pandas.date_range(start=None, end=None, periods=None, 
freq=None, tz=None, normalize=False, name=None, closed=None, **kwargs)

:param start: 开始时间 str or datetime-like 
:param end: 结束时间 str or datetime-like 
:param periods: 要生成的周期数
:param freq: 频率  str or DateOffset
:param tz: str or tzinfo 返回本地化DatetimeIndex的时区名称，
例如“Asia / Hong_Kong”
:param normalize: bool 默认为False 在生成日期范围之前将开始/结束日期标准化为午夜
:param name: str 生成的DatetimeIndex的名称
:param closed: {None, ‘left’, ‘right’} 给定时间区间的闭合
:return:时间序列 DatetimeIndex

生成时间序列

>>> pd.date_range(start='1/1/2018', end='1/08/2018')
DatetimeIndex(['2018-01-01', '2018-01-02', '2018-01-03', '2018-01-04',
               '2018-01-05', '2018-01-06', '2018-01-07', '2018-01-08'],
              dtype='datetime64[ns]', freq='D')

指定start和periods, periods为期间数

>>> pd.date_range(start='1/1/2018', periods=8)
DatetimeIndex(['2018-01-01', '2018-01-02', '2018-01-03', '2018-01-04',
               '2018-01-05', '2018-01-06', '2018-01-07', '2018-01-08'],
              dtype='datetime64[ns]', freq='D')

指定start, end, and periods;

>>> pd.date_range(start='2019-01-01', end='2019-07-03', periods=10)
DatetimeIndex(['2019-01-01 00:00:00', '2019-01-21 08:00:00',
               '2019-02-10 16:00:00', '2019-03-03 00:00:00',
               '2019-03-23 08:00:00', '2019-04-12 16:00:00',
               '2019-05-03 00:00:00', '2019-05-23 08:00:00',
               '2019-06-12 16:00:00', '2019-07-03 00:00:00'],
              dtype='datetime64[ns]', freq=None)

指定freq频率

pd.date_range(start='2019-01-01', end='2019-07-03',  freq='M')
DatetimeIndex(['2019-01-31', '2019-02-28',   
              '2019-03-31', '2019-04-30',
              '2019-05-31', '2019-06-30'],
              dtype='datetime64[ns]', freq='M')

指定tz设置时区

>>> pd.date_range(start='1/1/2018', periods=5, tz='Asia/Tokyo')
DatetimeIndex(['2018-01-01 00:00:00+09:00', '2018-01-02 00:00:00+09:00',
               '2018-01-03 00:00:00+09:00', '2018-01-04 00:00:00+09:00',
               '2018-01-05 00:00:00+09:00'],
              dtype='datetime64[ns, Asia/Tokyo]', freq='D')

使用closed='left'排除结束，如果它落在界上

>>> pd.date_range(start='2017-01-01', end='2017-01-04', closed='left')
DatetimeIndex(['2017-01-01', '2017-01-02', '2017-01-03'],
              dtype='datetime64[ns]', freq='D')

使用closed='right'排除启动，如果它落在界上

>>> pd.date_range(start='2017-01-01', end='2017-01-04', closed='right')
DatetimeIndex(['2017-01-02', '2017-01-03', '2017-01-04'],
              dtype='datetime64[ns]', freq='D')

freq参数参考