resample ohlc 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)

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