How to append two rows from dataframe in a single row?

I have dataframe like below:

import pandas as pd

df = pd.DataFrame.from_dict(
    {
        'Name': ['Jenny', 'Matt', 'Jenny',  'Matt', 'Jenny',  'Matt', 'Jenny', 'Matt'],
        'Year': [2020, 2021, 2022, 2020, 2021, 2022, 2020, 2021],
        'Income': [10000, 11000, 9000, 12000, 13000, 11000, 14000, 15000],
        'Gender': ['F', 'M', 'F', 'M', 'F', 'M', 'F', 'M']
    }
)
print(df)

Output:

     Name  Year  Income Gender
0  Jenny  2020   10000      F
1   Matt  2021   11000      M
2  Jenny  2022    9000      F
3   Matt  2020   12000      M
4  Jenny  2021   13000      F
5   Matt  2022   11000      M
6  Jenny  2020   14000      F
7   Matt  2021   15000      M

i want to append two rows into single row by using Gender (both F and M should be in one row). i dont bother on increasing the columns

My expected output should be:

 Name  Year  Income Gender  Name1  Year1  Income1 Gender1
Jenny  2020   10000      F Matt  2021   11000      M
Jenny  2022    9000      F Matt  2020   12000      M
Jenny  2021   13000      F Matt  2022   11000      M
Jenny  2020   14000      F Matt  2021   15000      M

Any suggestions how to do this would be helpful.

Answer

Split the dataframe into two dataframes (one for Gender = 'F' and one for Gender = 'M') and concatenate them:

df1 = df[df.Gender == 'F'].reset_index(drop=True)
df2 = df[df.Gender == 'M'].reset_index(drop=True)
df2.columns = [i + '1' for i in df.columns]

result = pd.concat([df1, df2], axis=1)

print(result)

Output:

    Name  Year  Income Gender Name1  Year1  Income1 Gender1
0  Jenny  2020   10000      F  Matt   2021    11000       M
1  Jenny  2022    9000      F  Matt   2020    12000       M
2  Jenny  2021   13000      F  Matt   2022    11000       M
3  Jenny  2020   14000      F  Matt   2021    15000       M