title: sort Pandas dataframe with NaT values on top
body: <p>Im trying to sort a pandas dataframe with NaT values on top. I'm using the df.sort_values function:</p>
  
  <pre><code>df=df.sort_values(by='date_of_last_hoorah_given')
  </code></pre>
  
  <p>Its working fine and I'm getting a sorted dataframe with NaT values in the bottom</p>
  
  <pre><code>    date_of_last_hoorah_given                              email   first_name  \
  16 2016-12-19 07:36:08.000000              mindy.lyndi@hoorah.io        Mindy   
  29 2016-12-19 07:36:08.000000              judi.seward@hoorah.io         Judi   
  7  2016-12-19 07:36:08.000000                  chao.an@hoorah.io         Chao   
  21 2016-12-19 07:36:08.000000              bala.harish@hoorah.io         Bala   
  12 2016-12-19 07:36:08.000000            pushpa.swaran@hoorah.io       Pushpa   
  30 2016-12-22 07:36:08.000000       sparrow.freespirit@hoorah.io      Sparrow   
  28 2016-12-22 07:36:08.000000         sanjeev.prasanna@hoorah.io      Sanjeev   
  27 2016-12-22 07:36:08.000000     twinklenose.snowleaf@hoorah.io  Twinklenose   
  25 2016-12-22 07:36:08.000000       sweetgaze.sugarshy@hoorah.io    Sweetgaze   
  23 2016-12-22 07:36:08.000000            shreya.sarika@hoorah.io       Shreya   
  19 2016-12-22 07:36:08.000000              jiahao.dong@hoorah.io       Jiahao   
  15 2016-12-22 07:36:08.000000            jannine.tyson@hoorah.io       Janine   
  14 2016-12-22 07:36:08.000000                arlo.reed@hoorah.io         Arlo   
  0  2016-12-22 07:36:08.000000         aditya.hariharan@hoorah.io       Aditya   
  11 2016-12-22 07:36:08.000000        shirley.madalitso@hoorah.io      Shirley   
  2  2016-12-22 07:36:08.000000             minerva.jena@hoorah.io     Minerva    
  3  2016-12-22 07:36:08.000000             colby.brandi@hoorah.io        Colby   
  13 2016-12-22 07:36:08.000000            beverly.cohen@hoorah.io      Beverly   
  6  2016-12-22 07:36:08.000000             guanting.jun@hoorah.io     Guanting   
  5  2016-12-22 07:36:08.000000                  chen.tu@hoorah.io         Chen   
  18 2016-12-22 10:55:03.474683                  fen.lin@hoorah.io          Fen   
  9  2016-12-23 07:36:08.000000             kourtney.pam@hoorah.io     Kourtney   
  10 2016-12-23 14:30:55.206581             kailee.alfie@hoorah.io       Kailee   
  4  2016-12-24 07:36:08.000000                jing.chao@hoorah.io        Jing    
  31 2016-12-24 16:02:28.945809               rich.oswin@hoorah.io         Rich   
  24 2016-12-25 07:36:08.000000           ganesh.vasanta@hoorah.io       Ganesh   
  8  2016-12-26 07:36:08.000000               xia.yaling@hoorah.io          Xia   
  20 2016-12-27 07:36:08.000000              kinley.joan@hoorah.io       Kinley   
  22 2016-12-28 07:36:08.000000   honeygleam.dazzlesmile@hoorah.io   Honeygleam   
  26 2016-12-28 15:29:48.629929             indira.padma@hoorah.io       Indira   
  17 2016-12-29 02:27:11.125078             ileen.gaynor@hoorah.io        Ileen   
  32 2016-12-29 15:38:02.335296            ragnar.lestat@hoorah.io       Ragnar   
  1                         NaT  flitterbeam.clovergaze@hoorah.com  Flitterbeam   
  </code></pre>
  
  <p>but when I try to get it on top with the following piece of code:</p>
  
  <pre><code>df=df.sort_values(by='date_of_last_hoorah_given',ascending=[1,0])
  </code></pre>
  
  <p>Im getting a valueError: Length of ascending (2) != length of by (1)
  Full stack trace given below:</p>
  
  <pre><code>ValueError                                Traceback (most recent call last)
  &lt;ipython-input-107-948a8354aeeb&gt; in &lt;module&gt;()
        1 cd = ClientData(1)
  ----&gt; 2 cd.get_inactive_users()
  
  &lt;ipython-input-106-ed230054ea86&gt; in get_inactive_users(self)
      346             inactive_users_result.append(user_dict)
      347         df=pd.DataFrame(inactive_users_result)
  --&gt; 348         df=df.sort_values(by='date_of_last_hoorah_given',ascending=[1,0])
      349         print(df)
  
  C:\Users\aditya\Anaconda3\lib\site-packages\pandas\core\frame.py in sort_values(self, by, axis, ascending, inplace, kind, na_position)
     3126         if com.is_sequence(ascending) and len(by) != len(ascending):
     3127             raise ValueError('Length of ascending (%d) != length of by (%d)' %
  -&gt; 3128                              (len(ascending), len(by)))
     3129         if len(by) &gt; 1:
     3130             from pandas.core.groupby import _lexsort_indexer
  
  ValueError: Length of ascending (2) != length of by (1)
  </code></pre>