CODEWITHSUNDEEP
pythonloopsnltktweetsstop-words
Kevin
Kevin

Reputation: 1739

Removing stopwords from tweets Python

I am trying to remove stopwords from tweets that I have imported from Twitter. After removing the stopwords, the list of strings will be placed in a new column in the same row. I can easily accomplish this one row at a time however when attempting to loop the method over the whole Data Frame does not seem to succeed.

How do would I do this?

Snippet of my data:

tweets['text'][0:5]
Out[21]: 
0    Why #litecoin will go over 50 USD soon ? So ma...
1    get 20 free #bitcoin spins at...
2    Are you Bullish or Bearish on #BMW? Start #Tra...
3    Are you Bullish or Bearish on the S&P 500?...
4    TIL that there is a DAO ExtraBalance Refund. M...

The following works in a single row scenario:

from nltk.corpus import stopwords
stop_words = set(stopwords.words('english'))
tweets['text-filtered'] = ""

word_tokens = word_tokenize(tweets['text'][1])
filtered_sentence = [w for w in word_tokens if not w in stop_words] 
tweets['text-filtered'][1] = filtered_sentence

tweets['text-filtered'][1]
Out[22]: 
['get',
 '20',
 'free',
 '#',
 'bitcoin',
 'spins',
 'withdraw',
 'free',
 '#',
 'btc',
 '#',
 'freespins',
 '#',
 'nodeposit',
 '#',
 'casino',
 '#',
 '...',
 ':']

My attempt at a loop does not succeed:

for i in tweets:
    word_tokens = word_tokenize(tweets.get(tweets['text'][i], False))
    filtered_sentence = [w for w in word_tokens if not w in stop_words] 
    tweets['text-filtered'][i] = filtered_sentence

A snippet of the traceback:

Traceback (most recent call last):

  File "<ipython-input-23-6d7dace7a2d0>", line 2, in <module>
    word_tokens = word_tokenize(tweets.get(tweets['text'][i], False))

...

KeyError: 'id'

Based off @Prune's reply, I have managed to correct my mistakes. Here is a potential solution:

count = 0    
for i in tweets['text']:
    word_tokens = word_tokenize(i)
    filtered_sentence = [w for w in word_tokens if not w in stop_words]
    tweets['text-filtered'][count] = filtered_sentence
    count += 1

My previous attempt was looping through the columns of the Data Frame, tweets. The first column in tweets was "id".

tweets.columns
Out[30]: 
Index(['id', 'user_bg_color', 'created', 'geo', 'user_created', 'text',
       'polarity', 'user_followers', 'user_location', 'retweet_count',
       'id_str', 'user_name', 'subjectivity', 'coordinates',
       'user_description', 'text-filtered'],
      dtype='object')

Upvotes: 0

Views: 3608

Answers (1)

Prune
Prune

Reputation: 77860

You're confused about list indexing:

for i in tweets:
    word_tokens = word_tokenize(tweets.get(tweets['text'][i], False))
    filtered_sentence = [w for w in word_tokens if not w in stop_words] 
    tweets['text-filtered'][i] = filtered_sentence

Note that tweets is a dictionary; tweets['text']list of strings. Thus, for i in tweets returns all of the keys in tweets: the dictionary keys in arbitrary order. It appears that "id" is the first one returned. When you try to assign tweets['text-filtered']['id'] = filtered_sentence, there just is no such element.

Try coding more gently: start at the inside, code a few lines at a time, and work your way up to more complex control structures. Debug each addition before you go on. Here, you seem to have lost your sense of what is a numeric index, what is a list, and what is a dictionary.

Since you haven't done any visible debugging, or provided the context, I can't fix the whole program for you -- but this should get you started.

Upvotes: 2

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