title: Strip time from an object date in pandas
body: <p>I am having trouble with some dates from zipped xlsx files. These files are loaded into a sqlite database then exported as .csv. Each file is about 40,000 rows per day. The issue I run into is that <code>pd.to_datetime</code> does not seem to work on these objects (dates from Excel format is causing the issue I think - pure .csv files work fine with this command). This is fine actually - I do not need them to be in datetime format. </p>
  
  <p>What I am trying to achieve is creating a column called ShortDate which is <code>%m/%d/%Y</code>. How can I do this on a datetime object (format is mm/dd/yyyy hh:mm:ss from Excel). I will then create a new column called RosterID which combines the EmployeeID field and the ShortDate field together into a unique ID. </p>
  
  <p>I am very new to pandas and I am currently only using it to process .csv files (rename and select certain columns, create unique IDs to use in filters in Tableau, etc).</p>
  
  <pre><code>rep = pd.read_csv(r'C:\Users\Desktop\test.csv.gz', dtype = 'str', compression = 'gzip', usecols = ['etc','etc2'])
  print('Read successfully.')
  rep['Total']=1
  rep['UniqueID']= rep['EmployeeID'] + rep['InteractionID']
  rep['ShortDate'] = ??? #what do I do here to get what I am looking for?
  rep['RosterID']= rep['EmployeeID'] + rep['ShortDate'] # this is my goal
  print('Modified successfully.')
  </code></pre>
  
  <p>Here is some of the raw data from the .csv. Column names would be </p>
  
  <pre><code>InteractionID, Created Date, EmployeeID, Repeat Date
  07927,04/01/2014 14:05:10,912a,04/01/2014 14:50:03
  02158,04/01/2014 13:44:05,172r,04/04/2014 17:47:29
  44279,04/01/2014 17:28:36,217y,04/07/2014 22:06:19
  </code></pre>