Using the pandas.date_range(startdate, periods=n, freq=f)
function you can create a range of pandas Timestamp
objects where the freq
optional paramter denotes the frequency (second, minute, hour, day...) in the range.
The documentation does not mention the literals that are expected to be passed in, but after a few minutes you can easily find most of them.
However, none of 'y', 'Y', 'yr', etc. create dates with year as frequency. Does anybody know what to pass in, or if it is possible at all?
Frequency is freq='A'
for end of year frequency, 'AS'
for start of year. Check the aliases in the documentation.
eg. pd.date_range(start=pd.datetime(2000, 1, 1), periods=4, freq='A')
returns
DatetimeIndex(['2000-12-31', '2001-12-31', '2002-12-31', '2003-12-31'], dtype='datetime64[ns]', freq='A-DEC', tz=None)
If you need it to be annual from a particular time use an anchored offset, eg. pd.date_range(start=pd.datetime(2000, 1, 1), periods=10, freq='AS-AUG')
returns
DatetimeIndex(['2000-08-01', '2001-08-01', '2002-08-01', '2003-08-01'], dtype='datetime64[ns]', freq='AS-AUG', tz=None)
To index from an arbitrary date, begin the series on that date and use a custom DateOffset
object.
eg. pd.date_range(start=pd.datetime(2000, 9, 10), periods=4, freq=pd.DateOffset(years=1))
returns
DatetimeIndex(['2000-09-10', '2001-09-10', '2002-09-10', '2003-09-10'], dtype='datetime64[ns]', freq='<DateOffset: kwds={'years': 1}>', tz=None)
With all those hacks, there is a clear way:
pd.date_range(start=datetime.datetime.now(),periods=5,freq='A')
A
: Annually.
365D
? Really? What about leap years?
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