I am trying to group by dataset in three month groups, or quarters, but as I'm starting from an arbitrary date, I cannot use the quarter function in sas.
Example data below of what I have and quarter is the column I need to create in SAS.
The start date is always the same, so my initial quarter will be 3rd Sep 2018 - 3rd Dec 2018 and any active date falling in that quarter will be 1, then quarter 2 will be 3rd Dec 2018 - 3rd Mar 2019 and so on. This cannot be coded manually as the start date will change depending on the data, and the number of quarters could be up to 20+.
The code I have attempted so far is below
data test_Data_op;
set test_data end=eof;
%let j = 0;
%let start_date = start_Date;
if &start_Date. <= effective_dt < (&start_date. + 90) then quarter = &j.+1;
run;
This works and gives the first quarter correctly, but I can't figure out how to loop this for every following quarter? Any help will be greatly appreciated!
No need for a DO loop if you already have the start_date and actual event dates. Just count the number of months and divide by three. Use the continuous method of the INTCK() function to handle start dates that are not the first day of a month.
month_number=intck('month',&start_date,mydate,'cont')+1;
qtr_number=floor((month_number-1)/3)+1;
Based on the comment by #Lee. Edited to match the data from the screenshot.
The example shows that May 11 would be in the 3rd quarter since the seed date is September 3.
data have;
input mydate :yymmdd10.;
format mydate yymmddd10.;
datalines;
2018-09-13
2018-12-12
2019-05-11
;
run;
%let start_date='03sep2018'd;
data want;
set have;
quarter=floor(mod((yrdif(&start_date,mydate)*4),4))+1;
run;
If you want the number of quarters to extend beyond 4 (e.g. September 4, 2019 would be in quarter 5 rather than cycle back to 1), then remove the "mod" from the function:
quarter=floor(yrdif(&start_date,mydate)*4)+1;
The traditional use of quarter means a 3 month time period relative to Jan 1. Make sure your audience understands the phrase quarter in your data presentation actually means 3 months relative to some arbitrary starting point.
The funky quarter can be functionally computed from a months apart derived using a mix of INTCK for the baseline months computation and a logical expression for adjusting with relation to the day of the month of the start date. No loops required.
For example:
data have;
do startDate = '11feb2019'd ;
do effectiveDate = startDate to startDate + 21*90;
output;
end;
end;
format startDate effectiveDate yymmdd10.;
run;
data want;
set have;
qtr = 1
+ floor(
( intck ('month', startDate, effectiveDate)
-
(day(effectiveDate) < day(startDate))
)
/ 3
);
format qtr 4.;
run;
Extra
Comparing my method (qtr) to #Tom (qtr_number) for a range of startDates:
data have;
retain seq 0;
do startDate = '01jan1999'd to '15jan2001'd;
seq + 1;
do effectiveDate = startDate to startDate + 21*90;
output;
end;
end;
format startDate effectiveDate yymmdd10.;
run;
data want;
set have;
qtr = 1
+ floor( ( intck ('month', startDate, effectiveDate)
- (day(effectiveDate) < day(startDate))
) / 3 );
month_number=intck('month',startDate,effectiveDate,'cont')+1;
qtr_number=floor((month_number-1)/3)+1;
format qtr: month: 4.;
run;
options nocenter nodate nonumber;title;
ods listing;
proc print data=want;
where qtr ne qtr_number;
run;
dm 'output';
-------- OUTPUT ---------
effective month_ qtr_
Obs seq startDate Date qtr number number
56820 31 1999-01-31 1999-04-30 1 4 2
57186 31 1999-01-31 2000-04-30 5 16 6
57551 31 1999-01-31 2001-04-30 9 28 10
57916 31 1999-01-31 2002-04-30 13 40 14
58281 31 1999-01-31 2003-04-30 17 52 18
168391 90 1999-03-31 1999-06-30 1 4 2
168483 90 1999-03-31 1999-09-30 2 7 3
168757 90 1999-03-31 2000-06-30 5 16 6
168849 90 1999-03-31 2000-09-30 6 19 7
169122 90 1999-03-31 2001-06-30 9 28 10
169214 90 1999-03-31 2001-09-30 10 31 11
169487 90 1999-03-31 2002-06-30 13 40 14
169579 90 1999-03-31 2002-09-30 14 43 15
169852 90 1999-03-31 2003-06-30 17 52 18
169944 90 1999-03-31 2003-09-30 18 55 19
280510 149 1999-05-29 2001-02-28 7 22 8
280875 149 1999-05-29 2002-02-28 11 34 12
281240 149 1999-05-29 2003-02-28 15 46 16
282035 150 1999-05-30 2000-02-29 3 10 4
282400 150 1999-05-30 2001-02-28 7 22 8
282765 150 1999-05-30 2002-02-28 11 34 12
I have problem that I find very hard to solve:
I need to calculate a column R_t in SQL where for each row, the sum of the "previous" calculated values SUM(R_t-1) is required as input. The calculation is done grouped over a ProjectID column. I have no clue how to proceed.
