bug when filling missing values with transform?

Hello there,

Consider this

df = pd.DataFrame({'group' : ['A', 'A', 'A', 'B',
                                              'B', 'B', 'B', 'B'],
                                              'B' : [np.nan,np.nan,np.nan,-4,-2,5,8,7],
                                              'C' : [-5,5,-20,0,np.nan,5,4,-4]})

df
Out[13]: 
     B     C group
0  NaN  -5.0     A
1  NaN   5.0     A
2  NaN -20.0     A
3 -4.0   0.0     B
4 -2.0   NaN     B
5  5.0   5.0     B
6  8.0   4.0     B
7  7.0  -4.0     B

Now I want to fill forward the missing values in C for each group

df.groupby('group').C.fillna(method ='ffill')
Out[11]: 
0    -5.0
1     5.0
2   -20.0
3     0.0
4     0.0
5     5.0
6     4.0
7    -4.0
Name: C, dtype: float64

df.groupby('group').C.transform('ffill')
Out[12]: 
0   -5.0
1   -5.0
2   -5.0
3    5.0
4    5.0
5    5.0
6    5.0
7    5.0
dtype: float64

the transform output is wrong. Is that expected? Pandas 18.1

[mroeschke]

Looks like https://github.com/pandas-dev/pandas/issues/24211 is the same issue and has a unit test so I think we are safe to close

[rhshadrach]

@geoffrey-eisenbarth It appears so. I’d also recommend searching the groupby tests for fillna used in transform - perhaps one already exists and this issue wasn’t known about.