Convert input dataset given in hex addresses to int

Question

I have created an LSTM Neural Network which take as input the following format in an .csv file

sinewave
0.841470985
0.873736397
0.90255357
0.927808777
0.949402346
0.967249058
0.98127848
0.991435244

How can I write some code so it can take as input hex addresses and convert them to int ?

eg the following .xlsx file containing 400.000 samples

0xbfb22b18
0xbfb22b14
0xbfb22b10
0xbfb22b0c
0xbfb22b18
0xbfb22b14
0xbfb22b10
0xbfb22b0c
0xbfb22b18
0xbfb22b14
0xbfb22b10
0xbfb22b0c

Answer 1

Add train_data 1st

import pandas as pd

df = pd.read_excel('data.xlsx', index_col=None, names=['train_data'])
df['train_data'] = df['train_data'].apply(lambda x: int(x, 16))
df.to_csv('data.csv', index=False)