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