如何在9点、12点和18点在pandasper day中创建自定义频率
How to create a custom frequency in pandasper day at 9, 12 and 18 o'clock
我了解如何创建 pandas 频率,如 python3:
import pandas as pd
import datetime
idx = pd.date_range('2017-01-01' ,'2017-06-16', freq='D')
ts = pd.Series(range(len(idx)), index=idx)
ts
对于9点12点和18点的不规则采样小时数据,我将如何做?
你可以试试:
idx = pd.date_range('2017-01-01' ,'2017-06-16', freq='H')
idx = idx[idx.hour.isin([9,12,18])]
ts = pd.Series(range(len(idx)), index=idx)
输出:
2017-01-01 09:00:00 0
2017-01-01 12:00:00 1
2017-01-01 18:00:00 2
2017-01-02 09:00:00 3
2017-01-02 12:00:00 4
...
2017-06-14 12:00:00 493
2017-06-14 18:00:00 494
2017-06-15 09:00:00 495
2017-06-15 12:00:00 496
2017-06-15 18:00:00 497
Length: 498, dtype: int64
我了解如何创建 pandas 频率,如 python3:
import pandas as pd
import datetime
idx = pd.date_range('2017-01-01' ,'2017-06-16', freq='D')
ts = pd.Series(range(len(idx)), index=idx)
ts
对于9点12点和18点的不规则采样小时数据,我将如何做?
你可以试试:
idx = pd.date_range('2017-01-01' ,'2017-06-16', freq='H')
idx = idx[idx.hour.isin([9,12,18])]
ts = pd.Series(range(len(idx)), index=idx)
输出:
2017-01-01 09:00:00 0
2017-01-01 12:00:00 1
2017-01-01 18:00:00 2
2017-01-02 09:00:00 3
2017-01-02 12:00:00 4
...
2017-06-14 12:00:00 493
2017-06-14 18:00:00 494
2017-06-15 09:00:00 495
2017-06-15 12:00:00 496
2017-06-15 18:00:00 497
Length: 498, dtype: int64