Reviews Label
0 Bromwell High is a cartoon comedy. It ran at t... Positive
1 Homelessness (or Houselessness as George Carli... Positive
2 Brilliant over-acting by Lesley Ann Warren. Be... Positive
The above one is my data frame with columns: Reviews and Label When I excecuted the code below : `
nltk.download('stopwords') This is used to update stop words.
from nltk.corpus import stopwords
stop = stopwords.words('english')
final_without_stopwords = final[['Reviews','Label']].apply(lambda x: ' '.join([word for word in x.split() if word not in (stop)])).str.replace('[^\w\s]','')
print(final_without_stopwords)`
Result:
KeyError Traceback (most recent call last)
~\Anaconda3\lib\site-packages\pandas\core\indexes\base.py in get_loc(self, key, method, tolerance)
3077 try:
-> 3078 return self._engine.get_loc(key)
3079 except KeyError:
pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_loc()
pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_loc()
pandas\_libs\hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()
pandas\_libs\hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()
KeyError: ('Reviews', 'Label')
During handling of the above exception, another exception occurred:
KeyError Traceback (most recent call last)
<ipython-input-52-cb4ca290db84> in <module>()
5 #final['Reviews'].apply(lambda x: ' '.join([word for word in x.split() if word not in (stop_words)]))
6
----> 7 final_without_stopwords = final['Reviews','Label'].apply(lambda x: ' '.join([word for word in x.split() if word not in (stop)])).str.replace('[^\w\s]','')
8 print(final_without_stopwords)
~\Anaconda3\lib\site-packages\pandas\core\frame.py in __getitem__(self, key)
2686 return self._getitem_multilevel(key)
2687 else:
-> 2688 return self._getitem_column(key)
2689
2690 def _getitem_column(self, key):
~\Anaconda3\lib\site-packages\pandas\core\frame.py in _getitem_column(self, key)
2693 # get column
2694 if self.columns.is_unique:
-> 2695 return self._get_item_cache(key)
2696
2697 # duplicate columns & possible reduce dimensionality
~\Anaconda3\lib\site-packages\pandas\core\generic.py in _get_item_cache(self, item)
2487 res = cache.get(item)
2488 if res is None:
-> 2489 values = self._data.get(item)
2490 res = self._box_item_values(item, values)
2491 cache[item] = res
~\Anaconda3\lib\site-packages\pandas\core\internals.py in get(self, item, fastpath)
4113
4114 if not isna(item):
-> 4115 loc = self.items.get_loc(item)
4116 else:
4117 indexer = np.arange(len(self.items))[isna(self.items)]
~\Anaconda3\lib\site-packages\pandas\core\indexes\base.py in get_loc(self, key, method, tolerance)
3078 return self._engine.get_loc(key)
3079 except KeyError:
-> 3080 return self._engine.get_loc(self._maybe_cast_indexer(key))
3081
3082 indexer = self.get_indexer([key], method=method, tolerance=tolerance)
pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_loc()
pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_loc()
pandas\_libs\hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()
pandas\_libs\hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()
KeyError: ('Reviews', 'Label')
enter code here
**
Actually I want to apply stop words to my data frame which only has two columns. When I excecuted this code with single column (Reviews) it worked well but when I excecuted with two columns (Reviews & Label) it is showing some error. Any suggestions how to handle this code with both columns.
**
If you want to apply a function elementwise to the dataframe, use applymap:
A simplified example:
import pandas as pd
stop = set(['a','the','i','is'])
df = pd.DataFrame( {'sentence1':['i am a boy','i am a girl'],
'sentence2':['Bromwell High is a cartoon comedy','i am a girl']})
df[['sentence1','sentence2']].applymap(lambda x: ' '.join(i for i in x.split() if i not in stop))
sentence1 sentence2
0 am boy Bromwell High cartoon comedy
1 am girl am girl
If you want to reassign the values without stopwords into your dataframe, use:
df[['sentence1','sentence2']] = df[['sentence1','sentence2']].applymap(lambda x: ' '.join(i for i in x.split() if i not in stop))