title: selecting across multiple columns with pandas
body: <p>I have a dataframe <code>df</code> in pandas that was built using <code>pandas.read_table</code> from a csv file. The dataframe has several columns and it is indexed by one of the columns (which is unique, in that each row has a unique value for that column used for indexing.) </p>
  
  <p>How can I select rows of my dataframe based on a "complex" filter applied to multiple columns? I can easily select out the slice of the dataframe where column <code>colA</code> is greater than 10 for example:</p>
  
  <pre><code>df_greater_than10 = df[df["colA"] &gt; 10]
  </code></pre>
  
  <p>But what if I wanted a filter like: select the slice of <code>df</code> where <em>any</em> of the columns are greater than 10? </p>
  
  <p>Or where the value for <code>colA</code> is greater than 10 but the value for <code>colB</code> is less than 5?</p>
  
  <p>How are these implemented in pandas?
  Thanks.</p>