how to use word_tokenize in data frame

Question

I have recently started using the nltk module for text analysis. I am stuck at a point. I want to use word_tokenize on a dataframe, so as to obtain all the words used in a particular row of the dataframe.

data example:
       text
1.   This is a very good site. I will recommend it to others.
2.   Can you please give me a call at 9983938428. have issues with the listings.
3.   good work! keep it up
4.   not a very helpful site in finding home decor. 

expected output:

1.   'This','is','a','very','good','site','.','I','will','recommend','it','to','others','.'
2.   'Can','you','please','give','me','a','call','at','9983938428','.','have','issues','with','the','listings'
3.   'good','work','!','keep','it','up'
4.   'not','a','very','helpful','site','in','finding','home','decor'

Basically, i want to separate all the words and find the length of each text in the dataframe.

I know word_tokenize can for it for a string, but how to apply it onto the entire dataframe?

Please help!

Thanks in advance...

Answer 1

You can use apply method of DataFrame API:

import pandas as pd
import nltk

df = pd.DataFrame({'sentences': ['This is a very good site. I will recommend it to others.', 'Can you please give me a call at 9983938428. have issues with the listings.', 'good work! keep it up']})
df['tokenized_sents'] = df.apply(lambda row: nltk.word_tokenize(row['sentences']), axis=1)

Output:

>>> df
                                           sentences  \
0  This is a very good site. I will recommend it ...   
1  Can you please give me a call at 9983938428. h...   
2                              good work! keep it up   

                                     tokenized_sents  
0  [This, is, a, very, good, site, ., I, will, re...  
1  [Can, you, please, give, me, a, call, at, 9983...  
2                      [good, work, !, keep, it, up]

For finding the length of each text try to use apply and lambda function again:

df['sents_length'] = df.apply(lambda row: len(row['tokenized_sents']), axis=1)

>>> df
                                           sentences  \
0  This is a very good site. I will recommend it ...   
1  Can you please give me a call at 9983938428. h...   
2                              good work! keep it up   

                                     tokenized_sents  sents_length  
0  [This, is, a, very, good, site, ., I, will, re...            14  
1  [Can, you, please, give, me, a, call, at, 9983...            15  
2                      [good, work, !, keep, it, up]             6