title: Calculate time difference in Hours or seconds between two columns of a dataframe
body: <p>I am trying to calculate machine downtime in a python code which is predominantly pandas dataframe manipulation. If a repair number starts during any of the days then I have take take time bewteen start of the day and start of the work order as my machine available time. I have created the column for day start time as  in every row which is at a day level granularity so that when there is a repair order I just need to subtract two time fields to get my answer in seconds/hours. But I am currently getting error as 'Timedelta' object has no attribute 'astype'. I tried out of a few options suggested here but to no vail. I know I am doing somehting very fundamentally wrong, please point me in the right directions. </p>
  
  <pre><code>for i, row in df4.iterrows():
      if (row['Date'] == row['START_DATE']) | (row['Date'] == row['END_DATE']):
          if (row['START_DATE'] == row['Date']) &amp; (row['END_DATE'] != row['Date']):
  
              value = pd.to_timedelta(row.REPAIR_START-row.Date_start).astype('timedelta64[h]')
              df4.set_value(i,'avail',value)
  
          if (row['START_DATE'] != row['Date']) &amp; (row['END_DATE'] == row['Date']):
  
              value = pd.to_timedelta((row.REPAIR_FINISH-row.Date_end)).astype('timedelta64[h]')
              df4.set_value(i,'avail',value)
  
          if (row['START_DATE'] == row['Date']) &amp; (row['END_DATE'] == row['Date']):
              value = pd.to_timedelta((row.REPAIR_START-row.REPAIR_FINISH)).astype('timedelta64[h]')
              df4.set_value(i,'avail',value)
          else: df4.set_value(i,'avail',full_day)
  </code></pre>
  
  <p>Data is at Machine , Date level. Explanation of the metadata of the code:<br>
  Date : Daily date<br>
  START_DATE : Only date part of the repair timestamp<br>
  END_DATE : Only date part of the repair timestamp<br>
  REPAIR_START : Repair order start timestamp<br>
  REPAIR_START  : Repair order end timestamp  </p>