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pythonpandaspandas-groupbyaggregate

groupby aggregation return different column

suppose i have a df and i want to groupby 'item' and aggregate on min and max of thing1 but return thing2. so for item 'c' the min is 1 so 0 is returned and the max is 3 so 100 is returned

item thing1 thing2
a 1 10
a 4 20
b 1 30
c 1 0
c 2 10
c 3 100
item min_thing1 -> thing2 max_thing1 -> thing2
a 10 20
b 30 30
c 0 100

I know i can aggregate min and max on thing1 by simply writing :

df.groupby('item').agg({'thing1' : [np.min, np.max]})

but how would i aggragate on thing2 by using min and max on thing1

Solution

  • Can use min/max directly

    >>> df.groupby('item').agg(lambda s: [s.min()['thing2'], s.max()['thing2']])

          thing1  thing2
item                
a         10      20
b         30      30
c          0     100

    Can, of course, rename the columns after the operation.