will try out porter stemmer which has been around the nltk module for quite some time now



In [2]:

    
from nltk.stem import PorterStemmer



In [3]:

    
example_words = ["python","pythoner","pythoning","pythoned","pythonly"]



In [4]:

    
ps = PorterStemmer()



In [6]:

    
for w in example_words:
    print(ps.stem(w))









    



python
python
python
python
pythonli

Trying stemming a sentence instead of a word now



In [7]:

    
from nltk.tokenize import word_tokenize



In [9]:

    
new_text = "It is important to by very pythonly while you are pythoning with python. All pythoners have pythoned poorly at least once."



In [10]:

    
words = word_tokenize(new_text)



In [11]:

    
for w in words:
    print(ps.stem(w))









    



It
is
import
to
by
veri
pythonli
while
you
are
python
with
python
.
All
python
have
python
poorli
at
least
onc
.



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