title: How to handle columns like 'country' and 'age groups' while making a prediction model in python?
body: <p>I am much new to machine learning and while I was working on this specific data-frame, I found it difficult to handle important columns like age groups and country. </p>
  
  <p>Here is a link to the data-set I am using:</p>
  
  <p><a href="https://www.kaggle.com/russellyates88/suicide-rates-overview-1985-to-2016https://www.kaggle.com/russellyates88/suicide-rates-overview-1985-to-2016" rel="nofollow noreferrer">https://www.kaggle.com/russellyates88/suicide-rates-overview-1985-to-2016https://www.kaggle.com/russellyates88/suicide-rates-overview-1985-to-2016</a></p>
  
  <p>In the more precise prediction of the data, the columns 'country' and 'age group' are pretty much important. But I am constantly getting the errors like:</p>
  
  <pre><code>{ 
    could not convert string to float: '15-24 years' 
  }
  </code></pre>
  
  <p>And similar for the country column.</p>
  
  <p>What could I do to make them suitable for the model?</p>