pandas.tseries.offsets.
DateOffset
Standard kind of date increment used for a date range.
Works exactly like relativedelta in terms of the keyword args you pass in, use of the keyword n is discouraged– you would be better off specifying n in the keywords you use, but regardless it is there for you. n is needed for DateOffset subclasses.
DateOffset work as follows. Each offset specify a set of dates that conform to the DateOffset. For example, Bday defines this set to be the set of dates that are weekdays (M-F). To test if a date is in the set of a DateOffset dateOffset we can use the is_on_offset method: dateOffset.is_on_offset(date).
If a date is not on a valid date, the rollback and rollforward methods can be used to roll the date to the nearest valid date before/after the date.
DateOffsets can be created to move dates forward a given number of valid dates. For example, Bday(2) can be added to a date to move it two business days forward. If the date does not start on a valid date, first it is moved to a valid date. Thus pseudo code is:
date = rollback(date) # does nothing if date is valid return date + <n number of periods>
When a date offset is created for a negative number of periods, the date is first rolled forward. The pseudo code is:
date = rollforward(date) # does nothing is date is valid return date + <n number of periods>
Zero presents a problem. Should it roll forward or back? We arbitrarily have it rollforward:
date + BDay(0) == BDay.rollforward(date)
Since 0 is a bit weird, we suggest avoiding its use.
The number of time periods the offset represents.
Whether to round the result of a DateOffset addition down to the previous midnight.
Temporal parameter that add to or replace the offset value.
Parameters that add to the offset (like Timedelta):
years
months
weeks
days
hours
minutes
seconds
microseconds
nanoseconds
Parameters that replace the offset value:
year
month
day
weekday
hour
minute
second
microsecond
nanosecond.
See also
dateutil.relativedelta.relativedelta
The relativedelta type is designed to be applied to an existing datetime an can replace specific components of that datetime, or represents an interval of time.
Examples
>>> from pandas.tseries.offsets import DateOffset >>> ts = pd.Timestamp('2017-01-01 09:10:11') >>> ts + DateOffset(months=3) Timestamp('2017-04-01 09:10:11')
>>> ts = pd.Timestamp('2017-01-01 09:10:11') >>> ts + DateOffset(months=2) Timestamp('2017-03-01 09:10:11')
Attributes
base
Returns a copy of the calling offset object with n=1 and all other attributes equal.
freqstr
kwds
n
name
nanos
normalize
rule_code
Methods
__call__(*args, **kwargs)
__call__
Call self as a function.
rollback
Roll provided date backward to next offset only if not on offset.
rollforward
Roll provided date forward to next offset only if not on offset.
apply
apply_index
copy
isAnchored
is_anchored
is_on_offset
onOffset