mars.dataframe.
date_range
Return a fixed frequency DatetimeIndex.
start (str or datetime-like, optional) – Left bound for generating dates.
end (str or datetime-like, optional) – Right bound for generating dates.
periods (int, optional) – Number of periods to generate.
freq (str or DateOffset, default 'D') – Frequency strings can have multiples, e.g. ‘5H’. See here for a list of frequency aliases.
tz (str or tzinfo, optional) – Time zone name for returning localized DatetimeIndex, for example ‘Asia/Hong_Kong’. By default, the resulting DatetimeIndex is timezone-naive.
normalize (bool, default False) – Normalize start/end dates to midnight before generating date range.
name (str, default None) – Name of the resulting DatetimeIndex.
closed ({None, 'left', 'right'}, optional) – Make the interval closed with respect to the given frequency to the ‘left’, ‘right’, or both sides (None, the default).
**kwargs – For compatibility. Has no effect on the result.
rng
DatetimeIndex
See also
An immutable container for datetimes.
timedelta_range
Return a fixed frequency TimedeltaIndex.
period_range
Return a fixed frequency PeriodIndex.
interval_range
Return a fixed frequency IntervalIndex.
Notes
Of the four parameters start, end, periods, and freq, exactly three must be specified. If freq is omitted, the resulting DatetimeIndex will have periods linearly spaced elements between start and end (closed on both sides).
start
end
periods
freq
To learn more about the frequency strings, please see this link.
Examples
Specifying the values
The next four examples generate the same DatetimeIndex, but vary the combination of start, end and periods.
Specify start and end, with the default daily frequency. >>> import mars.dataframe as md
>>> md.date_range(start='1/1/2018', end='1/08/2018').execute() 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')
Specify start and periods, the number of periods (days).
>>> md.date_range(start='1/1/2018', periods=8).execute() 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')
Specify end and periods, the number of periods (days).
>>> md.date_range(end='1/1/2018', periods=8).execute() DatetimeIndex(['2017-12-25', '2017-12-26', '2017-12-27', '2017-12-28', '2017-12-29', '2017-12-30', '2017-12-31', '2018-01-01'], dtype='datetime64[ns]', freq='D')
Specify start, end, and periods; the frequency is generated automatically (linearly spaced).
>>> md.date_range(start='2018-04-24', end='2018-04-27', periods=3).execute() DatetimeIndex(['2018-04-24 00:00:00', '2018-04-25 12:00:00', '2018-04-27 00:00:00'], dtype='datetime64[ns]', freq=None)
Other Parameters
Changed the freq (frequency) to 'M' (month end frequency).
'M'
>>> md.date_range(start='1/1/2018', periods=5, freq='M').execute() DatetimeIndex(['2018-01-31', '2018-02-28', '2018-03-31', '2018-04-30', '2018-05-31'], dtype='datetime64[ns]', freq='M')
Multiples are allowed
>>> md.date_range(start='1/1/2018', periods=5, freq='3M').execute() DatetimeIndex(['2018-01-31', '2018-04-30', '2018-07-31', '2018-10-31', '2019-01-31'], dtype='datetime64[ns]', freq='3M')
freq can also be specified as an Offset object.
>>> md.date_range(start='1/1/2018', periods=5, freq=md.offsets.MonthEnd(3)).execute() DatetimeIndex(['2018-01-31', '2018-04-30', '2018-07-31', '2018-10-31', '2019-01-31'], dtype='datetime64[ns]', freq='3M')
Specify tz to set the timezone.
>>> md.date_range(start='1/1/2018', periods=5, tz='Asia/Tokyo').execute() 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')
closed controls whether to include start and end that are on the boundary. The default includes boundary points on either end.
>>> md.date_range(start='2017-01-01', end='2017-01-04', closed=None).execute() DatetimeIndex(['2017-01-01', '2017-01-02', '2017-01-03', '2017-01-04'], dtype='datetime64[ns]', freq='D')
Use closed='left' to exclude end if it falls on the boundary.
closed='left'
>>> md.date_range(start='2017-01-01', end='2017-01-04', closed='left').execute() DatetimeIndex(['2017-01-01', '2017-01-02', '2017-01-03'], dtype='datetime64[ns]', freq='D')
Use closed='right' to exclude start if it falls on the boundary.
closed='right'
>>> md.date_range(start='2017-01-01', end='2017-01-04', closed='right').execute() DatetimeIndex(['2017-01-02', '2017-01-03', '2017-01-04'], dtype='datetime64[ns]', freq='D')