getting the maximum value of each group after groupby pandas

Asked Feb 05 '20 at 19:32

Active Feb 05 '20 at 19:32

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I have this dataframe and I want to groupby city and country and get the city with higher pop in each group:

df = pd.DataFrame({'country': ['Brasil', 'Brasil' , 'EUA', 'EUA'],
                  'city': ['Santos', 'São Paulo', 'Orlando', 'Nova York'],
                  'pop': [100000, 500000, 200000, 550000]})
df

What I want:

country city pop
Brasil São Paulo 500000
EUA Nova York 550000

What I have already done:

df.groupby(['country','city']).loc[df.pop == df.pop.max()]

Python returns: "AttributeError: Cannot access callable attribute 'loc' of 'DataFrameGroupBy' objects, try using the 'apply' method"

I know that I must use apply, but I still don´t understand the logic of it in python. Does anyone know how to help me?

asked Feb 05 '20 at 19:32

jvqp

2

`df.groupby(['country','city'],as_index = False)['pop'].max()`? – ansev Feb 05 '20 at 19:33
@ansev I said it worked but I was wrong. This didn´t change my output – jvqp Feb 05 '20 at 19:46
`df =df.groupby(['country','city'],as_index = False)['pop'].max()` – ansev Feb 05 '20 at 20:11

getting the maximum value of each group after groupby pandas

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