Transpose Pandas DataFrame and change the column headers to a list

Question

I have the following Pandas sub-dataframe

 col1 name1 name2 522 a 10 0.2 1021 b 72 -0.1

col1 has no duplicate. I want to transpose the dataframe and change the column header to col1 values. Ideally the output should look like

Variable a b name1 10 72 name2 0.2 -0.1

it is easy to transpose the df and label the first column as Variable

df.transpose().reset_index().rename(columns={'index':'Variable'})

the resulting DF will have indices of original DF as column headers (and they are not sorted and don't start from 1 in my data!). How can I change the rest of column names?

jezrael · Accepted Answer · 2017-11-06 14:36:39Z

Need set_index + T:

df = df.set_index('col1').T print (df) col1 a b name1 10.0 72.0 name2 0.2 -0.1 df = df.set_index('col1').T.rename_axis('Variable').rename_axis(None, 1) print (df) a b Variable name1 10.0 72.0 name2 0.2 -0.1

If need column from index:

df = df.set_index('col1').T.rename_axis('Variable').rename_axis(None, 1).reset_index() print (df) Variable a b 0 name1 10.0 72.0 1 name2 0.2 -0.1

cottontail · Accepted Answer · 2023-10-07 05:46:41Z

It's also possible to do the task with a combination of melt and pivot. The idea is to

df = df.melt('col1').pivot(index='variable', columns='col1', values='value')

or set_index and unstack twice:

df = df.set_index('col1').unstack().unstack()

If the variable column needs to be a column instead of an index, then use reset_index():

df.set_index('col1').unstack().unstack().reset_index(names='Variable').rename_axis(columns=None)

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