fy5253
Syntax
fy5253(X, [weekday=0], [startingMonth=1], [nearest=true], [offset],
[n=1])
Arguments
X is a scalar/vector. Its data type can be DATE, DATETIME, TIMESTAMP, or NANOTIMESTAMP.
weekday (optional) is an integer between 0 and 6. 0 means Monday, 1 means Tuesday, …, and 6 means Sunday. The default value is 0.
startingMonth (optional) is an integer between 1 and 12 indicating the beginning month of a year. The default value is 1.
nearest (optional) is a Boolean value. The default value is true.
offset (optional) is a scalar with the same data type as X. It must be no greater than the minimum value in X. The default value is the minimum value in X.
n (optional) is a positive integer.The default value is 1.
Details
Using the 52-53 weeks in a fiscal year (4-4-5 calendar), it returns the start date of fiscal year which includes X.
-
If nearest=true, the last weekday which is closest to the last day of startingMonth will be used as the starting date of the fiscal year.
-
If nearest=false, the last weekday in startingMonth will be used as the starting date of the fiscal year.
If offset is specified, it means that starting from the offset, the result will be updated every n years. Note that offset can take effect only when n is greater than 1.
Examples
fy5253(2016.11.01,0,1,true);
// output
2016.02.01 // The Monday closest to 2016.01.31 is 2016.02.01
fy5253(2016.11.01,0,1,false);
// output
2016.01.25 // The last Monday in January 2016 is 2016.01.25
date=2011.10.25 2012.10.25 2013.10.25 2014.10.25 2015.10.25 2016.10.25 2017.10.25 2018.10.25 2019.10.25 2020.10.25
time = [09:34:07,09:36:42,09:36:51,09:36:59,09:32:47,09:35:26,09:34:16,09:34:26,09:38:12,09:38:13]
sym = take(`MSFT,10)
price= 49.6 29.46 29.52 30.02 174.97 175.23 50.76 50.32 51.29 52.38
qty = 2200 1900 2100 3200 6800 5400 1300 2500 8800 4500
t1 = table(date, time, sym, qty, price);
select avg(price),sum(qty) from t1 group by fy5253(date,0,1,true,2011.10.01,2);
fy5253_date | avg_price | sum_qty |
---|---|---|
2011.01.31 | 39.53 | 4100 |
2013.01.28 | 29.77 | 5300 |
2015.02.02 | 175.1 | 12200 |
2017.01.30 | 50.54 | 3800 |
2019.01.28 | 51.835 | 13300 |
Related function: fy5253Quarter