pandas.tseries.offsets.MonthBegin

classpandas.tseries.offsets.MonthBegin

DateOffset of one month at beginning.

MonthBegin goes to the next date which is a start of the month.

Parameters:

n:int, default 1

The number of months represented.

normalize:bool, default False

Normalize start/end dates to midnight before generating date range.

See also

DateOffset

Standard kind of date increment.

Examples

>>> ts = pd.Timestamp(2022, 11, 30)
>>> ts + pd.offsets.MonthBegin()
Timestamp('2022-12-01 00:00:00')

>>> ts = pd.Timestamp(2022, 12, 1)
>>> ts + pd.offsets.MonthBegin()
Timestamp('2023-01-01 00:00:00')

If you want to get the start of the current month:

>>> ts = pd.Timestamp(2022, 12, 1)
>>> pd.offsets.MonthBegin().rollback(ts)
Timestamp('2022-12-01 00:00:00')

Attributes

base	Returns a copy of the calling offset object with n=1 and all other attributes equal.
freqstr	Return a string representing the frequency.
kwds	Return a dict of extra parameters for the offset.
n
name	Return a string representing the base frequency.
nanos
normalize
rule_code

Methods

copy()	Return a copy of the frequency.
is_anchored()	(DEPRECATED) Return boolean whether the frequency is a unit frequency (n=1).
is_month_end(ts)	Return boolean whether a timestamp occurs on the month end.
is_month_start(ts)	Return boolean whether a timestamp occurs on the month start.
is_on_offset(dt)	Return boolean whether a timestamp intersects with this frequency.
is_quarter_end(ts)	Return boolean whether a timestamp occurs on the quarter end.
is_quarter_start(ts)	Return boolean whether a timestamp occurs on the quarter start.
is_year_end(ts)	Return boolean whether a timestamp occurs on the year end.
is_year_start(ts)	Return boolean whether a timestamp occurs on the year start.
rollback(dt)	Roll provided date backward to next offset only if not on offset.
rollforward(dt)	Roll provided date forward to next offset only if not on offset.