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python - Resample intraday pandas DataFrame without add new days

Asked 12 years, 6 months ago

Viewed 8k times

I want to downsample some intraday data without adding in new days

df.resample('30Min')

Will add weekends etc which is undesirable. Is there anyway around this?

asked Feb 15, 2013 at 16:03

66711 gold badge77 silver badges1414 bronze badges

A combined groupby/resample might work:

In [22]: dates = pd.date_range('01-Jan-2014','11-Jan-2014', freq='T')[0:-1]
    ...: dates = dates[dates.dayofweek < 5]
    ...: s = pd.TimeSeries(np.random.randn(dates.size), dates)
    ...: 

In [23]: s.size
Out[23]: 11520

In [24]: s.groupby(lambda d: d.date()).resample('30min').size
Out[24]: 384

In [25]: s.groupby(lambda d: d.date()).resample('30min')
Out[25]: 
2014-01-01  2014-01-01 00:00:00    0.202943
            2014-01-01 00:30:00   -0.466010
            2014-01-01 01:00:00    0.029175
            2014-01-01 01:30:00   -0.064492
            2014-01-01 02:00:00   -0.113348
            2014-01-01 02:30:00    0.100408
            2014-01-01 03:00:00   -0.036561
            2014-01-01 03:30:00   -0.029578
            2014-01-01 04:00:00   -0.047602
            2014-01-01 04:30:00   -0.073846
            2014-01-01 05:00:00   -0.410143
            2014-01-01 05:30:00    0.143853
            2014-01-01 06:00:00   -0.077783
            2014-01-01 06:30:00   -0.122345
            2014-01-01 07:00:00    0.153003
...
2014-01-10  2014-01-10 16:30:00   -0.107377
            2014-01-10 17:00:00   -0.157420
            2014-01-10 17:30:00    0.201802
            2014-01-10 18:00:00   -0.189018
            2014-01-10 18:30:00   -0.310503
            2014-01-10 19:00:00   -0.086091
            2014-01-10 19:30:00   -0.090800
            2014-01-10 20:00:00   -0.263758
            2014-01-10 20:30:00   -0.036789
            2014-01-10 21:00:00    0.041957
            2014-01-10 21:30:00   -0.192332
            2014-01-10 22:00:00   -0.263690
            2014-01-10 22:30:00   -0.395939
            2014-01-10 23:00:00   -0.171149
            2014-01-10 23:30:00    0.263057
Length: 384

In [26]: np.unique(_25.index.get_level_values(1).minute)
Out[26]: array([ 0, 30])

In [27]: np.unique(_25.index.get_level_values(1).dayofweek)
Out[27]: array([0, 1, 2, 3, 4]) 

answered Feb 17, 2013 at 7:53

76822 gold badges66 silver badges1515 bronze badges

The easiest workaround right now is probably something like:

rs = df.resample('30min')
rs[rs.index.dayofweek < 5]

answered Feb 17, 2013 at 3:12

17k88 gold badges4343 silver badges2626 bronze badges

Probably the simplest way is to just do a dropna afterwards to get rid of the empty rows, e.g.

df.resample('30Min').dropna()

answered Sep 26, 2014 at 2:22

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