Pandas - convert float to int when there are NaN values in the column

Question

I'm trying to convert float numbers to int in my df column with this one liner:

df['id'] = df['id'].map(lambda x: int(x))

But some values are NaN an will throw:

ValueError: cannot convert float NaN to integer

How do I fix this?

Answer 1

NaN is itself float and can't be convert to usual int. You can use pd.Int64Dtype() for nullable integers:

# sample data:
df = pd.DataFrame({'id':[1, np.nan]})

df['id'] = df['id'].astype(pd.Int64Dtype())

Output:

     id
0     1
1  <NA>

Another option, is use apply, but then the dtype of the column will be object rather than numeric/int:

df['id'] = df['id'].apply(lambda x: x if np.isnan(x) else int(x))