title: Return rows with set time difference in elements within cell (containing datetime64ns) Python dataframe np.array
body: <p>I'm trying to find a way to just return rows of a dataframe that have a difference of 24 hours or less between the first and second element within a particular cell.</p>
  
  <pre><code>df = pd.DataFrame({'ItemID': [23146, 23146, 23146, 23191, 23198, 23198],
                      'CustomerID': ['23166', '23167', '23168', '23169', '23170', '23171'],
                     'Value': [11, 21, 22, 53, 15, 8],
                      'TransDts': [(['2011-01-26T14:30:00.000000000', '2011-04-07T10:43:00.000000000']), 
                            (['2011-01-26T14:30:00.000000000', '2011-01-26T14:45:00.000000000']), 
                            (['2011-01-26T14:45:00.000000000', '2011-01-26T14:55:00.000000000']), 
                            (['2011-01-26T14:30:00.000000000', '2011-01-27T10:43:00.000000000']), 
                            (['2011-01-26T14:30:00.000000000', '2011-01-28T10:43:00.000000000']), 
                            (['2011-01-26T14:30:00.000000000', '2011-01-29T10:43:00.000000000'])]})
  </code></pre>
  
  <p>The df contains transnational data and the 'TransDts' columns always contains 2 datetimes - and I only want to return (or flag) rows in which the transactions are within 24 hours of eachother.</p>
  
  <p>Any ideas or input would be greatly appreciated. Thanks in advance</p>