resample pandas

1df.resample("W").agg(['min','max','mean','std'])
2
3#  resample("3T") ==> 3 minutes
4#  resample("30S") ==> 30 seconds
5#  resample("1H") ==> 1 hour
6#  resample("D") ==> day
7#  resample("W") ==> week
8#  resample("M") ==> month
9#  resample("Y") ==> year  
10#  resample("Q") ==> quarter
11#  Ex. 2018-01-01 ==> 2018-03-01 , 2018-06-01 , 2018-09-01 , 2018-12-01 
12#####################################
13#  .mean() 
14#  .max()
15#  .min() 
16#  .sum()
17......
18#  .agg(['min','max',...]) specified functions are applied for every column

1In [101]: df.resample('1H').agg({'openbid': 'first', 
2                                 'highbid': 'max', 
3                                 'lowbid': 'min', 
4                                 'closebid': 'last'})
5Out[101]: 
6                      lowbid  highbid  closebid  openbid
7ctime                                                   
82015-09-30 23:00:00  1.11687  1.11712   1.11708    1.117
9

1#We can also use custom functions and apply them when resampling using the .apply(method_name) method
2#This is an example used in a downsampling example
3def custom_resampler(arraylike):
4    return np.sum(arraylike) + 5
5data.resample('Q').apply(custom_resampler)

1>>> d = dict({'price': [10, 11, 9, 13, 14, 18, 17, 19],
2...           'volume': [50, 60, 40, 100, 50, 100, 40, 50]})
3>>> df = pd.DataFrame(d)
4>>> df['week_starting'] = pd.date_range('01/01/2018',
5...                                     periods=8,
6...                                     freq='W')
7>>> df
8   price  volume week_starting
90     10      50    2018-01-07
101     11      60    2018-01-14
112      9      40    2018-01-21
123     13     100    2018-01-28
134     14      50    2018-02-04
145     18     100    2018-02-11
156     17      40    2018-02-18
167     19      50    2018-02-25
17# try below code when you want resample on datetime column to other all columns in dataframe
18>>> df.resample('M', on='week_starting').mean() 
19               price  volume
20week_starting
212018-01-31     10.75    62.5
222018-02-28     17.00    60.0
23

1B         business day frequency
2C         custom business day frequency (experimental)
3D         calendar day frequency
4W         weekly frequency
5M         month end frequency
6SM        semi-month end frequency (15th and end of month)
7BM        business month end frequency
8CBM       custom business month end frequency
9MS        month start frequency
10SMS       semi-month start frequency (1st and 15th)
11BMS       business month start frequency
12CBMS      custom business month start frequency
13Q         quarter end frequency
14BQ        business quarter endfrequency
15QS        quarter start frequency
16BQS       business quarter start frequency
17A         year end frequency
18BA, BY    business year end frequency
19AS, YS    year start frequency
20BAS, BYS  business year start frequency
21BH        business hour frequency
22H         hourly frequency
23T, min    minutely frequency
24S         secondly frequency
25L, ms     milliseconds
26U, us     microseconds
27N         nanoseconds

1data_ask_bid=pd.concat([data_ask, data_bid], axis=1, keys=['Ask', 'Bid'])