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I have to transpose a dataframe to get the desirable result. I need help.

Example:

df:

    filter filter_value      columns user_id   password api_name
0   kol_id       101152       kol_id  vmani4  abede1234      KOL
1  thrc_nm          VIR       jnj_id  vmani4  abede1234      KOL
2   jnj_id      7124166  kol_full_nm  vmani4  abede1234      KOL
3                            thrc_cd  vmani4  abede1234      KOL

I filter out two columns from the above dataframe:

df1 = df[['filter', 'filter_value']]

df1:

    filter    filter_value      
0   kol_id       101152       
1   thrc_nm      VIR       
2   jnj_id       7124166  
3                      

After transpose I am getting below dataframe:

                   0        1        2 3
filter        kol_id  thrc_nm   jnj_id
filter_value  101152      VIR  7124166

but i want to Remove the index label and column label both.

df_final:

kol_id    thrc_nm     jnj_id
101152    VIR         7124166
ashmita
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1 Answers1

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Pandas Transpose will do what you need. Assuming the below is in a dataframe: df

filter      filter_value
0   kol_id       101152
1  thrc_nm          VIR
2   jnj_id      7124166

df = df.transpose().reset_index(drop=True)

print(df.to_string(index=False, header=False))

Output:

kol_id  thrc_nm   jnj_id
 101152      VIR  7124166

EDIT: updated based on comment from O/P

David Warren
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