Calculate row-wise average pandas python

I am new to python. I want to calculate the row-wise average based on unique IDs.

My DataFrame is:

       ID            Time[h]  concentration[g/L]  
15127  V527          23.425      59.9  
20361  V527          27.570      73.4  
21880  V527          29.281      75.4
33133  V560          27.677      75.9  
35077  V560          30.183      75.7  
37117  V560          31.847      74.6

I want to calculate the row wise average based on each ID. so that my output looks something like this

       ID            Time[h]  concentration[g/L]  avg [g/L]
15127  V527          23.425      59.9               NaN
20361  V527          27.570      73.4               66.5
21880  V527          29.281      75.4               74.4
33133  V560          27.677      75.9               NaN 
35077  V560          30.183      75.7               66.5 
37117  V560          31.847      74.6               75.8

I tried:

df.groupby(['ID'])['concentration[g/L]'].mean()

But this returned mean for each ID, as a whole.

So I tried this:

df.groupby(['ID'])['concentration[g/L]'].transform('mean')

This returns again the mean of each group, but fills to the same length of my df.

Can you please help me, if something is not clear I can rephrase my question.

Thanks in Advance!

Solution

Try using pd.rolling.mean with a window of 2:

>>> df['avg [g/L]'] = df.groupby('ID')['concentration[g/L]'].rolling(2).mean().values
>>> df
         ID  Time[h]  concentration[g/L]  avg [g/L]
15127  V527   23.425                59.9        NaN
20361  V527   27.570                73.4      66.65
21880  V527   29.281                75.4      74.40
33133  V560   27.677                75.9        NaN
35077  V560   30.183                75.7      75.80
37117  V560   31.847                74.6      75.15