如何用熊猫将列更改为行？

Question

这是我的df：

import pandas as pd

categoria = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']
dados1 = [29.9, 71.5, 106.4, 129.2, 144.0, 176.0, 135.6, 148.5, 216.4, 194.1, 95.6, 54.4]
dados2 = [144.0, 176.0, 135.6, 148.5, 216.4, 194.1, 95.6, 54.4, 29.9, 71.5, 106.4, 129.2]

df = pd.DataFrame([dados1, dados2], columns = categoria)
print(df)
     Jan    Feb    Mar    Apr    May  ...    Aug    Sep    Oct    Nov    Dec
0   29.9   71.5  106.4  129.2  144.0  ...  148.5  216.4  194.1   95.6   54.4
1  144.0  176.0  135.6  148.5  216.4  ...   54.4   29.9   71.5  106.4  129.2

但是我想要这样的东西：

     dados1   dados2
Jan    29.9    144.0
Feb    71.5    176.0
Mar   106.4    135.6

到目前为止我尝试过的事情：

df1 = pd.pivot_table(df, index = categoria, columns = [dados1, dados2])

但是我有一个错误：

ValueError: Grouper and axis must be same length

我该怎么办？

Answer 1

IIUC

df = pd.DataFrame(zip(dados1, dados2), index = categoria)
df
         0      1
Jan   29.9  144.0
Feb   71.5  176.0
Mar  106.4  135.6
Apr  129.2  148.5
May  144.0  216.4
Jun  176.0  194.1
Jul  135.6   95.6
Aug  148.5   54.4
Sep  216.4   29.9
Oct  194.1   71.5
Nov   95.6  106.4
Dec   54.4  129.2

Answer 2

我认为您可以使用transpose（）函数并根据需要重命名列。

df=df.transpose()
df.columns=['dados1','dados2']