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Applying a function to multiple columns in groups in Pandas

Pandas
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DataFrame Cookbooks
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Data Aggregation Cookbook
schedule Jul 1, 2022
Last updated
local_offer PythonPandas
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tocTable of Contents
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Consider the following DataFrame:

df = pd.DataFrame({"A":[2,3,4],"B":[5,6,7],"group":["a","a","b"]})
df
A B group
0 2 5 a
1 3 6 a
2 4 7 b

To group by group, and then apply a function on multiple columns in each group:

def f(my_df):
return pd.Series({"C": my_df["A"].sum() + my_df["B"].sum()})

df.groupby("group").apply(f)
C
group
a 16
b 11

Note the following:

  • our f function is called twice in this case - once for each group

  • argument for f is a DataFrame representing each group

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Published by Isshin Inada
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