Find the total % of each value in its respective index level

April 21, 2022

I’m trying to find the % total of the value within its respective index level, however, the current result is producing Nan values.

pd.DataFrame({"one": np.arange(0, 20), "two": np.arange(20, 40)}, index=[np.array([np.zeros(10), np.ones(10).flatten()], np.arange(80, 100)])

DataFrame:

        one  two
0.0 80    0   20
    81    1   21
    82    2   22
    83    3   23
    84    4   24
    85    5   25
    86    6   26
    87    7   27
    88    8   28
    89    9   29
1.0 90   10   30
    91   11   31
    92   12   32
    93   13   33
    94   14   34
    95   15   35
    96   16   36
    97   17   37
    98   18   38
    99   19   39

Aim:
To see the % total of a column ‘one’ within its respective level.

Excel example:

Current attempted code:

for loc in df.index.get_level_values(0):
 df.loc[loc, 'total'] = df.loc[loc, :] / df.loc[loc, :].sum()

>Solution :

IIUC, use:

df['total'] = df['one'].div(df.groupby(level=0)['one'].transform('sum'))

output:

      one  two     total
0 80    0   20  0.000000
  81    1   21  0.022222
  82    2   22  0.044444
  83    3   23  0.066667
  84    4   24  0.088889
  85    5   25  0.111111
  86    6   26  0.133333
  87    7   27  0.155556
  88    8   28  0.177778
  89    9   29  0.200000
1 90   10   30  0.068966
  91   11   31  0.075862
  92   12   32  0.082759
  93   13   33  0.089655
  94   14   34  0.096552
  95   15   35  0.103448
  96   16   36  0.110345
  97   17   37  0.117241
  98   18   38  0.124138
  99   19   39  0.131034