title: Find daily observation closest to specific time for irregularly spaced data
body: <p>I have a python dataframe like</p>
  
  <pre><code>Out[110]:
  Time
  2014-09-19 21:59:14    55.975
  2014-09-19 21:56:08    55.925
  2014-09-19 21:53:05    55.950
  2014-09-19 21:50:29    55.950
  2014-09-19 21:50:03    55.925
  2014-09-19 21:47:00    56.150
  2014-09-19 21:53:57    56.225
  2014-09-19 21:40:51    56.225
  2014-09-19 21:37:50    56.300
  2014-09-19 21:34:46    56.300
  2014-09-19 21:31:41    56.350
  2014-09-19 21:30:08    56.500
  2014-09-19 21:28:39    56.375
  2014-09-19 21:25:34    56.350
  2014-09-19 21:22:32    56.400
  2014-09-19 21:19:27    56.325
  2014-09-19 21:16:25    56.325
  2014-09-19 21:13:21    56.350
  2014-09-19 21:10:18    56.425
  2014-09-19 21:07:13    56.475
  Name: Spread, dtype: float64
  </code></pre>
  
  <p>which extends over long time periods (months to years) so with very many observation for each day. What I want to do is that I for each day want to retrieve the time series observation closest to a specific time, say 16:00.  </p>
  
  <p>My approach so far have been  </p>
  
  <pre><code>eodsearch = pd.DataFrame(df['Date'] + datetime.timedelta(hours=16))
  
  eod = df.iloc[df.index.get_loc(eodsearch['Date'] ,method='nearest')]
  </code></pre>
  
  <p>which currently gives me an error of</p>
  
  <pre><code>"Cannot convert input [Time Date, dtype: datetime64[ns]] of type &lt;class 'pandas.core.series.Series'&gt; to Timestamp 
  </code></pre>
  
  <p>Moreover I saw that get_loc also accepted tolerance as an input so if I could set tolerance to say 30 min that would be great as well. </p>
  
  <p>Any advice on why my code fails or how to fix it?  </p>