How to duplicate each row having only one column different than the previous row pandas data frame?

Question

I have a big data and I want to duplicate each row just below the original column by changing just one column value

I want to copy the previous row value in place of "same" and I want to change the last column which is the same as the c column

import numpy as np
import pandas as pd
import sys
df = pd.DataFrame([[45, 20, 'A1',   46, 20, 'A2'],
                      [45, 20 ,'B2',   46, 20, 'B1'],
                      [46, 20, 'A2',   47, 20, 'A1'],
                     [46, 20, 'B1',   47, 20, 'B2']],columns=['A','B','C','D','E','F'])
 
new_row = {"A":0,"B":0,"C":0,"D":0, "E":0,"F":0}
s = pd.Series(new_row, df.columns)
f = lambda d: d.append(s, ignore_index=True)
grp = np.arange(len(df)) // 1
df.groupby(grp, group_keys=False).apply(f).reset_index(drop=True)

input:

expected output:

Answer 1

Assuming this input:

A  B  C    D  E  F
45 20 A1   46 20 A2
45 20 B2   46 20 B1
46 20 A2   47 20 A1
46 20 B1   47 20 B2 

and the fact that you want to duplicate rows while getting the values of C for column F:

out = (pd.concat([df, df.assign(F=df['C'])])
         .sort_index(kind='stable').reset_index(drop=True)
       )

output:

    A   B   C   D   E   F
0  45  20  A1  46  20  A2
1  45  20  A1  46  20  A1
2  45  20  B2  46  20  B1
3  45  20  B2  46  20  B2
4  46  20  A2  47  20  A1
5  46  20  A2  47  20  A2
6  46  20  B1  47  20  B2
7  46  20  B1  47  20  B1