Python stemming (with pandas dataframe)

Question

I created a dataframe with sentences to be stemmed. I would like to use a Snowballstemmer to obtain higher accuracy with my classification algorithm. How can I achieve this?

import pandas as pd
from nltk.stem.snowball import SnowballStemmer

# Use English stemmer.
stemmer = SnowballStemmer("english")

# Sentences to be stemmed.
data = ["programmers program with programming languages", "my code is working so there must be a bug in the interpreter"] 
    
# Create the Pandas dataFrame.
df = pd.DataFrame(data, columns = ['unstemmed']) 

# Split the sentences to lists of words.
df['unstemmed'] = df['unstemmed'].str.split()

# Make sure we see the full column.
pd.set_option('display.max_colwidth', -1)

# Print dataframe.
df 

+----+---------------------------------------------------------------+
|    | unstemmed                                                     |
|----+---------------------------------------------------------------|
|  0 | ['programmers', 'program', 'with', 'programming', 'languages']|
|  1 | ['my', 'code', 'is', 'working', 'so', 'there', 'must',        |  
|    |  'be', 'a', 'bug', 'in', 'the', 'interpreter']                |
+----+---------------------------------------------------------------+

Solution

You have to apply the stemming on each word and store it into the "stemmed" column.

df['stemmed'] = df['unstemmed'].apply(lambda x: [stemmer.stem(y) for y in x]) # Stem every word.
df = df.drop(columns=['unstemmed']) # Get rid of the unstemmed column.
df # Print dataframe.

+----+--------------------------------------------------------------+
|    | stemmed                                                      |
|----+--------------------------------------------------------------|
|  0 | ['program', 'program', 'with', 'program', 'languag']         |
|  1 | ['my', 'code', 'is', 'work', 'so', 'there', 'must',          |   
|    |  'be', 'a', 'bug', 'in', 'the', 'interpret']                 |
+----+--------------------------------------------------------------+

Comments

[Has QUIT--Anony-Mousse]

What is the type of this column? string (= sentences), or array of strings (= words)? Don't aplly the stemmer to a sentence, but one word at a time.

[Chiel]

Sorry if I am a little noobish, I am kinda new to Python as well as Stack Overflow.

[arthur]

Ok. It's because you did it inside a for loop. remove for w in data[["stemmed"]]: and it should work.

[arthur]

The apply method is designed to apply a function on all rows/columns of a dataframe. So you don't have to iterate on rows/columns. For more informations you can have a look at the doc : link

[Chiel]

After removing the first for loop I still get the same type of error:imgur.com/AUaaqmM

[arthur]

Can you show me the dataframe just before executing the apply ?

[arthur]

I would prefer a screenshot of your python console after : print data

[arthur]

your data['stemmed'] column has not exactly the same format as mine. I edit my answer

[Chiel]

That's awesome! By the way I went from a ~70% accuracy to a 71.17 accuracy (after stemming) using the K-nearest neighbor algorithm, so it clearly helped.