Pandas Df.resample With Column-specific Aggregation Function

With pandas.DataFrame.resample I can downsample a DataFrame: df.resample('3s', how='mean') This resamples a data frame with a datetime-like index such that all values within 3 sec

Solution 1:

You can use .agg after resample. With a dictionary, you can aggregate different columns with various functions.

Try this:

df.resample("3s").agg({'x':'sum','y':'mean','z':'last'})

Also, how is deprecated:

C:\Program Files\Anaconda3\lib\site-packages\ipykernel__main__.py:1: FutureWarning: how in .resample() is deprecated the new syntax is .resample(...).mean()

Solution 2:

Consider the dataframe df

np.random.seed([3,1415])tidx=pd.date_range('2017-01-01',periods=18,freq='S')df=pd.DataFrame(np.random.rand(len(tidx),3),tidx,list('XYZ'))print(df)XYZ2017-01-01 00:00:00  0.4449390.4075540.4601482017-01-01 00:00:01  0.4652390.4626910.0165452017-01-01 00:00:02  0.8504450.8177440.7779622017-01-01 00:00:03  0.7579830.9348290.8311042017-01-01 00:00:04  0.8798910.9268790.7215352017-01-01 00:00:05  0.1176420.1459060.1998442017-01-01 00:00:06  0.4375640.1007020.2787352017-01-01 00:00:07  0.6098620.0858230.8369972017-01-01 00:00:08  0.7396350.8660590.6912712017-01-01 00:00:09  0.3771850.2251460.4352802017-01-01 00:00:10  0.7009000.7009460.7964872017-01-01 00:00:11  0.0186880.7005660.9007492017-01-01 00:00:12  0.7648690.2532000.5480542017-01-01 00:00:13  0.7788830.6516760.1360972017-01-01 00:00:14  0.5448380.0350730.2750792017-01-01 00:00:15  0.7066850.7136140.7760502017-01-01 00:00:16  0.5423290.8365410.5381862017-01-01 00:00:17  0.1855230.6521510.746060

Use agg

df.resample('3S').agg(dict(X='sum',Y='mean',Z='last'))XYZ2017-01-01 00:00:00  1.7606240.5626630.7779622017-01-01 00:00:03  1.7555160.6692040.1998442017-01-01 00:00:06  1.7870610.3508610.6912712017-01-01 00:00:09  1.0967730.5422200.9007492017-01-01 00:00:12  2.0885900.3133160.2750792017-01-01 00:00:15  1.4345380.7341020.746060