Parsing unstructured data frame python

Question

I have a unstructured Data frame in python which has two variables X and Y. Every observation in X is array and Y is class variable which looks like

             X           Y
      1. [ [ 1,2] ]      a
      2. [ [ 2,3] ]      b

I want to Have it like

 1.   1    2     a
 2.   2    3     b 

I have tried option from numpy to data frame but not working 

Answer 1

import pandas as pd

# Create the initial DataFrame
data = {'X': [[[1, 2]], [[2, 3]]], 'Y': ['a', 'b']}
df = pd.DataFrame(data)

# Transform the DataFrame
df_transformed = pd.DataFrame(df['X'].apply(lambda x: x[0]).tolist(), columns=['X1', 'X2'])
df_transformed['Y'] = df['Y']

# Display the transformed DataFrame
print(df_transformed)

Answer 2

import pandas as pd
df=pd.DataFrame({'X':[[[1,2]],[[3,4]]],'Y':['a','b']})

def expand(x):
     x=x['X'][0]
     return x
df['X1'],df['X2']=zip(*df.apply(expand,axis=1))
df=df.drop(['X'],axis=1)

Explanation: using zip() with apply(axis=1), we can generate 2 new columns using 'X'.

For many elements in 'X':

import pandas as pd
df=pd.DataFrame({'X':[[[1,2,3,4]],[[3,4,5,6]]],'Y':['a','b']})

def expand(x):
    new_columns=x['X'][0]
    return new_columns+[x['Y']]
df=pd.DataFrame(zip(*df.apply(expand,axis=1))).T

Now, 'X' can have any number of elements. I used 'X' with 4 elements for example.