title: Removing stop words from a pandas column
body: <pre><code>import nltk
  nltk.download('punkt')
  nltk.download('stopwords')
  import datetime
  import numpy as np
  import re
  from nltk.tokenize import word_tokenize
  from nltk.corpus import stopwords
  from nltk.stem.wordnet import WordNetLemmatizer
  from nltk.stem.porter import PorterStemmer
  # Load the Pandas libraries with alias 'pd' 
  import pandas as pd 
  # Read data from file 'filename.csv' 
  # (in the same directory that your python process is based)
  # Control delimiters, rows, column names with read_csv (see later) 
  data = pd.read_csv(&quot;march20_21.csv&quot;) 
  # Preview the first 5 lines of the loaded data 
  #drop NA rows
  data.dropna()
  #drop all columns not needed
  droppeddata = data.drop(columns=['created_at'])
  #drop NA rows
  alldata = droppeddata.dropna()
  
  ukdata = alldata[alldata.place.str.contains('England')]
  ukdata.drop(columns=['place'])
  
  ukdata['text'].apply(word_tokenize)
  eng_stopwords = stopwords.words('english') 
  </code></pre>
  <p>I know there is a lot of redundant variables, but im still working on gettig it working before going back to refine it.</p>
  <p>I am unsure on how to remove the stopwords, stored in the variable, from the tokenised columns. Any help is appreciated, I am brand new to Python! Thanks.</p>