title: Pandas: How to handle columns with mixed types
body: <p>I am reading a csv file with columns that contain mixed data types. I am not sure what to do.</p>
  
  <p>First, this is the data that I am using: <a href="https://www.kaggle.com/epa/fuel-economy/data" rel="nofollow noreferrer">https://www.kaggle.com/epa/fuel-economy/data</a></p>
  
  <p>Now I am reading that file in:</p>
  
  <pre><code>    data = pd.read_csv('data/database.csv', sep=',')
  </code></pre>
  
  <p>This the error message I am getting:</p>
  
  <pre><code>DtypeWarning: Columns (7,16,62,64,65,67,68,78) have mixed types. Specify dtype option on import or set low_memory=False.
    interactivity=interactivity, compiler=compiler, result=result)
  </code></pre>
  
  <p>Now I'm wondering what to do.
  I could add <code>low_memory=False</code> or set the data type of these columns wihtin the <code>read_csv</code> method. My problem is that I am not sure what kind of type I should set it to, because that dataset is that huge and I can't figure out what data type would be the best for each column.</p>
  
  <p>Could someone help me with my problem?</p>