title: Pandas datetime format to prevent NaT
body: <p>I am reading in an excel file into python with pandas. </p>
  
  <p>xls = pd.ExcelFile("filename.xlsx")</p>
  
  <p>df = xls.parse('Sheet1')</p>
  
  <p>I have a column in my dataframe (time_since_illness_onset) with datetime objects of the form: </p>
  
  <p>1900-01-03 00:00:00
  1900-01-04 04:30:00</p>
  
  <p>I would like to parse these so that I have a column for days, hours and seconds (the year and month here is meaningless). </p>
  
  <p>I had used the following code:</p>
  
  <pre><code>df['time_since_illness_onset'] = pd.to_datetime(df['time_since_illness_onset'], errors='coerce')
  df['time_since_illness_onset'] = df['time_since_illness_onset'].dt.day + df['time_since_illness_onset'].dt.hour/24. + df['time_since_illness_onset'].dt.minute/60./24
  </code></pre>
  
  <p>It seemed to work fine. However, I noticed that for datetimes that are less than one day the above code turns the dates into NaT. </p>
  
  <p>As an example, I had a row in the original dataframe like this:
  22:00:00
  And after I manipulated the dataframe with the two lines above it turned into a NaT. Any help would be greatly appreciated, thank you!! </p>