SQL - spread previous values from one column into multiple new columns - sql

Question

I have a SQL table of Customer_ID, showing Payments by Year. The first (of many) customer appears like this:
ID Payment Year
112 0 2004
112 0 2005
112 0 2006
112 9592 2007
112 12332 2008
112 9234 2011
112 5400 2012
112 7392 2014
112 8321 2015
Note that some years are missing. I need to create 10 new columns, showing the Payments in the previous 10 years, for each row. The resulting table should look like this:
ID Payment Year T-1 T-2 T-3 T-4 T-5 T-6 T-7 T-8 T-9 T-10
112 0 2004 NULL NULL NULL NULL NULL NULL NULL NULL NULL NULL
112 0 2005 0 NULL NULL NULL NULL NULL NULL NULL NULL NULL
112 0 2006 0 0 NULL NULL NULL NULL NULL NULL NULL NULL
112 952 2007 0 0 0 NULL NULL NULL NULL NULL NULL NULL
112 1232 2008 952 0 0 0 NULL NULL NULL NULL NULL NULL
112 924 2011 NULL NULL 1232 952 0 0 0 NULL NULL NULL
112 500 2012 924 NULL NULL 1232 952 0 0 0 NULL NULL
112 392 2014 NULL 500 924 NULL NULL 1232 952 0 0 0
112 821 2015 392 NULL 500 924 NULL NULL 1232 952 0 0
I am well aware that this is a large duplication of data, and so seems like a strange thing to do. However, I would still like to do it! (the data is being prepared for a predictive model, in which previous payments (and other info) will be used to predict the current year's payment)
I'm not really sure where to start with this. I have been looking at using pivot, but can't figure out how to get it to select values from a customer's previous year.
I would very much like to do this in SQL. If that is not possible I may be able to copy the table into R - but SQL is my preference.
Any help much appreciated.

Answer 1

You could use lag() if you had full data:
select t.*,
lag(payment, 1) over (partition by id order by year) as t_1,
lag(payment, 2) over (partition by id order by year) as t_2,
. . .
from t;
However, for your situation with missing intermediate years, left join may be simpler:
select t.*,
t1.payment as t_1,
t2.payment as t_2,
. . .
from t left join
t t1
on t1.id = t.id and
t1.year = t.year - 1 left join
t t2
on t1.id = t.id and
t1.year = t.year - 2 left join
. . .;

Answer 2

I thnk your friend will be LAG
Here's an implementation:
Declare #t table (
ID int,
Payment int,
Yr int
)
Insert Into #t Values(112,0,2004)
Insert Into #t Values(112,0,2005)
Insert Into #t Values(112,0,2006)
Insert Into #t Values(112,9592,2007)
Insert Into #t Values(112,12332,2008)
Insert Into #t Values(112,9234,2011)
Insert Into #t Values(112,5400,2012)
Insert Into #t Values(112,7392,2014)
Insert Into #t Values(112,8321,2015)
Insert Into #t Values(113,0,2009)
Insert Into #t Values(113,9234,2011)
Insert Into #t Values(113,5400,2013)
Insert Into #t Values(113,8321,2015)
;with E1(n) as (Select 1 Union All Select 1 Union All Select 1 Union All Select 1 Union All Select 1 Union All Select 1 Union All Select 1 Union All Select 1 Union All Select 1 Union All Select 1)
,E2(n) as (Select 1 From E1 a, E1 b)
,E4(n) as (Select 1 From E2 a, E2 b)
,E5(n) as (Select row_number() over(order by isnull(null,1)) From E4 a, E1 b)
,IDYears as (
Select z.ID, Yr = y.n
From (
Select
Id,
MinYear = min(Yr),
MaxYear = max(Yr)
From #t a
Group By Id
) z
Inner Join E5 y On y.n between z.MinYear and z.MaxYear
)
Select
*,
[t-1] = Lag(B.Payment, 1) Over(Partition By a.ID Order By a.Yr),
[t-2] = Lag(B.Payment, 2) Over(Partition By a.ID Order By a.Yr),
[t-3] = Lag(B.Payment, 3) Over(Partition By a.ID Order By a.Yr),
[t-4] = Lag(B.Payment, 4) Over(Partition By a.ID Order By a.Yr),
[t-5] = Lag(B.Payment, 5) Over(Partition By a.ID Order By a.Yr),
[t-6] = Lag(B.Payment, 6) Over(Partition By a.ID Order By a.Yr),
[t-7] = Lag(B.Payment, 7) Over(Partition By a.ID Order By a.Yr),
[t-8] = Lag(B.Payment, 8) Over(Partition By a.ID Order By a.Yr),
[t-9] = Lag(B.Payment, 9) Over(Partition By a.ID Order By a.Yr),
[t-10] = Lag(B.Payment, 10) Over(Partition By a.ID Order By a.Yr)
From IDYears a
Left Join #t b On a.ID = b.ID and a.Yr = b.Yr
Order By A.ID