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POHow to group DataFrame by a period of time?
 

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  1. POHow to group DataFrame by a period of time?
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    <p>I have some data from log files and would like to group entries by a minute:</p> <pre><code> def gen(date, count=10): while count &gt; 0: yield date, "event{}".format(randint(1,9)), "source{}".format(randint(1,3)) count -= 1 date += DateOffset(seconds=randint(40)) df = DataFrame.from_records(list(gen(datetime(2012,1,1,12, 30))), index='Time', columns=['Time', 'Event', 'Source']) </code></pre> <p>df:</p> <pre><code> Event Source 2012-01-01 12:30:00 event3 source1 2012-01-01 12:30:12 event2 source2 2012-01-01 12:30:12 event2 source2 2012-01-01 12:30:29 event6 source1 2012-01-01 12:30:38 event1 source1 2012-01-01 12:31:05 event4 source2 2012-01-01 12:31:38 event4 source1 2012-01-01 12:31:44 event5 source1 2012-01-01 12:31:48 event5 source2 2012-01-01 12:32:23 event6 source1 </code></pre> <p>I tried these options:</p> <ol> <li><code>df.resample('Min')</code> is too high level and wants to aggregate.</li> <li><code>df.groupby(date_range(datetime(2012,1,1,12, 30), freq='Min', periods=4))</code> fails with exception.</li> <li><p><code>df.groupby(TimeGrouper(freq='Min'))</code> works fine and returns a <code>DataFrameGroupBy</code> object for further processing, e.g.:</p> <pre><code>grouped = df.groupby(TimeGrouper(freq='Min')) grouped.Source.value_counts() 2012-01-01 12:30:00 source1 1 2012-01-01 12:31:00 source2 2 source1 2 2012-01-01 12:32:00 source2 2 source1 2 2012-01-01 12:33:00 source1 1 </code></pre></li> </ol> <p><em>However</em>, the <code>TimeGrouper</code> class is not documented.</p> <p>What is the correct way to group by a period of time? How can I group the data by a minute AND by the Source column, e.g. <code>groupby([TimeGrouper(freq='Min'), df.Source])</code>?</p>
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