Adding a column in Dataframe with a specific property in python

I have the following dataframe,

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

which looks like,

    a       b
0   [1, 2]  2
1   [2, 3]  4
2   [1]     1

Now, I want to add a column in this dataframe whose elements are that value in each list of column ‘a’ whose absolute difference with corresponding value in column ‘b’ is minimum.
i.e. I want to add a column ‘c’ in my dataframe, such that my df becomes,

   a     b  c
0 [1,2]  2  2
1 [2,3]  4  3
2 [1]    1  1

I tried using lambda function, but couldn’t do it.

>Solution :

You can iterate through the column using zip and store the index of min absolute result.

import numpy as np
import pandas as pd

df = pd.DataFrame({'a':[[1,2],[2,3],[1]],'b':[2,4,1]})
c_col = []

for x, y in zip(df['a'], df['b']):
    array = abs(np.array(x)-y)
    c_col.append(x[array.argmin(axis=0)])

df['c'] = c_col
print(df)

Output :

        a  b  c
0  [1, 2]  2  2
1  [2, 3]  4  3
2     [1]  1  1