Convert column to row in Python Pandas

You need set_index with transpose by T:

print (df.set_index('fruits').T)fruits     apples  grapes  figsnumFruits      10      20    15

If need rename columns, it is a bit complicated:

print (df.rename(columns={'numFruits':'Market 1 Order'})         .set_index('fruits')         .rename_axis(None).T)                apples  grapes  figsMarket 1 Order      10      20    15

Another faster solution is use numpy.ndarray.reshape:

print (pd.DataFrame(df.numFruits.values.reshape(1,-1),                     index=['Market 1 Order'],                     columns=df.fruits.values))                apples  grapes  figsMarket 1 Order      10      20    15

Timings:

#[30000 rows x 2 columns] df = pd.concat([df]*10000).reset_index(drop=True)    print (df)In [55]: %timeit (pd.DataFrame([df.numFruits.values], ['Market 1 Order'], df.fruits.values))1 loop, best of 3: 2.4 s per loopIn [56]: %timeit (pd.DataFrame(df.numFruits.values.reshape(1,-1), index=['Market 1 Order'], columns=df.fruits.values))The slowest run took 5.64 times longer than the fastest. This could mean that an intermediate result is being cached.1000 loops, best of 3: 424 µs per loopIn [57]: %timeit (df.rename(columns={'numFruits':'Market 1 Order'}).set_index('fruits').rename_axis(None).T)100 loops, best of 3: 1.94 ms per loop

pd.DataFrame([df.numFruits.values], ['Market 1 Order'], df.fruits.values)                apples  grapes  figsMarket 1 Order      10      20    15

Refer to jezrael's enhancement of this concept. df.numFruits.values.reshape(1, -1) is more efficient.

You can use transpose api of pandas as follow:

df.transpose()

Considering df as your pandas dataframe