Stemming text data

When we deal with a text document, we encounter different forms of a word. Consider the word "play". This word can appear in various forms, such as "play", "plays", "player", "playing", and so on. These are basically families of words with similar meanings. During text analysis, it's useful to extract the base form of these words. This will help us in extracting some statistics to analyze the overall text. The goal of stemming is to reduce these different forms into a common base form. This uses a heuristic process to cut off the ends of words to extract the base form. Let's see how to do this in Python.

How to do it…

1. Create a new Python file, and import the following packages:

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

2. Let's define a few words to play with, as follows:

   words = ['table', 'probably', 'wolves', 'playing', 'is', 
           'dog', 'the', 'beaches', 'grounded', 'dreamt...