title: How should I go about using TF-IDF for text classification on the data I collected?
body: <p>I'm working on a personal project to build a text classifier. I scraped around 3000 news articles from 8 categories. I have every single word in every article with its article's category tag in a dataframe. </p>
  
  <p>The answers I saw online referred to using tfidf on entire articles/text blocks. Is there any way to analyze individual words?</p>
  
  <p>Here is an idea of what my data currently looks like:</p>
  
  <pre><code>Word:       Category:
  
  Mobile      Science/tech
  Phone       Science/tech
  Google      Science/tech
  Facebook    Science/tech
  Implant     Science/tech
  Interest    Business/economy
  Bank        Business/economy
  IMF         Business/economy
  Downturn    Business/economy
  President   Politics
  Donald      Politics
  Trump       Politics
  etc...        etc...
  </code></pre>
  
  <p>I apologize for the horrible formatting; I'm somewhat new to this.</p>