title: Handle missing values in pandas using dtype to read files
body: <p>I'm reading a bunch of CSV files using dtype to specify the type of data of  each column:</p>
  
  <pre><code>dict_tpye = {"columns_1":"int","column_2":"str"}
  pd.read_csv(path,dtype=dict_tpye)
  </code></pre>
  
  <p>the problem I'm facing with at doing this that columns with non-float values have missing rows, which rise and error. How can I handle this?</p>
  
  <p>I'll like to use a default value for such a cases, like a 0 for  numeric values and an empty string for names.</p>