title: Python Filling in missing values, with other data
body: <p>Currently im working on a script to fill in missing values in a timeline. The dataframe is looking thusfar, values are examples:</p>
  
  <pre><code>timestamp   id  value
  2016-01-01 01:00:00 1   10
  2016-01-01 02:00:00 1   15
  2016-01-01 03:00:00 1   12
  2016-01-01 04:00:00 1   NAN
  2016-01-01 05:00:00 1   NAN
  2016-01-01 06:00:00 1   7
  2016-01-01 07:00:00 1   9
  2016-01-01 01:00:00 2   10
  2016-01-01 02:00:00 2   12
  2016-01-01 03:00:00 2   14
  2016-01-01 04:00:00 2   16
  2016-01-01 05:00:00 2   8
  2016-01-01 06:00:00 2   11
  2016-01-01 07:00:00 2   14
  2016-01-01 01:00:00 3   10
  2016-01-01 02:00:00 3   12
  2016-01-01 03:00:00 3   14
  2016-01-01 04:00:00 3   12
  2016-01-01 05:00:00 3   8
  2016-01-01 06:00:00 3   9
  2016-01-01 07:00:00 3   12
  </code></pre>
  
  <p>What i would like is to fill in the NAN values by looking at the rise in values by the other object's.
  So for example if object id 2 and 3 rise 50% on average from 3:00:00 to 4:00:00 i can use the value 12 in this example and multiply it by 1.5. Im working in python at the moment using pandas. </p>
  
  <p>I can run a function through the column 'value' checking if its NAN. But im sorta stuck how to go from there.</p>
  
  <p>Basicly i want a function that when it finds a missing value to take the timestamp, then for that timestamp find the values the other objects. So in this example its missing data at 4:00:00, it will grab 16 of object 2 and 12 of object 3. Once it done that it will compare the found value to the value before this timestamp and divide by this. So 16/14 and 12/14. the average of this is 1, which i want multiplied by the value before the missing value. So 1.00 * 12.00. It has then filled in the timestamp at 4:00:00 and continue at 5:00:00</p>