Convert Pandas column containing NaNs to dtype `int`

In version 0.24.+ pandas has gained the ability to hold integer dtypes with missing values.

Nullable Integer Data Type.

Pandas can represent integer data with possibly missing values using arrays.IntegerArray. This is an extension types implemented within pandas. It is not the default dtype for integers, and will not be inferred; you must explicitly pass the dtype into array() or Series:

arr = pd.array([1, 2, np.nan], dtype=pd.Int64Dtype())
pd.Series(arr)

0      1
1      2
2    NaN
dtype: Int64

For convert column to nullable integers use:

df['myCol'] = df['myCol'].astype('Int64')