Stemming text data

The stemming procedure involves creating a suitable word with reduced letters for the words of the tokenizer.

How to do it...

1. Initialize the stemming process with a new Python file:

from nltk.stem.porter import PorterStemmer 
from nltk.stem.lancaster import LancasterStemmer 
from nltk.stem.snowball import SnowballStemmer 

2. Let's describe some words to consider, as follows:

words = ['ability', 'baby', 'college', 'playing', 'is', 'dream', 'election', 'beaches', 'image', 'group', 'happy'] 

3. Identify a group of stemmers to be used:

stemmers = ['PORTER', 'LANCASTER', 'SNOWBALL'] 

4. Initialize the necessary tasks for the chosen stemmers:

stem_porter = PorterStemmer() 
stem_lancaster = LancasterStemmer() 
stem_snowball = SnowballStemmer('english') 

5. Format a table to print the results:

formatted_row = '{:>16}' * (len(stemmers) + 1) 
print 'n', formatted_row.format('WORD', *stemmers), 'n' 

6. Repeatedly check the list of words and arrange them using chosen stemmers:

for word in words:
  stem_words...