如何读取.CSV文件的特定行/列并将它们存储为numpy矩阵？

Question

我有一个.CSV文件，内容如下：

DATE    OPEN    HIGH    LOW CLOSE   PRICE   YCLOSE  VOL TICKS
13950309    1000000 1000000 1000000 1000000 1000000 1000000 2100000 74
13950326    1050000 1050010 1050000 1050001 1050000 1000000 1648    5
13950329    1030200 1060000 1030200 1044474 1042265 1050001 28469   108
13950330    1040001 1049999 1040001 1042303 1045001 1044474 6518    10
13950331    1049800 1050000 1048600 1048787 1050000 1042303 277 11
13950401    1059973 1059974 1052000 1053807 1055000 1048787 916 17
13950402    1050000 1054498 1043009 1048173 1043009 1053807 2098    29
13950405    1045678 1049989 1040002 1049961 1049979 1048173 28098   14

例如，不需要DATE列，或第一行（包含字符串）。所以我喜欢从第2行到第25行，第2列到结束列，然后将数据存储为numpy矩阵。我怎样才能做到这一点？

编辑：我尝试了这个代码，如其中一个答案所示：

import pandas as pd
import numpy as np

data = pd.read_csv("C:/Users/m/Desktop/python/IRB3MAIZ9936-a.csv", sep="\s")
del data['DATE'] 
np.array(data.values)

但我得到了这个结果：

C:\Users\m\Desktop\python\read_csv.py:4: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.
  data = pd.read_csv("C:/Users/m/Desktop/python/IRB3MAIZ9936-a.csv", sep="\s")
Traceback (most recent call last):
  File "C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexes\base.py", line 3078, in get_loc
    return self._engine.get_loc(key)
  File "pandas\_libs\index.pyx", line 140, in pandas._libs.index.IndexEngine.get_loc
  File "pandas\_libs\index.pyx", line 162, in pandas._libs.index.IndexEngine.get_loc
  File "pandas\_libs\hashtable_class_helper.pxi", line 1492, in pandas._libs.hashtable.PyObjectHashTable.get_item
  File "pandas\_libs\hashtable_class_helper.pxi", line 1500, in pandas._libs.hashtable.PyObjectHashTable.get_item
KeyError: 'DATE'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "C:\Users\m\Desktop\python\read_csv.py", line 6, in <module>
    del data['DATE']
  File "C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\generic.py", line 2743, in __delitem__
    self._data.delete(key)
  File "C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\internals.py", line 4174, in delete
    indexer = self.items.get_loc(item)
  File "C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexes\base.py", line 3080, in get_loc
    return self._engine.get_loc(self._maybe_cast_indexer(key))
  File "pandas\_libs\index.pyx", line 140, in pandas._libs.index.IndexEngine.get_loc
  File "pandas\_libs\index.pyx", line 162, in pandas._libs.index.IndexEngine.get_loc
  File "pandas\_libs\hashtable_class_helper.pxi", line 1492, in pandas._libs.hashtable.PyObjectHashTable.get_item
  File "pandas\_libs\hashtable_class_helper.pxi", line 1500, in pandas._libs.hashtable.PyObjectHashTable.get_item
KeyError: 'DATE'
[Finished in 1.7s with exit code 1]
[shell_cmd: python -u "C:\Users\m\Desktop\python\read_csv.py"]
[dir: C:\Users\m\Desktop\python]
[path: C:\ProgramData\Anaconda3;C:\ProgramData\Anaconda3\Library\mingw-w64\bin;C:\ProgramData\Anaconda3\Library\usr\bin;C:\ProgramData\Anaconda3\Library\bin;C:\ProgramData\Anaconda3\Scripts;C:\Program Files (x86)\Common Files\Oracle\Java\javapath;C:\Windows\system32;C:\Windows;C:\Windows\System32\Wbem;C:\Windows\System32\WindowsPowerShell\v1.0\;C:\Windows\System32\OpenSSH\;C:\Program Files (x86)\NVIDIA Corporation\PhysX\Common;C:\mingw64\bin;D:\cmake-3.11.3-win64-x64\cmake-3.11.3-win64-x64\bin;C:\opencv\build\install\x64\mingw\bin;C:\Program Files\nodejs\;C:\Program Files\MATLAB\R2018b\runtime\win64;C:\Program Files\MATLAB\R2018b\bin;C:\Program Files\Git\cmd;C:\Program Files\Microsoft SQL Server\130\Tools\Binn\;C:\Program Files\dotnet\;C:\Users\m\AppData\Local\Microsoft\WindowsApps;C:\Users\m\AppData\Roaming\npm;C:\Users\m\AppData\Local\Programs\Microsoft VS Code\bin]

Answer 1

这应该会让您了解解决问题的方法。

import pandas as pd
import numpy as np

data = pd.read_csv("/Users/DHarun/Desktop/STD_MASTER/F_Bildverarbeitung/aim2/iaai/stack/xyz.csv", sep="\s")

del data['DATE']

np.array(data.values)

输出：

array([[1000000, 1000000, 1000000, 1000000, 1000000, 1000000, 2100000,
             74],
       [1050000, 1050010, 1050000, 1050001, 1050000, 1000000,    1648,
              5],
       [1030200, 1060000, 1030200, 1044474, 1042265, 1050001,   28469,
            108],
       [1040001, 1049999, 1040001, 1042303, 1045001, 1044474,    6518,
             10],
       [1049800, 1050000, 1048600, 1048787, 1050000, 1042303,     277,
             11],
       [1059973, 1059974, 1052000, 1053807, 1055000, 1048787,     916,
             17],
       [1050000, 1054498, 1043009, 1048173, 1043009, 1053807,    2098,
             29],
       [1045678, 1049989, 1040002, 1049961, 1049979, 1048173,   28098,
             14],
       [1050001, 1053000, 1046700, 1049473, 1046700, 1049961,    5498,
             33]])

Answer 2

只需使用csv模块处理文件，跳过第一行和第一列。代码可以简单如下：

with open('file.csv') as fd:
    next(fd)                                  # skip initial line
    rd = csv.reader(fd, delimiter = ' ', skipinitialspace = True)
    arr =  np.array([[int(i) for i in row[1:]] for row in rd])  # skip initial column

print(repr(arr))

按预期给出：

array([[1000000, 1000000, 1000000, 1000000, 1000000, 1000000, 2100000,
             74],
       [1050000, 1050010, 1050000, 1050001, 1050000, 1000000,    1648,
              5],
       [1030200, 1060000, 1030200, 1044474, 1042265, 1050001,   28469,
            108],
       [1040001, 1049999, 1040001, 1042303, 1045001, 1044474,    6518,
             10],
       [1049800, 1050000, 1048600, 1048787, 1050000, 1042303,     277,
             11],
       [1059973, 1059974, 1052000, 1053807, 1055000, 1048787,     916,
             17],
       [1050000, 1054498, 1043009, 1048173, 1043009, 1053807,    2098,
             29],
       [1045678, 1049989, 1040002, 1049961, 1049979, 1048173,   28098,
             14]])