在 Python Pandas 中将列转换为行
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Convert column to row in Python Pandas
提问by Reise45
I have the following Python pandas dataframe:
我有以下 Python 熊猫数据框：
fruits | numFruits
---------------------
0 | apples | 10
1 | grapes | 20
2 | figs | 15
I want:
我想要：
apples | grapes | figs
-----------------------------------------
Market 1 Order | 10 | 20 | 15
I have looked at pivot(), pivot_table(), Transpose and unstack() and none of them seem to give me this. Pandas newbie, so all help appreciated.
我看过pivot()、pivot_table()、Transpose和unstack()，但似乎没有一个给我这个。熊猫新手，所以感谢所有帮助。
回答by jezrael
You need set_indexwith transpose by T:
print (df.set_index('fruits').T)
fruits apples grapes figs
numFruits 10 20 15
If need rename columns, it is a bit complicated:
如果需要重命名列，有点复杂：
print (df.rename(columns={'numFruits':'Market 1 Order'})
.set_index('fruits')
.rename_axis(None).T)
apples grapes figs
Market 1 Order 10 20 15
Another faster solution is use numpy.ndarray.reshape:
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 figs
Market 1 Order 10 20 15
Timings:
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 loop
In [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 loop
In [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
回答by piRSquared
pd.DataFrame([df.numFruits.values], ['Market 1 Order'], df.fruits.values)
apples grapes figs
Market 1 Order 10 20 15
Refer to jezrael's enhancement of this concept. df.numFruits.values.reshape(1, -1)is more efficient.
参考 jezrael 对这个概念的增强。 df.numFruits.values.reshape(1, -1)效率更高。
回答by Akash Desarda
You can use transpose api of pandas as follow:
您可以使用熊猫的转置 api 如下：
df.transpose()
Considering df as your pandas dataframe
将 df 视为您的熊猫数据框
