opposite of df.diff() in pandas

You can use rolling with a window size of 2 and sum:

df['f'] = df['d'].rolling(2).sum().shift(-1)

    c  d    f
0  dd  1  3.0
1  ee  2  5.0
2  ff  3  7.0
3  gg  4  9.0
4  hh  5  NaN

df.cumsum()

Example:
data = {'a':[1,6,3,9,5], 'b':[13,1,2,5,23]}
df = pd.DataFrame(data)

df = 
    a   b
0   1   13
1   6   1
2   3   2
3   9   5
4   5   23

df.diff()

a   b
0   NaN NaN
1   5.0 -12.0
2   -3.0    1.0
3   6.0 3.0
4   -4.0    18.0

df.cumsum()

a   b
0   1   13
1   7   14
2   10  16
3   19  21
4   24  44