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pythonpython-3.xpandasdate-range

How to create a pandas DatetimeIndex with year as frequency?

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.

  • 's' : second
  • 'min' : minute
  • 'H' : hour
  • 'D' : day
  • 'w' : week
  • 'm' : month

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?

Solution

  • Annual indexing to the beginning or end of the year

    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)

    Annual indexing to the beginning of an arbitrary month

    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)

    Annual indexing from an arbitrary date

    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)