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将熊猫对象转换为 numpy 数组

热度:150   发布时间:2023-06-14 08:57:42.0

我有一个简单的代码来查找数据集中的相似行。

 h=0
count=0
#227690
deletedIndexes=np.zeros((143,))
len(data)
for i in np.arange(len(data)):
    if(data[i-1,2]==data[i,2]):
        similarIndexes[h]=int(i)
        h=h+1        
        count=count+1
        print("similar found in -->", i," there are--->", count)

当数据是 numpy.ndarray 时它可以正常工作但是如果数据是熊猫对象,我会给出以下错误:

Traceback (most recent call last):
File "<stdin>", line 1, in <module>
 File "<stdin>", line 7, in smilarData
  File "/usr/lib/python2.7/dist-packages/pandas/core/frame.py", line 1658, in __getitem__
return self._getitem_column(key)
  File "/usr/lib/python2.7/dist-packages/pandas/core/frame.py", line 1665, in _getitem_column

返回 self._get_item_cache(key)

File "/usr/lib/python2.7/dist-packages/pandas/core/generic.py", line 1005, in _get_item_cache
values = self._data.get(item)



File "/usr/lib/python2.7/dist-packages/pandas/core/internals.py", line 2874, in get
_, block = self._find_block(item)



File "/usr/lib/python2.7/dist-packages/pandas/core/internals.py", line 3186, in _find_block
self._check_have(item)



 File "/usr/lib/python2.7/dist-packages/pandas/core/internals.py", line 3193, in _check_have


 raise KeyError('no item named %s' % com.pprint_thing(item))
KeyError: u'no item named (-1, 2)'

我应该怎么做才能使用此代码? 如果将 pandas 对象转换为 numpy 数组有帮助,我该怎么做?

要将 Pandas 数据帧转换为 numpy 数组:

import numpy as np
np.array(dataFrame)

我还不能对 Adrienne 的回答发表评论,所以我想补充一点,数据帧已经内置了将 df 转换为数组即矩阵的方法

>>> df = pd.DataFrame({"a":range(5),"b":range(5,10)})
>>> df
   a  b
0  0  5
1  1  6
2  2  7
3  3  8
4  4  9
>>> mat = df.as_matrix()
array([[0, 5],
       [1, 6],
       [2, 7],
       [3, 8],
       [4, 9]])
>>>col = [x[0] for x in mat] # to get certain columns
>>> col
[0, 1, 2, 3, 4]

还可以找到重复的行:

>>> df2
   a  b
0  0  5
1  1  6
2  2  7
3  3  8
4  4  9
5  0  5
>>> df2[df2.duplicated()]
   a  b
5  0  5

我同意前面的答案,但如果你想直接与工作pandas对象,访问数据帧的项目有它自己的特殊方式。 在您的代码中,您应该说例如

if(data.iloc[i-1,2]==data.iloc[i,2]):

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