I have a pandas dataframe called females:
iid id gender idg condtn wave round position positin1 order \
0 1 1.0 0 1 1 1 10 7 NaN 4
1 1 1.0 0 1 1 1 10 7 NaN 3
and so on. each iid has around ten rows and in total there are around 3500 rows.
I also have a dataframe:
females_scores = pd.DataFrame(columns=['iid', 'Number Matches', 'Number Decisions', 'Match Rate', ' Decision Rate'])
which has data on each iid.
My question: What is the best way to add a column in the first dataframe (females) that maps the "Number Decisions" in the second dataframe according to iid, to every row in the first dataframe?
I was thinking of using np.where, but this would return an array? Im not sure what the best path is tbh thanks in advance!
