Make Several Operations In A Dataframe At Once

I am trying to do in a smart way several calculation by using .groupby with pandas dataframe, with the following data: import numpy as np import pandas as pd df = pd.DataFrame({'A

Solution 1:

You can use agg():

df.groupby(['A','B']).agg({'C': diff, 'D': [per, ratio1]})

To skip the renaming part you can call your functions var1, var2 and var3 and use it in groupby.

var1 = lambda x: max(x)-min(x)
var2 = lambda x: (max(x)-min(x))/max(x)
var3 = lambda x: (max(x)-min(x))/ len(x)
df.groupby(['A','B']).agg({'C': var1, 'D': [var2, var3]})
df.columns = df.columns.droplevel()

EDIT

Try with:

defvar1(x): returnmax(x)-min(x)
defvar2(x): return (max(x)-min(x))/max(x)
defvar3(x): return (max(x)-min(x))/ len(x)

EDIT of EDIT

This works for me on pandas version 0.19.2:

import numpy as np
import pandas as pd

df = pd.DataFrame({'A' : ['foo', 'bar', 'foo', 'bar',
                              'foo', 'bar', 'foo', 'foo'],
                       'B' : ['one', 'one', 'two', 'three',
                              'two', 'two', 'one', 'three'],
                       'C' : np.random.randn(8),
                       'D' : np.random.randn(8)})

defvar1(x): returnmax(x)-min(x)
defvar2(x): return (max(x)-min(x))/max(x)
defvar3(x): return (max(x)-min(x))/ len(x)

df = df.groupby(['A','B']).agg({'C': var1, 'D': [var2, var3]})

df.columns = df.columns.droplevel()