使用sklearn并导入CSV时出现不可用的类型错误

时间:2014-02-02 03:42:46

标签: python-2.7 pandas machine-learning scikit-learn prediction

我正在尝试执行以下代码,但我不明白我做错了什么。代码的目的是使用Python的& sklearn的train_test_split函数将数据分区为训练和测试块。

数据(downloadable here)是各种房屋/公寓的租金数据,以及每个房屋/公寓的房产。最终,我正在尝试使用预测模型来预测租金价格(因此租金价格是目标)。这是代码:

import pandas as pd
rentdata = pd.read_csv('6000_clean.csv')

import sklearn as sk
import numpy as np
import matplotlib.pyplot as plt

from sklearn.cross_validation import train_test_split

#trying to make a all rows of the first column and b all rows of columns 2-46, i.e., a will be only target data (rent prices) and b will be the data.

a, b = rentdata[ : ,0], rentdata[ : ,1:46]

以下错误导致什么结果:

TypeError                                 Traceback (most recent call last)
<ipython-input-24-789fb8e8c2f6> in <module>()
      8 from sklearn.cross_validation import train_test_split
      9 
---> 10 a, b = rentdata[ : ,0], rentdata[ : ,1:46]
     11 

C:\Users\Nick\Anaconda\lib\site-packages\pandas\core\frame.pyc in __getitem__(self, key)
   2001             # get column
   2002             if self.columns.is_unique:
-> 2003                 return self._get_item_cache(key)
   2004 
   2005             # duplicate columns

C:\Users\Nick\Anaconda\lib\site-packages\pandas\core\generic.pyc in _get_item_cache(self, item)
    665             return cache[item]
    666         except Exception:
--> 667             values = self._data.get(item)
    668             res = self._box_item_values(item, values)
    669             cache[item] = res

C:\Users\Nick\Anaconda\lib\site-packages\pandas\core\internals.pyc in get(self, item)
   1653     def get(self, item):
   1654         if self.items.is_unique:
-> 1655             _, block = self._find_block(item)
   1656             return block.get(item)
   1657         else:

C:\Users\Nick\Anaconda\lib\site-packages\pandas\core\internals.pyc in _find_block(self, item)
   1933 
   1934     def _find_block(self, item):
-> 1935         self._check_have(item)
   1936         for i, block in enumerate(self.blocks):
   1937             if item in block:

C:\Users\Nick\Anaconda\lib\site-packages\pandas\core\internals.pyc in _check_have(self, item)
   1939 
   1940     def _check_have(self, item):
-> 1941         if item not in self.items:
   1942             raise KeyError('no item named %s' % com.pprint_thing(item))
   1943 

C:\Users\Nick\Anaconda\lib\site-packages\pandas\core\index.pyc in __contains__(self, key)
    317 
    318     def __contains__(self, key):
--> 319         hash(key)
    320         # work around some kind of odd cython bug
    321         try:

TypeError: unhashable type

您可以下载CSV以查看此处的数据:http://wikisend.com/download/776790/6000_clean.csv

1 个答案:

答案 0 :(得分:3)

我下载了您的数据并将问题行修改为:

a, b = rentdata.iloc[0], rentdata.iloc[1:46]

iloc逐行选择,请参阅文档:http://pandas.pydata.org/pandas-docs/stable/indexing.html#selection-by-position

现在选择第一行和第2-46行(请记住切片是开放式的,包括范围的开始但不是范围的结束)

请注意,您始终可以使用head选择第一行:

a, b = rentdata.head(0), rentdata.iloc[1:46]

也可以使用

In [5]:

a

Out[5]:

Monthly $ rent                                                    1150
Location                                                       alameda
# of bedrooms                                                        1
# of bathrooms                                                       1
# of square feet                                                   NaN
Latitude                                                      37.77054
Longitude                                                    -122.2509
Street address                                  1500-1598 Lincoln Lane
# more rows so trimmed for brevity here
.......

In [9]: b

Out[9]:
# too large to paste here
.....
45 rows × 46 columns