title: pandas grouping and aggregating
body: <p>I have a pandas dataframe in the format below:</p>
  
  <pre><code>Timestamp            Column1    Column2   Column3
  2018-01-01 00:00:01    5.7        4.0        2.0
  2018-01-01 00:00:02    5.7        4.2        1.8
  2018-01-01 00:00:03    4.9        5.1        5.5
  2018-01-01 00:00:04    5.8        5.2        1.9
  </code></pre>
  
  <p>and so on. Essentially have data in second level granularity.
  I am looking to summarize as follows:</p>
  
  <pre><code>Timestamp            Column1    Column2   Column3
  2018-01-01 00:00       5.8        5.2       5.5
  </code></pre>
  
  <p>Essentially for every minute, I want to calculate the max value. Any value occurring between say </p>
  
  <pre><code>  2018-01-01 00:00:01 and 2018-01-01 00:00:59 
  </code></pre>
  
  <p>needs to be included in the calculation and summarized as value for timestamp</p>
  
  <pre><code> 2018-01-01 00:00:00
  </code></pre>
  
  <p>I have tried (assuming df is the name of the dataframe) and pandas loaded as pd</p>
  
  <pre><code> df=df.groupby(pd.Timestamp.floor(df['Timestamp'], freq='min')).max()
  </code></pre>
  
  <p>But this does not work.
  Thoughts?
  Thanks!</p>