pandas resample timeframe code example
Example 1: how i resamplae a datetime column in python
>>> d = dict({'price': [10, 11, 9, 13, 14, 18, 17, 19],
... 'volume': [50, 60, 40, 100, 50, 100, 40, 50]})
>>> df = pd.DataFrame(d)
>>> df['week_starting'] = pd.date_range('01/01/2018',
... periods=8,
... freq='W')
>>> df
price volume week_starting
0 10 50 2018-01-07
1 11 60 2018-01-14
2 9 40 2018-01-21
3 13 100 2018-01-28
4 14 50 2018-02-04
5 18 100 2018-02-11
6 17 40 2018-02-18
7 19 50 2018-02-25
>>> df.resample('M', on='week_starting').mean()
price volume
week_starting
2018-01-31 10.75 62.5
2018-02-28 17.00 60.0
Example 2: resample 5 minutes on date
df['timestamps'] = pd.to_datetime(df['timestamps'])
df.set_index('timestamps', inplace=True)
>>> df.resample('5T', how=ohlc_dict)
high close open low volume
timestamps
2016-08-09 12:35:00 536.7849 536.7849 536.7841 536.6141 0.656000
2016-08-09 12:40:00 536.6749 534.8416 536.6749 534.1801 2.277200
2016-08-09 12:45:00 538.5999 537.7289 534.8131 534.2303 2.971872
2016-08-09 12:50:00 539.2199 539.2199 537.9829 537.9829 1.115219
Example 3: pandas resample documentation
B business day frequency
C custom business day frequency (experimental)
D calendar day frequency
W weekly frequency
M month end frequency
SM semi-month end frequency (15th and end of month)
BM business month end frequency
CBM custom business month end frequency
MS month start frequency
SMS semi-month start frequency (1st and 15th)
BMS business month start frequency
CBMS custom business month start frequency
Q quarter end frequency
BQ business quarter endfrequency
QS quarter start frequency
BQS business quarter start frequency
A year end frequency
BA, BY business year end frequency
AS, YS year start frequency
BAS, BYS business year start frequency
BH business hour frequency
H hourly frequency
T, min minutely frequency
S secondly frequency
L, ms milliseconds
U, us microseconds
N nanoseconds