title: Transforming Data in a Pandas Dataframe
body: <p>I am importing an excel sheet into a Dataframe. When call dtypes in python I get the column as an Object.</p>
  
  <p>I am turning it to float with a function and then .apply()</p>
  
  <p>When I do a </p>
  
  <pre><code>df.groupby(['A'])['B'].sum()
  </code></pre>
  
  <p>I get this error:</p>
  
  <pre><code> unsupported operand type(s) for +: 'int' and 'datetime.datetime'
  </code></pre>
  
  <p>I´ve checked the excel sheet and there are only numbers. How can I transform this data into integer or ignore the values that python can´t transform?</p>
  
  <p>There are <code>Nan</code> values in this column.</p>