title: Keep only date part when using pandas.to_datetime
body: <p>I use <code>pandas.to_datetime</code> to parse the dates in my data. Pandas by default represents the dates with <code>datetime64[ns]</code> even though the dates are all daily only.
  I wonder whether there is an elegant/clever way to convert the dates to <code>datetime.date</code> or <code>datetime64[D]</code> so that, when I write the data to CSV, the dates are not appended with <code>00:00:00</code>. I know I can convert the type manually element-by-element:</p>
  
  <pre><code>[dt.to_datetime().date() for dt in df.dates]
  </code></pre>
  
  <p>But this is really slow since I have many rows and it sort of defeats the purpose of using <code>pandas.to_datetime</code>. Is there a way to convert the <code>dtype</code> of the entire column at once? Or alternatively, does <code>pandas.to_datetime</code> support a precision specification so that I can get rid of the time part while working with daily data?</p>