Python Pandas 日期时间索引
Python Pandas DateTimeIndex
低于 DataFrame 的 DateTimeIndex。 Summer/Winter 时区是 'US/Eastern',但是记录的时间戳是 'Europe/London'。我正在尝试重新索引,这将实现完整的时间序列。
DatetimeIndex(['1993-10-24 21:00:00', '1993-10-25 21:00:00',
'1993-10-26 21:00:00', '1993-10-27 21:00:00',
'1993-10-28 21:00:00', '1993-10-31 22:00:00',
'1993-11-01 22:00:00', '1993-11-02 22:00:00',
'1993-11-03 22:00:00', '1993-11-04 22:00:00'],
dtype='datetime64[ns]', name=u'TIME', freq=None)
如何在不弄乱小时元素的情况下重新索引以上内容?
tidx = pd.DatetimeIndex(
[
'1993-10-24 21:00:00', '1993-10-25 21:00:00',
'1993-10-26 21:00:00', '1993-10-27 21:00:00',
'1993-10-28 21:00:00', '1993-10-31 22:00:00',
'1993-11-01 22:00:00', '1993-11-02 22:00:00',
'1993-11-03 22:00:00', '1993-11-04 22:00:00'],
dtype='datetime64[ns]', name=u'TIME', freq=None
)
ts = tidx.to_series().dt.hour.resample('D').last().ffill().rename_axis('date')
ts.index + pd.to_timedelta(ts.values, unit='H')
DatetimeIndex(['1993-10-24 21:00:00', '1993-10-25 21:00:00',
'1993-10-26 21:00:00', '1993-10-27 21:00:00',
'1993-10-28 21:00:00', '1993-10-29 21:00:00',
'1993-10-30 21:00:00', '1993-10-31 22:00:00',
'1993-11-01 22:00:00', '1993-11-02 22:00:00',
'1993-11-03 22:00:00', '1993-11-04 22:00:00'],
dtype='datetime64[ns]', freq=None)
低于 DataFrame 的 DateTimeIndex。 Summer/Winter 时区是 'US/Eastern',但是记录的时间戳是 'Europe/London'。我正在尝试重新索引,这将实现完整的时间序列。
DatetimeIndex(['1993-10-24 21:00:00', '1993-10-25 21:00:00',
'1993-10-26 21:00:00', '1993-10-27 21:00:00',
'1993-10-28 21:00:00', '1993-10-31 22:00:00',
'1993-11-01 22:00:00', '1993-11-02 22:00:00',
'1993-11-03 22:00:00', '1993-11-04 22:00:00'],
dtype='datetime64[ns]', name=u'TIME', freq=None)
如何在不弄乱小时元素的情况下重新索引以上内容?
tidx = pd.DatetimeIndex(
[
'1993-10-24 21:00:00', '1993-10-25 21:00:00',
'1993-10-26 21:00:00', '1993-10-27 21:00:00',
'1993-10-28 21:00:00', '1993-10-31 22:00:00',
'1993-11-01 22:00:00', '1993-11-02 22:00:00',
'1993-11-03 22:00:00', '1993-11-04 22:00:00'],
dtype='datetime64[ns]', name=u'TIME', freq=None
)
ts = tidx.to_series().dt.hour.resample('D').last().ffill().rename_axis('date')
ts.index + pd.to_timedelta(ts.values, unit='H')
DatetimeIndex(['1993-10-24 21:00:00', '1993-10-25 21:00:00',
'1993-10-26 21:00:00', '1993-10-27 21:00:00',
'1993-10-28 21:00:00', '1993-10-29 21:00:00',
'1993-10-30 21:00:00', '1993-10-31 22:00:00',
'1993-11-01 22:00:00', '1993-11-02 22:00:00',
'1993-11-03 22:00:00', '1993-11-04 22:00:00'],
dtype='datetime64[ns]', freq=None)