Pandas dataframe aggregation with different operations-CodePudding

I have created a pandas dataframe called df with this code:

d = {'col1' : [5,3,2,1,34,54,6,7], 
        'col2' : [23,65,7,8,9,12,11,10], 
        'col3' : [65,67,7,11,7,7,9,10], 
        'col4' : [32,32,12,12,1,2,1,3],
        'ops' : [1,1,1,1,2,2,2,2]}

df = pd.DataFrame(data=d)
print(df)

The dataframe looks like this:

   col1  col2  col3  col4  ops
0     5    23    65    32    1
1     3    65    67    32    1
2     2     7     7    12    1
3     1     8    11    12    1
4    34     9     7     1    2
5    54    12     7     2    2
6     6    11     9     1    2
7     7    10    10     3    2

I need to group / aggregate the dataframe df by the column called ops so to get:

the first value of column col1
the minimum value of column col2
the maximum value of column col3
the last value of column col4

So, the resulting dataframe should look like:

Is there a pythonic way of doing it in one go?

CodePudding user response：

Let's try

out = df.groupby('ops', as_index=False).agg({'col1': 'first',
                                             'col2': 'min',
                                             'col3': 'max',
                                             'col4': 'last'})

print(out)

   ops  col1  col2  col3  col4
0    1     5     7    67    12
1    2    34     9    10     3