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how to remove common words from a column in pandas? [duplicate]

1

This question already has an answer here:

• 
  Python remove stop words from pandas dataframe
  
  3 answers
  
  

Value counts of words

How do I remove common words like 'to','and','from','this'. I am only interested in keeping the words like 'AI','Data','Learning','Machine','Artificial'.

python pandas

share|improve this question

asked 20 hours ago

bhola prasadbhola prasad

82

New contributor

bhola prasad is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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marked as duplicate by Nihal, anky_91, smci, Community♦ 19 hours ago

This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  this answer stackoverflow.com/a/43407993/7053679
  
  – Nihal
  20 hours ago
  

  
  
  
  

add a comment | 

1

This question already has an answer here:

• 
  Python remove stop words from pandas dataframe
  
  3 answers
  
  

Value counts of words

How do I remove common words like 'to','and','from','this'. I am only interested in keeping the words like 'AI','Data','Learning','Machine','Artificial'.

python pandas

share|improve this question

asked 20 hours ago

bhola prasadbhola prasad

82

New contributor

bhola prasad is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

marked as duplicate by Nihal, anky_91, smci, Community♦ 19 hours ago

This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  this answer stackoverflow.com/a/43407993/7053679
  
  – Nihal
  20 hours ago
  

  
  
  
  

add a comment | 

This question already has an answer here:

• 
  Python remove stop words from pandas dataframe
  
  3 answers
  
  

Value counts of words

How do I remove common words like 'to','and','from','this'. I am only interested in keeping the words like 'AI','Data','Learning','Machine','Artificial'.

python pandas

share|improve this question

asked 20 hours ago

bhola prasadbhola prasad

82

New contributor

bhola prasad is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

share|improve this question

asked 20 hours ago

bhola prasadbhola prasad

82

New contributor

bhola prasad is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

share|improve this question

asked 20 hours ago

bhola prasadbhola prasad

82

New contributor

bhola prasad is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

asked 20 hours ago

bhola prasadbhola prasad

82

New contributor

bhola prasad is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

asked 20 hours ago

bhola prasadbhola prasad

82

1 Answer
1

active

oldest

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2

I think what you want to remove are the stopwords like 'to','the' etc. nltk has a predefined list of stop words:

from nltk.corpus import stopwords
stop_words = stopwords.words('english')
stop_words

['i',
 'me',
 'my',
 'myself',
 'we',
 'our',
 'ours',
 'ourselves',
 'you',...

You can use np.where to replace the stopwords with np.nan

title_analysis['new_col'] = np.where(title_analysis['words'].str.contains(stopwords), np.nan, title_analysis['words'])

Then do value_counts()

title_analysis['new_col'].value_counts()

If you have your own set of words that you want to ignore, just replace stop_words with your list of words.

share|improve this answer

answered 19 hours ago

Mohit MotwaniMohit Motwani

1,9001623

add a comment | 

2

I think what you want to remove are the stopwords like 'to','the' etc. nltk has a predefined list of stop words:

from nltk.corpus import stopwords
stop_words = stopwords.words('english')
stop_words

['i',
 'me',
 'my',
 'myself',
 'we',
 'our',
 'ours',
 'ourselves',
 'you',...

You can use np.where to replace the stopwords with np.nan

title_analysis['new_col'] = np.where(title_analysis['words'].str.contains(stopwords), np.nan, title_analysis['words'])

Then do value_counts()

title_analysis['new_col'].value_counts()

If you have your own set of words that you want to ignore, just replace stop_words with your list of words.

share|improve this answer

answered 19 hours ago

Mohit MotwaniMohit Motwani

1,9001623

add a comment | 

2

I think what you want to remove are the stopwords like 'to','the' etc. nltk has a predefined list of stop words:

from nltk.corpus import stopwords
stop_words = stopwords.words('english')
stop_words

['i',
 'me',
 'my',
 'myself',
 'we',
 'our',
 'ours',
 'ourselves',
 'you',...

You can use np.where to replace the stopwords with np.nan

title_analysis['new_col'] = np.where(title_analysis['words'].str.contains(stopwords), np.nan, title_analysis['words'])

Then do value_counts()

title_analysis['new_col'].value_counts()

If you have your own set of words that you want to ignore, just replace stop_words with your list of words.

share|improve this answer

answered 19 hours ago

Mohit MotwaniMohit Motwani

1,9001623

add a comment | 

I think what you want to remove are the stopwords like 'to','the' etc. nltk has a predefined list of stop words:

from nltk.corpus import stopwords
stop_words = stopwords.words('english')
stop_words

['i',
 'me',
 'my',
 'myself',
 'we',
 'our',
 'ours',
 'ourselves',
 'you',...

You can use np.where to replace the stopwords with np.nan

title_analysis['new_col'] = np.where(title_analysis['words'].str.contains(stopwords), np.nan, title_analysis['words'])

Then do value_counts()

title_analysis['new_col'].value_counts()

If you have your own set of words that you want to ignore, just replace stop_words with your list of words.

share|improve this answer

answered 19 hours ago

Mohit MotwaniMohit Motwani

1,9001623

from nltk.corpus import stopwords
stop_words = stopwords.words('english')
stop_words

['i',
 'me',
 'my',
 'myself',
 'we',
 'our',
 'ours',
 'ourselves',
 'you',...

title_analysis['new_col'] = np.where(title_analysis['words'].str.contains(stopwords), np.nan, title_analysis['words'])

title_analysis['new_col'].value_counts()

share|improve this answer

answered 19 hours ago

Mohit MotwaniMohit Motwani

1,9001623

answered 19 hours ago

Mohit MotwaniMohit Motwani

1,9001623

answered 19 hours ago

Mohit MotwaniMohit Motwani

1,9001623