我有一个熊猫时间序列,看起来像这样:
<>之前
2012-01-01 00:00:00.250000 12
2012-01-01 00:00:00.257000 34
2012-01-01 00:00:00.258000 45
2012-01-01 00:00:01.350000 56
2012-01-01 00:00:02.300000 78
2012-01-01 00:00:03.200000 89
2012-01-01 00:00:03.500000 90
2012-01-01 00:00:04.200000 12
之前是否有一种方法可以在不对齐1秒边界的情况下将其采样到1秒数据?例如,是否有一种方法可以获得这些数据(假设使用采样时间之前或之后的最新值进行downsampling):
<>之前
2012-01-01 00:00:00.250000 12
2012-01-01 00:00:01.250000 45
2012-01-01 00:00:02.250000 56
2012-01-01 00:00:03.250000 89
2012-01-01 00:00:04.250000 12
创建一个DateTimeIndex,频率为1秒,偏移量为1/4秒,如下所示
index = pd.date_range('2012-01-01 00:00:00.25',
'2012-01-01 00:00:04.25', freq='S')
让你的数据符合这个索引,并"向前填写"以在你想要的结果中显示的方式向下抽样。
s.reindex(index, method='ffill')
data
2012-01-01 00:00:00.250000 12
2012-01-01 00:00:01.250000 45
2012-01-01 00:00:02.250000 56
2012-01-01 00:00:03.250000 89
2012-01-01 00:00:04.250000 12