title: Merging/combining two dataframes with different frequency time series indexes in Pandas?
body: <p>Using pandas 0.15.1.  Suppose I have the following two dataframes:</p>
  
  <pre><code>daily
  2014-11-20 00:00:00 Rain
  2014-11-21 00:00:00 Cloudy
  2014-11-22 00:00:00 Sunny
  </code></pre>
  
  <p>.</p>
  
  <pre><code>minutely
  2014-11-20 12:45:00     51
  2014-11-20 12:46:00     43
  2014-11-20 12:47:00     44
  ...
  2014-11-21 12:45:00     44
  2014-11-21 12:46:00     46
  2014-11-21 12:47:00     48
  ...
  2014-11-22 12:45:00     38
  2014-11-22 12:46:00     32
  2014-11-22 12:47:00     37
  </code></pre>
  
  <p>I'd like to combine the two dataframes such that the day values get propagated to each minute row that have the corresponding day.</p>
  
  <p>And since the minute rows do not actually have data at 00:00:00 I do not want that time included in the resulting dataframe.  Desired output:</p>
  
  <pre><code>2014-11-20 12:45:00     51  Rain
  2014-11-20 12:46:00     43  Rain
  2014-11-20 12:47:00     44  Rain
  ...
  2014-11-21 12:45:00     44  Cloudy
  2014-11-21 12:46:00     46  Cloudy
  2014-11-21 12:47:00     48  Cloudy
  ...
  2014-11-22 12:45:00     38  Sunny
  2014-11-22 12:46:00     32  Sunny
  2014-11-22 12:47:00     37  Sunny
  </code></pre>
  
  <p>How can I achieve this?  Do I need to use merge, concat, or join?</p>