The formula for the calculation I am trying to achieve is R_t = ([Contract value]t - SUM(R{t-1})) / [Remaining Hours]_t * [HoursRegistered]t where "t" denotes time and SUM(R{t-1}) is the sum of R_t from t = 0 to t-1.
Time is always consecutive and always begin in t = 0. But number of time periods may differ across [ProjectID], i.e. one project having t = {0,1,2} and another t = {0,1,2,3,4,5}. The time period will never "jump" from 5 to 7
The expected output (using the data from below is) for ProjectID 101 is
R_0 = (500,000 - 0) / 500 * 65 = 65,000
R_1 = (500,000 - (65,000)) / 435 * 100 = 100,000
R_2 = (500,000 - (65,000 + 100,000)) / 335 * 85 = 85,000
R_3 = (500,000 - (65,000 + 100,000 + 85,000)) / 250 * 69 = 69,000
etc...
This calculation is done for each ProjectID.
My question is how to formulate this in a SQL query? My first thought was to create a recursive CTE, but I am actually not sure it is the right way proceed. Recursive CTE is (from my understanding) made for handling more of hierarchical like structure, which this isn't really.
My other thought was to calculate the SUM(R_t-1) using windowed functions, ie SUM OVER (PARITION BY ORDER BY) with a LAG, but the recursiveness really gives me trouble and I run my head against the wall when I am trying.
Below a query for creating the input data
CREATE TABLE [dbo].[InputForRecursiveCalculation]
(
[Time] int NULL,
ProjectID [int],
ContractValue float,
ContractHours float,
HoursRegistered float,
RemainingHours float
)
GO
INSERT INTO [dbo].[InputForRecursiveCalculation]
(
[Time]
,[ProjectID]
,[ContractValue]
,[ContractHours]
,[HoursRegistered]
,[RemainingHours]
)
VALUES
(0,101,500000,500,65,500),
(1,101,500000,500,100,435),
(2,101,500000,500,85,335),
(3,101,500000,500,69,250),
(4,101,450000,650,100,331),
(5,101,450000,650,80,231),
(6,101,450000,650,90,151),
(7,101,450000,650,45,61),
(8,101,450000,650,16,16),
(0,110,120000,90,10,90),
(1,110,120000,90,10,80),
(2,110,130000,90,10,70),
(3,110,130000,90,10,60),
(4,110,130000,90,10,50),
(5,110,130000,90,10,40),
(6,110,130000,90,10,30),
(7,110,130000,90,10,20),
(8,110,130000,90,10,10)
GO
For those of you who dare downloading something from a complete stranger, I have created an Excel file demonstrating the calculation (please download the file as you will not be to see the actual formula in the HTML representation shown when first clicking the link):
https://www.dropbox.com/s/3rxz72lbvooyc4y/Calculation%20example.xlsx?dl=0
Best regards,
Victor
I think it will be usefull for you. There is additional column SumR that stands for sumarry of previest rows (for ProjectID)
;with recu as
(
select
Time,
ProjectId,
ContractValue,
ContractHours,
HoursRegistered,
RemainingHours,
cast((ContractValue - 0)*HoursRegistered/RemainingHours as numeric(15,0)) as R,
cast((ContractValue - 0)*HoursRegistered/RemainingHours as numeric(15,0)) as SumR
from
InputForRecursiveCalculation
where
Time=0
union all
select
input.Time,
input.ProjectId,
input.ContractValue,
input.ContractHours,
input.HoursRegistered,
input.RemainingHours,
cast((input.ContractValue - prev.SumR)*input.HoursRegistered/input.RemainingHours as numeric(15,0)),
cast((input.ContractValue - prev.SumR)*input.HoursRegistered/input.RemainingHours + prev.SumR as numeric(15,0))
from
recu prev
inner join
InputForRecursiveCalculation input
on input.ProjectId = prev.ProjectId
and input.Time = prev.Time + 1
)
select
*
from
recu
order by
ProjectID,
Time
RESULTS:
Time ProjectId ContractValue ContractHours HoursRegistered RemainingHours R SumR
----------- ----------- ---------------------- ---------------------- ---------------------- ---------------------- --------------------------------------- ---------------------------------------
0 101 500000 500 65 500 65000 65000
1 101 500000 500 100 435 100000 165000
2 101 500000 500 85 335 85000 250000
3 101 500000 500 69 250 69000 319000
4 101 450000 650 100 331 39577 358577
5 101 450000 650 80 231 31662 390239
6 101 450000 650 90 151 35619 425858
7 101 450000 650 45 61 17810 443668
8 101 450000 650 16 16 6332 450000
0 110 120000 90 10 90 13333 13333
1 110 120000 90 10 80 13333 26666
2 110 130000 90 10 70 14762 41428
3 110 130000 90 10 60 14762 56190
4 110 130000 90 10 50 14762 70952
5 110 130000 90 10 40 14762 85714
6 110 130000 90 10 30 14762 100476
7 110 130000 90 10 20 14762 115238
8 110 130000 90 10 10 14762 130000
Having some problems finding an answer to what I think is a simple query but I'm very green with SQL:
YR MO ID FLAG RETURN
2001 01 1 1 3.00
2001 02 1 2 4.00
2001 03 1 3 -1.00
2001 04 1 4 1.00
2001 05 1 5 1.00
2001 06 1 6 1.00
2001 07 1 7 1.00
2001 08 1 8 1.00
2001 09 1 9 1.00
2001 10 1 10 1.00
2001 11 1 11 2.00
2001 12 1 12 1.00
2002 12 2 3 1.00
2002 04 2 0 0.05
I'd like a new column next to sum the previous 12 RETURN values WHERE FLAG = 12. Any help is greatly appreciated!
