python - Groupby on condition and calculate sum of subgroups -

here data:

import numpy np  import pandas pd z = pd.dataframe({'a':[1,1,1,2,2,3,3],'b':[3,4,5,6,7,8,9], 'c':[10,11,12,13,14,15,16]}) z        b   c 0   1   3   10 1   1   4   11 2   1   5   12 3   2   6   13 4   2   7   14 5   3   8   15 6   3   9   16 

question:

how can calculation on different element of each subgroup? example, each group, want extract element in column 'c' corresponding element in column 'b' between 4 , 9, , sum them all.

here code wrote: (it runs cannot correct result)

gbz = z.groupby('a') # displaying groups: gbz.apply(lambda x: print(x))   list = []  def f(x):     list_new = []     row in range(0,len(x)):         if (x.iloc[row,0] > 4 , x.iloc[row,0] < 9):             list_new.append(x.iloc[row,1])     list.append(sum(list_new))  results = gbz.apply(f) 

the output result should this:

      c 0   1   12 1   2   27 2   3   15 

it might easiest change order of operations, , filter against criteria first - not change after groupby.

z.query('4 < b < 9').groupby('a', as_index=false).c.sum() 

which yields

     c 0  1  12 1  2  27 2  3  15