How to update group in df after iteration

I am trying to apply an operation to each data frame group, and then update the corresponding rows in the original data frame. However, the new values are not being inserted at the correct locations. Effectively, I am trying to diff within each group.

mydf = pd.read_csv("my.csv")
mydf["forwardDelta"] = np.NaN

for name, group in mydf.groupby(["a", "b"]):
    group["forwardDelta"] = group["c"] - group["c"].shift(1)
    for index, row in group.iterrows():
        mydf.iloc[index, 4] = row["forwardDelta"]

I think here no loops are necessary - use DataFrameGroupBy.diff and if need set values in 5th column use DataFrame.iloc with : for select all rows:

mydf = pd.DataFrame({'a':[5,8]*3,
                      'b':[1,2]*3,
                      'c':[2,7,5,4,3,9],
                      'd':list('abcdef'),
                      'e':range(5,11)}).sort_values(['a','b'], ignore_index=True)


print (mydf)
   a  b  c  d   e
0  5  1  2  a   5
1  5  1  5  c   7
2  5  1  3  e   9
3  8  2  7  b   6
4  8  2  4  d   8
5  8  2  9  f  10

mydf["forwardDelta"] = mydf.groupby(["a", "b"])["c"].diff()

mydf.iloc[:, 4] = mydf["forwardDelta"]

print (mydf)
   a  b  c  d    e  forwardDelta
0  5  1  2  a  NaN           NaN
1  5  1  5  c  3.0           3.0
2  5  1  3  e -2.0          -2.0
3  8  2  7  b  NaN           NaN
4  8  2  4  d -3.0          -3.0
5  8  2  9  f  5.0           5.0