title: read timeseries from sqlite with pandas
body: <p>I have a sqlite3 database table that I'd like to analyze in pandas.  The database represents a time-series, so I'd my DataFrame to reflect that.  Specifically, I'd like to be able use dates as an index in my DataFrame so that I can do nifty things like <a href="http://pandas.pydata.org/pandas-docs/stable/timeseries.html" rel="nofollow noreferrer">resampling</a>.</p>
  
  <p>Right now, I'm reading the DataFrame as:</p>
  
  <pre><code>db = sqlite3.connect('data.db')
  query = """
    SELECT
     *
    FROM DataTable
  """
  data = pd.read_sql_query(query, db, parse_dates={'datetime': '%Y-%m-%d %H:%M:%S'})
  </code></pre>
  
  <p>This dataframe is indexed using sequential integers, not by timestamps as I'd like.  Is there some magic incantation to create a date index on the parsed <code>datetime</code> field rather than using sequential integers?</p>