Python numpy数组到数据帧转换-值错误

Python numpy数组到数据帧转换-值错误,python,arrays,pandas,numpy,dataframe,Python,Arrays,Pandas,Numpy,Dataframe,我有一个名为“data”的numpy数组- array([['ksr-usconeng101', 'C', '632.3', '1'], ['ksr-usconeng101', 'D', '242.9', '2'], ['ksr-usconeng158', 'C', '1044.5', '3'], ['ksr-usconeng158', 'D', '2771.2', '4'], ['ksr-usconeng158', 'G', '7.3',

我有一个名为“data”的numpy数组-

array([['ksr-usconeng101', 'C', '632.3', '1'],
       ['ksr-usconeng101', 'D', '242.9', '2'],
       ['ksr-usconeng158', 'C', '1044.5', '3'],
       ['ksr-usconeng158', 'D', '2771.2', '4'],
       ['ksr-usconeng158', 'G', '7.3', '5'],
       ['ksr-usconeng163', 'C', '1597.0', '6'],
       ['ksr-usconeng163', 'D', '1676.3', '7'],
       ['server', 'drive', 'size', '']],
      dtype='<U15')
数据-

data[0:-1,0:3]
Out[145]: 
array([['ksr-usconeng101', 'C', '632.3'],
       ['ksr-usconeng101', 'D', '242.9'],
       ['ksr-usconeng158', 'C', '1044.5'],
       ['ksr-usconeng158', 'D', '2771.2'],
       ['ksr-usconeng158', 'G', '7.3'],
       ['ksr-usconeng163', 'C', '1597.0'],
       ['ksr-usconeng163', 'D', '1676.3']],
      dtype='<U15')
请说明我遗漏了什么

试试这个

pd.DataFrame(data=data[0:-1,0:3],
                   index = data[0:-1,-1],
                   columns = data[-1:, 0:-1].tolist())

列需要为1D:

df = pd.DataFrame(data=data[:-1,:3],
                  index=data[:-1,-1],
                  columns=data[-1, :-1])
print(df)
输出:

         server drive    size
1  ksr-usconeng101     C   632.3
2  ksr-usconeng101     D   242.9
3  ksr-usconeng158     C  1044.5
4  ksr-usconeng158     D  2771.2
5  ksr-usconeng158     G     7.3
6  ksr-usconeng163     C  1597.0
7  ksr-usconeng163     D  1676.3
你有:

>>> data[-1:, 0:-1].shape
(1, 3)
但需要:

>>> data[-1, :-1].shape
(3,)
df = pd.DataFrame(data=data[:-1,:3],
                  index=data[:-1,-1],
                  columns=data[-1, :-1])
print(df)
         server drive    size
1  ksr-usconeng101     C   632.3
2  ksr-usconeng101     D   242.9
3  ksr-usconeng158     C  1044.5
4  ksr-usconeng158     D  2771.2
5  ksr-usconeng158     G     7.3
6  ksr-usconeng163     C  1597.0
7  ksr-usconeng163     D  1676.3
>>> data[-1:, 0:-1].shape
(1, 3)
>>> data[-1, :-1].shape
(3,)
import  numpy as np, pandas as pd

df = pd.DataFrame(data[0:7, 0:3].flatten().reshape(7,3),
       columns = ["a", "b", "c"])

            a           b     c
0   ksr-usconeng101     C   632.3
1   ksr-usconeng101     D   242.9
2   ksr-usconeng158     C   1044.5
3   ksr-usconeng158     D   2771.2
4   ksr-usconeng158     G   7.3
5   ksr-usconeng163     C   1597.0
6   ksr-usconeng163     D   1676.3