您需要
set_index通过转置
T：
print (df.set_index('fruits').T)fruits apples grapes figsnumFruits 10 20 15如果需要重命名列，则有点复杂：
print (df.rename(columns={'numFruits':'Market 1 Order'}) .set_index('fruits') .rename_axis(None).T) apples grapes figsMarket 1 Order 10 20 15另一个更快的解决方案是使用
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
时间 ：
#[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
