[FIXED] Panda astype not converting column to int even when using errors=ignore

Issue

I have the following DF

    ID
0   1.0
1   555555.0
2   NaN
3   200.0

When I try to convert the ID column to Int64 I got the following error:

Cannot convert non-finite values (NA or inf) to integer

I've used the following code to solve this problem:

df["ID"] = df["ID"].astype('int64', errors='ignore')

Although, when I use the above code my ID column persists with float64 type.

Any tip to solve this problem?

Solution

Use pd.Int64DType64 instead of np.int64:

df['ID'] = df['ID'].fillna(pd.NA).astype(pd.Int64Dtype())

Output:

>>> df
       ID
0       1
1  555555
2    <NA>
3     200

>>> df['ID'].dtype
Int64Dtype()

>>> df['ID'] + 10
0        11
1    555565
2      <NA>
3       210
Name: ID, dtype: Int64

>>> print(df.to_csv(index=False))
ID
1
555555
""
200

Answered By - Corralien