Sometimes a pandas DataFrame will have mixed data types. You're able to replace all null values with None (instead of default np.nan)
To do this use pd.DataFrame.where
""" Uses df value when condition is met, otherwise uses None """
df.where(df.notnull(), None)| 1 | 2 | 3 | 4 | |
|---|---|---|---|---|
| 0 | 1 | two | None | 4 |