title: Unable to resample between irregular 15 minutes time-stamp 00:14:59 - 00:29:59 in pandas
body: <p>I have a dataframe 'df' with datetime index set at 15 minute intervals. The intervals are like this </p>
  
  <pre><code>Index                Data
  2015-03-15 00:14:59  36.0
  2015-03-15 00:29:59  54.9
  2015-03-15 00:44:59  28.7
  </code></pre>
  
  <p>I want to upsample the above data to minute by minute intervals like below by interpolating the data.</p>
  
  <pre><code>Index                Data
  2015-03-15 00:14:59  36.0
  2015-03-15 00:15:59  36.5
  2015-03-15 00:16:59  43.3
  ...... so on
  </code></pre>
  
  <p>However, I have tried to do following: </p>
  
  <pre><code>df = df.resample('T').interpolate(method='spline', order=3)
  </code></pre>
  
  <p>Also tried : </p>
  
  <pre><code>df = df.resample('60s').interpolate(method='spline', order=3)
  </code></pre>
  
  <p>However both of the above produce following result. They set the microseconds to 00:00:00 whereas I want it to be set according to the starting timestamp that ends at 59. 00:14:59. </p>
  
  <pre><code>Index                Data
  2015-03-15 00:14:00  NaN
  2015-03-15 00:15:00  NaN
  2015-03-15 00:16:00  NaN
  ...... so on
  </code></pre>
  
  <p>How do I upsample according to uniform intervals of 59 microseconds at the end?</p>