Question

我想计算出现在一列的每一行中的每个单词的数量（'Comment'），并将其存储在名为headlamp的数据框中的新列（'word'）中。我正在尝试使用以下代码，但是，我得到了错误。

for i in range(0,len(headlamp)):
    headlamp['word'].apply(lambda text: Counter(" ".join(headlamp['Comment'][i].astype(str)).split(" ")).items())
---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
<ipython-input-16-a0c20291b4f5> in <module>()
  1 for i in range(0,len(headlamp)):
  ----> 2     headlamp['word'].apply(lambda text: Counter("".join(headlamp['Comment'][i].astype(str)).split(" ")).items())

  C:\Users\Rafael\Anaconda2\envs\gl-env\lib\site-packages\pandas\core\frame.pyc in __getitem__(self, key)
  1995             return self._getitem_multilevel(key)
  1996         else:
  -> 1997             return self._getitem_column(key)
  1998 
  1999     def _getitem_column(self, key):

  C:\Users\Rafael\Anaconda2\envs\gl-env\lib\site-packages\pandas\core\frame.pyc in _getitem_column(self, key)
  2002         # get column
  2003         if self.columns.is_unique:
  -> 2004             return self._get_item_cache(key)
  2005 
  2006         # duplicate columns & possible reduce dimensionality

  C:\Users\Rafael\Anaconda2\envs\gl-env\lib\site-packages\pandas\core\generic.pyc in _get_item_cache(self, item)
  1348         res = cache.get(item)
  1349         if res is None:
  -> 1350             values = self._data.get(item)
   1351             res = self._box_item_values(item, values)
   1352             cache[item] = res

   C:\Users\Rafael\Anaconda2\envs\gl-env\lib\site-packages\pandas\core\internals.pyc in get(self, item, fastpath)
   3288 
   3289             if not isnull(item):
   -> 3290                 loc = self.items.get_loc(item)
   3291             else:
   3292                 indexer = np.arange(len(self.items))[isnull(self.items)]

   C:\Users\Rafael\Anaconda2\envs\gl-env\lib\site-packages\pandas\indexes\base.pyc in get_loc(self, key, method, tolerance)
   1945                 return self._engine.get_loc(key)
   1946             except KeyError:
   -> 1947                 returnself._engine.get_loc(self._maybe_cast_indexer(key))
   1948 
   1949         indexer = self.get_indexer([key], method=method, tolerance=tolerance)

   pandas\index.pyx in pandas.index.IndexEngine.get_loc (pandas\index.c:4154)()

   pandas\index.pyx in pandas.index.IndexEngine.get_loc (pandas\index.c:4018)()

   pandas\hashtable.pyx in pandas.hashtable.PyObjectHashTable.get_item (pandas\hashtable.c:12368)()

   pandas\hashtable.pyx in pandas.hashtable.PyObjectHashTable.get_item (pandas\hashtable.c:12322)()

   KeyError: 'word'

任何帮助都将非常感谢

Answer 1

你可以试试这个：

headlamp['word'] = headlamp['Comment'].apply(lambda x: len(x.split()))

示例：

headlamp = pd.DataFrame({'Comment': ['hello world','world','foo','foo and bar']}) print(headlamp) Comment 0 hello world 1 world 2 foo 3 foo and bar headlamp['word'] = headlamp['Comment'].apply(lambda x: len(x.split())) print(headlamp) Comment word 0 hello world 2 1 world 1 2 foo 1 3 foo and bar 3

Answer 2

使用most_common()方法可以实现您想要的效果。

随意使用这段代码：

import pandas as pd
from collections import Counter

df = pd.DataFrame({'Comment': ['This has has words words words that are written twice twice', 'This is a comment without repetitions', 'This comment, has ponctuations!']}, index = [0, 1, 2])

#you must create the new column before trying to assing any value
df['Words'] = ""

#counting frequencies
i = 0
for row in df['Comment']:
    df['Words'][i] = str(Counter(row.split()).most_common())
    i+=1

print df

输出：

                                             Comment  \
0  This has has words words words that are writte...   
1              This is a comment without repetitions   
2                    This comment, has ponctuations!   

                                               Words  
0  [('words', 3), ('twice', 2), ('has', 2), ('tha...  
1  [('a', 1), ('comment', 1), ('This', 1), ('is',...  
2  [('This', 1), ('comment,', 1), ('has', 1), ('p...

Python：计算列中单词的频率，并将结果存储到我的数据框中的另一列

2 个答案: