title: python pandas - how to merge date from one and time from another column and create new column
body: <p>I have a dataframe that comes from a database like this:
  Both FltDate and ESTAD2 are datetime64[ns]</p>
  
  <pre><code>&gt;&gt;&gt; print df[['Airport', 'FltDate', 'Carrier', 'ESTAD2']]
  
       Airport    FltDate Carrier              ESTAD2
  0       EDI 2017-06-18    BACJ 1899-12-30 05:35:00
  1       EDI 2017-06-18      BA 1899-12-30 06:40:00
  2       EDI 2017-06-18    BACJ 1899-12-30 07:00:00
  3       EDI 2017-06-18      BA 1899-12-30 07:05:00
  4       EDI 2017-06-18      BA 1899-12-30 09:00:00
  5       EDI 2017-06-18      I2 1899-12-30 11:05:00
  6       EDI 2017-06-18      BA 1899-12-30 11:25:00
  7       EDI 2017-06-18      BA 1899-12-30 13:45:00
  
  
  &gt;&gt;&gt; df.info()
  
  &lt;class 'pandas.core.frame.DataFrame'&gt;
  RangeIndex: 214 entries, 0 to 213
  Data columns (total 12 columns):
  Airport         214 non-null object
  FltDate         214 non-null datetime64[ns]
  &lt;snip&gt;
  ESTAD2          214 non-null datetime64[ns]
  &lt;snip&gt;
  dtypes: datetime64[ns](4), object(8)
  memory usage: 20.1+ KB
  </code></pre>
  
  <p>How to get the <strong>Date Part from FltDate</strong> and <strong>Time Part from ESTAD2.</strong></p>
  
  <p>Result should be like this say for Row 0</p>
  
  <pre><code>2017-06-18 05:35:00 (that is 18Jun2017 of FltDate + 05:35 of ESTAD2)
  </code></pre>
  
  <p>I may replace ESTAD2 with above result.. or create a new column as FltDateTime.</p>
  
  <p>Tried various ways and failed... like below... adding was unsuccessful.</p>
  
  <pre><code>&gt;&gt;&gt; df.FltDate.dt.date
  
  0      2017-06-18
  1      2017-06-18
  2      2017-06-18
  &gt;&gt;&gt; df.ESTAD2.dt.time
  
  0      05:35:00
  1      06:40:00
  2      07:00:00
  </code></pre>