Conversion of hexadecimal value represented as string into int in column in dataframe

I am working on a dataset where two of its attributes sport and dport have hexadecimal values such as 'Ox0303' and 'Ox5000' along with integer values. The datatype of these attributes is object type. When I am replacing these hexadecimal values with their respective decimal value in the following way:

df1['sport']= df1['sport'].replace(to_replace='Ox0303',value = 771, inplace=True)  
df1['sport']= df1['sport'].replace(to_replace='-1',value = 0, inplace=True)

it is setting the value to None in the dataframe.

sport and dport values after replacing values:

I want to set dtype of these columns as int and to replace hexadecimal values with their respective decimal values. Pls help

Consider this dataframe:

          saddr   sport        daddr dport
0   192.168.1.1  0x0303  192.168.1.1    -1
1  192.168.1.10  0x0301  192.168.1.2  0xFF
2  192.168.1.20    0x03  192.168.1.3  0x01

The values in sport and dport columns are strings. To convert them to integers you can do:

from ast import literal_eval

df["dport"] = df["dport"].apply(literal_eval)
df["sport"] = df["sport"].apply(literal_eval)

print(df)

Prints:

          saddr  sport        daddr  dport
0   192.168.1.1    771  192.168.1.1     -1
1  192.168.1.10    769  192.168.1.2    255
2  192.168.1.20      3  192.168.1.3      1