Nan in groupby gives a wrong behavior for cumsum() of ints contrary to floats
**Example :**
df = pd.DataFrame([[np.nan,0],[0,1]])
df.groupby(0)[1].cumsum()

**out:**
0 -1
1 1
which is incorrect

df = pd.DataFrame([[np.nan,0],[0.0,1.0]])
df.groupby(0)[1].cumsum()

**out:**
0 NaN
1 1.0
which is correct

#### Problem description
pandas version 0.22.0
when the aggregation key contains nan, the cumulative aggregation of int gives a wrong result on the contrary the aggregation of float works.