temporalAdd

Syntax

temporalAdd(obj, duration, unit)

Alias: datetimeAdd

Arguments

obj is a temporal scalar/pair/vector.

duration is an integer.

unit is a STRING vector.

  • When parameter duration is an integer, unit is:

    • the unit of parameter duration. It can be “ns”(nanosecond), “us”(microsecond), “ms”( millisecond), “s”(second), “m”(minute), “H”(hour), “d”(day), “w”(week), “M”(month), “y”( year), or “B”(business day).

    • the identifier of trading calendar, e.g., the Market Identifier Code of an exchange, or a user-defined calendar name. The corresponding file must be saved in marketHolidayDir.

  • When duration is of DURATION type, this parameter is not required.

Note: When unit is “y” or “M”, the result is consistent with mysql. Pandas provides an offset object Dateoffsets to move dates forward a given number of valid dates. When the DateOffset parameter is specified as months or years, the result is also consistent with temporalAdd.

Details

Add a value to a temporal variable.

Examples

$ temporalAdd(2017.01.16,1,"d");
2017.01.17

$ temporalAdd(2017.01.16,1,"w");
2017.01.23

$ temporalAdd(2016.12M,2,"M");
2017.02M

$ temporalAdd(2012.07.31T13:30:10.008,-1,'M');
2012.06.30T13:30:10.008

$ temporalAdd(2012.07.31T13:30:10.008,1,'y');
2013.07.31T13:30:10.008

$ temporalAdd(13:30:10.008007006,100,"ns");
13:30:10.008007106

$ x=[12:23:34, 23:34:45];
$ temporalAdd(x, 10m);
[12:33:34,23:44:45]

Add four business days to 2021.08.06.

$ temporalAdd(2021.08.06, 4B)
2021.08.12

Add 2 trading days for “date” according to the trading calendar CFFEX.

$ date=[2023.01.01, 2023.01.02, 2023.01.03, 2023.01.04]
$ temporalAdd(date,2,`CFFEX)
[2023.01.04,2023.01.04,2023.01.05,2023.01.06]

$ temporalAdd(datetime(2020.08.31), -2M)
2020.06.30T00:00:00

//The result is the same as setting months=2 in pandas *DateOffset*.
$ pd1 = pd.Timestamp("2020.08.31")
$ print(pd1 -pd.offsets.DateOffset(months=2))
2020-06-30 00:00:00

$ temporalAdd(datetime(2020.02.29), -1y)
2019.02.28T00:00:00
$ temporalAdd(datetime(2020.02.29), -4y)
2016.02.29T00:00:00

//The result is the same as setting years=1 in pandas *DateOffset*.
$ pd1 = pd.Timestamp("2020.02.29")
$ print(pd1 - pd.offsets.DateOffset(years=1))
2019-02-28 00:00:00

//The result is the same as setting years=4 in pandas *DateOffset*.
$ pd2 = pd.Timestamp("2020.02.29")
$ print(pd2 - pd.offsets.DateOffset(years=4))
2016-02-29 00:00:00