title: How should I select rows of a pandas dataframe whose entries start with a certain string?
body: <p>Apologies if this is contained in a previous answer but I've read this one: <a href="https://stackoverflow.com/questions/17071871/how-to-select-rows-from-a-dataframe-based-on-column-values">How to select rows from a DataFrame based on column values?</a> and can't work out how to do what I need to do:</p>
  
  <p>Suppose  have some pandas dataframe X and one of the columns is 'timestamp'. The entries are formatted like <code>'2010-11-03 09:44:05'</code>. I want to select just those rows that correspond to a specific <em>day</em>, for example, select just those rows for which the actual string in timestamp column <em>starts with</em> '2010-11-03'. Is there a neat way to do this? Can I do it with a mask or Boolean indexing? Or should I just write a separate line to peel off the day from each entry and then select the rows? Bear in mind the dataframe is large if it helps.</p>
  
  <p>i.e. I want to write something like</p>
  
  <p><code>X.loc[X['timestamp'].startswith('2010-11-03')]</code></p>
  
  <p>or</p>
  
  <p><code>mask = '2010-11-03' in X["timestamp"]</code></p>
  
  <p>but these don't actually make any sense.</p>