Pandas Hashtable KeyError

时间:2017-05-20 12:03:26

标签: python pandas kaggle sklearn-pandas

我在Kaggle中找到了以下代码。

import re

from nltk.corpus import stopwords # Import the stop word list

def description_to_words(review_text):

    # 2. Remove non-letters        
    letters_only = re.sub("[^a-zA-Z]", " ", review_text)
    # 3. Convert to lower case, split into individual words
    words = letters_only.lower().split()
    # 4. In Python, searching a set is much faster than searching
    #   a list, so convert the stop words to a set
    stops = set(stopwords.words("english"))
    # 5. Remove stop words
    meaningful_words = [w for w in words if not w in stops]
    # 6. Join the words back into one string separated by space, 
    # and return the result.
    return( " ".join( meaningful_words ))

以上代码适用于以下函数调用

clean_review = description_to_words(df['MaterialDescription'][3] )
print(clean_review)

但是,当我尝试上述同样的事情,比如将DataFrame分配给另一个变量,如下所示,

X = df['MaterialDescription']
clean_review = description_to_words(X[3] )
print(clean_review)

我收到以下错误,这完全是荒谬的。我确信我需要在Pandas中有一些清晰度

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
C:\Anaconda\envs\tensorflow\lib\site-packages\pandas\indexes\base.py in get_loc(self, key, method, tolerance)
   2133             try:
-> 2134                 return self._engine.get_loc(key)
   2135             except KeyError:

pandas\index.pyx in pandas.index.IndexEngine.get_loc (pandas\index.c:4433)()

pandas\index.pyx in pandas.index.IndexEngine.get_loc (pandas\index.c:4279)()

pandas\src\hashtable_class_helper.pxi in pandas.hashtable.PyObjectHashTable.get_item (pandas\hashtable.c:13742)()

pandas\src\hashtable_class_helper.pxi in pandas.hashtable.PyObjectHashTable.get_item (pandas\hashtable.c:13696)()

KeyError: 3

During handling of the above exception, another exception occurred:

KeyError                                  Traceback (most recent call last)
<ipython-input-15-5c63f93c009a> in <module>()
----> 1 clean_review = description_to_words(X[3] )
      2 print(clean_review)

C:\Anaconda\envs\tensorflow\lib\site-packages\pandas\core\frame.py in __getitem__(self, key)
   2057             return self._getitem_multilevel(key)
   2058         else:
-> 2059             return self._getitem_column(key)
   2060 
   2061     def _getitem_column(self, key):

C:\Anaconda\envs\tensorflow\lib\site-packages\pandas\core\frame.py in _getitem_column(self, key)
   2064         # get column
   2065         if self.columns.is_unique:
-> 2066             return self._get_item_cache(key)
   2067 
   2068         # duplicate columns & possible reduce dimensionality

C:\Anaconda\envs\tensorflow\lib\site-packages\pandas\core\generic.py in _get_item_cache(self, item)
   1384         res = cache.get(item)
   1385         if res is None:
-> 1386             values = self._data.get(item)
   1387             res = self._box_item_values(item, values)
   1388             cache[item] = res

C:\Anaconda\envs\tensorflow\lib\site-packages\pandas\core\internals.py in get(self, item, fastpath)
   3541 
   3542             if not isnull(item):
-> 3543                 loc = self.items.get_loc(item)
   3544             else:
   3545                 indexer = np.arange(len(self.items))[isnull(self.items)]

C:\Anaconda\envs\tensorflow\lib\site-packages\pandas\indexes\base.py in get_loc(self, key, method, tolerance)
   2134                 return self._engine.get_loc(key)
   2135             except KeyError:
-> 2136                 return self._engine.get_loc(self._maybe_cast_indexer(key))
   2137 
   2138         indexer = self.get_indexer([key], method=method, tolerance=tolerance)

pandas\index.pyx in pandas.index.IndexEngine.get_loc (pandas\index.c:4433)()

pandas\index.pyx in pandas.index.IndexEngine.get_loc (pandas\index.c:4279)()

pandas\src\hashtable_class_helper.pxi in pandas.hashtable.PyObjectHashTable.get_item (pandas\hashtable.c:13742)()

pandas\src\hashtable_class_helper.pxi in pandas.hashtable.PyObjectHashTable.get_item (pandas\hashtable.c:13696)()

KeyError: 3

我也试过在pandas对象中给出切片。这会产生另一个错误

clean_review = description_to_words(X[:3] )
print(clean_review)

以下是代码

的上述2行的堆栈跟踪
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-18-f8b01af18e4b> in <module>()
----> 1 clean_review = description_to_words(X[:3] )
      2 print(clean_review)

<ipython-input-6-70647cd7caba> in description_to_words(review_text)
      6 
      7     # 2. Remove non-letters
----> 8     letters_only = re.sub("[^a-zA-Z]", " ", review_text)
      9     # 3. Convert to lower case, split into individual words
     10     words = letters_only.lower().split()

C:\Anaconda\envs\tensorflow\lib\re.py in sub(pattern, repl, string, count, flags)
    180     a callable, it's passed the match object and must return
    181     a replacement string to be used."""
--> 182     return _compile(pattern, flags).sub(repl, string, count)
    183 
    184 def subn(pattern, repl, string, count=0, flags=0):

TypeError: expected string or bytes-like object

如果有人帮助我理解,这里真正发生了什么,那将是一个很大的帮助。

2 个答案:

答案 0 :(得分:1)

以下行

X = df['MaterialDescription']
clean_review = description_to_words(X[3] )

给出python description_to_words(df['MaterialDescription'][3] )

您必须通过以下方式找到索引:

clean_review = description_to_words(df.iloc[3]['MaterialDescription'] )

答案 1 :(得分:0)

我的一个代码中遇到了类似的错误。原来,当我删除空行时,该特定索引从我的数据框中丢失了。 在这种情况下,您可以执行df.reset_index(inplace = True)并解决错误。