:
Tag: aggregation
Aggregation $match within a $sum
I was wondering if it was possible to somehow use the $match operator within the $sum function for aggregation. I want to be able to use the value of the $sum operator within the project fields somehow, I just don’t really understand what the right approach would be for this. Sample Input (may be too long): https://www.toptal.com/developers/hastebin/ixamekaxoq.json Sample Output: (
Ungrouping a pandas dataframe after aggregation operation
I have used the “groupby” method on my dataframe to find the total number of people at each location. To the right of the “sum” column, I need to add a column that lists all of the people’s names at each location (ideally in separate rows, but a list would be fine too). Is there a way to “ungroup” my
Pandas: Tidy up groupby aggregation
I really struggle with tidying up the table into a “normal” dataframe again after having aggregated something. I had a table like that (columns): So I calculated average and std of the Result column over multiple runs using that command: The output is a DataFrame like that: It looks a bit like three levels. df.columns outputs the following multiindex: How
Amount of months calculation in DataFrame in Python Pandas?
I have DataFrame like below: And I need to calculate number of MONTHS from Date column until today. Below I upload result which I need: Answer You can modify this solution for subtract by scalar d: