Question

我有一个简单的代码来查找数据集中的类似行。

 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（键）

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)'

我该怎么做才能使用这段代码？如果将pandas对象转换为numpy数组很有帮助，我该怎么做？

Answer 1

将pandas数据帧转换为numpy数组：

import numpy as np
np.array(dataFrame)

Answer 2

我还不能评论Adrienne的回答所以我想补充一点，数据帧有内置方法将df转换为数组即矩阵

>>> 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]

还可以找到可以执行的重复行：

>>> 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

Answer 3

我订阅了之前的答案，但如果您想直接使用pandas个对象，访问DataFrame项目有其特殊的方法。在您的代码中，您应该说例如。

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

请参阅documentation了解更多

将panda对象转换为numpy数组

3 个答案: