CODEWITHSUNDEEP
pythonpandasdataframe
theUnknown
theUnknown

Reputation: 283

Dataframe convert header row to row pandas

have a df with values

df:

165  156  1    test    greater 56gsa
-------------------------------------
spin 201  2    normal  lesser  12asgs
pine 202  3    fast    greater 5sasgs

required output:

0     1   2     3        4       5
-------------------------------------
165  156  1    test    greater 56gsa
spin 201  2    normal  lesser  12asgs
pine 202  3    fast    greater 5sasgs

Upvotes: 17

Views: 19306

Answers (3)

jezrael
jezrael

Reputation: 862511

If DataFrame is created from file then header=None parameter is your friend:

df = pd.read_csv(file, header=None)

pandas >= 2.0:

If not then convert column to one row DataFrame and concatenate (append not working anymore) to original data:

df = pd.concat([df.columns.to_frame().T, df])
df.columns = range(len(df.columns))
print (df)
      0    1  2       3        4       5
0   165  156  1    test  greater   56gsa
1  spin  201  2  normal   lesser  12asgs
2  pine  202  3    fast  greater  5sasgs

pandas < 2.0 (original answer):

If not then convert column to one row DataFrame and DataFrame.append to original data:

df = df.columns.to_frame().T.append(df, ignore_index=True)
df.columns = range(len(df.columns))
print (df)
      0    1  2       3        4       5
0   165  156  1    test  greater   56gsa
1  spin  201  2  normal   lesser  12asgs
2  pine  202  3    fast  greater  5sasgs

Upvotes: 19

U13-Forward
U13-Forward

Reputation: 71570

Try using reset_index:

print(df.T.reset_index().T)

For resetting and dropping original columns:

print(df.T.reset_index(drop=True).T)

Upvotes: 12

Shibiraj
Shibiraj

Reputation: 769

Try the code below,

df.loc[len(df)] = df.columns
df.columns = range(len(df.columns))
df

Upvotes: 1

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