title: upsample in a timeseries and interpolating data
body: <p>I need to perform an Upsample in a timeseries, and then to interpolate data and I would like to find the best way to do that. Timeseries has not constant interval. I show a DatFrame example and the result I'm looking. In the result example I'm interpolating just 1 row. It would be great to bea able to interpolate n rows.</p>
  
  <pre><code>data = {'time': ['08-12-2018 10:00:00','08-12-2018 10:01:00','08-12-2018 \
  10:01:30','08-12-2018 10:03:00','08-12-2018 10:03:10'], 'value':[1,2,3,4,5]}
  df=pd.DataFrame(data)
  df.time=pd.to_datetime(df.time)
  df
  Out[42]: 
                   time  value
  0 2018-08-12 10:00:00      1
  1 2018-08-12 10:01:00      2
  2 2018-08-12 10:01:30      3
  3 2018-08-12 10:03:00      4
  4 2018-08-12 10:03:10      5
  </code></pre>
  
  <p>Result</p>
  
  <pre><code>                 time  value
  0 2018-08-12 10:00:00      1
  1 2018-08-12 10:00:30      1.5
  2 2018-08-12 10:01:00      2
  3 2018-08-12 10:01:15      2.5
  4 2018-08-12 10:01:30      3
  5 2018-08-12 10:02:15      3.5
  6 2018-08-12 10:03:00      4
  7 2018-08-12 10:03:05      4.5
  8 2018-08-12 10:03:10      5
  </code></pre>