Stop Pandas from converting int to float
If you set dtype=object
, your series will be able to contain arbitrary data types:
df["int"] = pd.Series([], dtype=object)
df["str"] = pd.Series([], dtype=str)
df.loc[0] = [0, "zero"]
print(df)
print()
df.loc[1] = [1, None]
print(df)
int str
0 0 zero
1 NaN NaN
int str
0 0 zero
1 1 None
As of pandas 1.0.0 I believe you have another option, which is to first use convert_dtypes. This converts the dataframe columns to dtypes that support pd.NA, avoiding the issues with NaN/None.
...
df = df.convert_dtypes()
df.loc[1] = [1, None]
print(df)
# int str
# 0 0 zero
# 1 1 NaN