The data will be sorted by ID, then Year, and Month so it should be order sequentially.
The output would be (3+4+-1+1+1+1+1+1+1+1+2+1) = 16
I'd like the output (16) in the FLAG=12 row
Maybe a Windowed Function would fit the bill here:
SELECT *, CASE WHEN FLAG = 12 THEN SUM([RETURN]) OVER (PARTITION BY ID ORDER BY YR, MO ROWS BETWEEN 12 PRECEDING AND CURRENT ROW) ELSE NULL END
FROM SomeTable
ORDER BY ID, YR, MO
So, there are a couple issues with what you are attempting. First, you will need to either programmatically or administratively (through the UI) create the new column; the select call will not do this for you. Next, you need to be sure you want that data in your schema as it will be very 'odd' to have a column that sums flagged values. It seems as if you want to know that result but don't necessarily need to store it. If that is true (or can be made true), then I would suggest creating a select call that uses the 'sum', 'order by ... desc' (this means you need to know the ordering) and 'limit 12' functions. Given any row where the Flag is 12, you should be able get the result you want with a single call.
Just another note, since you've mentioned two different DBMSs, make sure you validate the SQL against both; I'm fairly certain you can find a generic request that will work in both systems. Good luck.
I have a dataset in the below format:
Date 1 Date 1 Date 1 Date 2 Date 2 Date 3 Date 3
Product 1 10 20 10 5 10 20 30
Product 2 5 5 10 10 10 5 30
Product 3 30 10 5 10 30 30 40
Product 4 5 10 10 20 5 10 20
and I am trying to sum the sales of the products by the date, to create the below:
Date 1 Date 2 Date 3
Product 1 40 15 50
Product 3 45 40 70
Product 4 25 25 30
Product 2 20 20 35
The products in the second table will often be in a different order, so a simple SUMIF will not suffice.
I've attempted a combination of SUM, INDEX and MATCH, as well as SUM with nested IF function, but no amount of Googling or trial and error is getting me there. I keep just bringing back the values in one cell, but not managing to sum.
With the following setup:
I used the following formula
=SUMIF($B$1:$H$1,B$10,INDIRECT("$B" & MATCH($A11,$A$1:$A$5,0) & ":$H" &MATCH($A11,$A$1:$A$5,0)))
To get what was wanted. I put the formula in B11 and then copied across and Down
for a table on ms-sql2000 containing the following columns and numbers:
S_idJ_id Se_id B_id Status Count multiply
63 1000 16 12 1 10 2
64 1001 12 16 1 9 3
65 1002 17 12 1 10 2
66 1003 16 12 1 6 3
67 1004 12 16 1 10 2
I want to generate an classic asp script which will do the following for each row
where status=1 :
-multiply -> answer= multiply column 'count' with column 'multiply'
Then:
count the total answer and sum for each se_id like :
se_id total
12 47
16 38
17 20
and display on screen like
Rank se_id total
1 12 47
2 16 38
3 17 20
Condition:
if there are multiple equal total values then give the lower numbered se_id a priority for
getting a ranking and give the next higher numbered se_id the next number in rank
Any sample code in classic asp or advice is welcome on how to get this accomplished
'score' = source table.
if (EXISTS (select * from INFORMATION_SCHEMA.TABLES where TABLE_NAME = 'result_table'))
begin
drop table result_table;
end
select
rank = IDENTITY(INT,1,1),
se_id, sum(multiply * count) as total
into result_table
from score
where status = 1
group by se_id
order by total desc, se_id;
[Edit] Change query as answer on first comment