resample(self, rule, *args, **kwargs)
Given a grouper, the function resamples it according to a string "string" -> "frequency".
See the frequency aliases <timeseries.offset_aliases>
documentation for more details.
The offset string or object representing target grouper conversion.
Possible arguments are :None:None:`how`, :None:None:`fill_method`, :None:None:`limit`, kind
and :None:None:`on`, and other arguments of :None:None:`TimeGrouper`.
Return a new grouper with our resampler appended.
Provide resampling when using a TimeGrouper.
DatetimeIndex.resample
Frequency conversion and resampling of time series.
Grouper
Specify a frequency to resample with when grouping by a key.
>>> idx = pd.date_range('1/1/2000', periods=4, freq='T')
... df = pd.DataFrame(data=4 * [range(2)],
... index=idx,
... columns=['a', 'b'])
... df.iloc[2, 0] = 5
... df a b 2000-01-01 00:00:00 0 1 2000-01-01 00:01:00 0 1 2000-01-01 00:02:00 5 1 2000-01-01 00:03:00 0 1
Downsample the DataFrame into 3 minute bins and sum the values of the timestamps falling into a bin.
This example is valid syntax, but we were not able to check execution>>> df.groupby('a').resample('3T').sum() a b a 0 2000-01-01 00:00:00 0 2 2000-01-01 00:03:00 0 1 5 2000-01-01 00:00:00 5 1
Upsample the series into 30 second bins.
This example is valid syntax, but we were not able to check execution>>> df.groupby('a').resample('30S').sum() a b a 0 2000-01-01 00:00:00 0 1 2000-01-01 00:00:30 0 0 2000-01-01 00:01:00 0 1 2000-01-01 00:01:30 0 0 2000-01-01 00:02:00 0 0 2000-01-01 00:02:30 0 0 2000-01-01 00:03:00 0 1 5 2000-01-01 00:02:00 5 1
Resample by month. Values are assigned to the month of the period.
This example is valid syntax, but we were not able to check execution>>> df.groupby('a').resample('M').sum() a b a 0 2000-01-31 0 3 5 2000-01-31 5 1
Downsample the series into 3 minute bins as above, but close the right side of the bin interval.
This example is valid syntax, but we were not able to check execution>>> df.groupby('a').resample('3T', closed='right').sum() a b a 0 1999-12-31 23:57:00 0 1 2000-01-01 00:00:00 0 2 5 2000-01-01 00:00:00 5 1
Downsample the series into 3 minute bins and close the right side of the bin interval, but label each bin using the right edge instead of the left.
This example is valid syntax, but we were not able to check execution>>> df.groupby('a').resample('3T', closed='right', label='right').sum() a b a 0 2000-01-01 00:00:00 0 1 2000-01-01 00:03:00 0 2 5 2000-01-01 00:03:00 5 1See :
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