Counting number of cases within a case - sql

Question

I'm looking to count the number of people who spent a certain amount at a certain store in a certain year.
I tried making a nested CASE expression, the first that looks at transactions at a certain year, the second looking at the sum of a person's transaction to a certain store, but Oracle didn't like nested CASE expressions (unless I was doing it wrong).
From this SQL example:
CREATE TABLE table_name ( PersonId, StoreId, AmountSpent, Year) as
select 1, 1, 60, 2017 from dual union
select 1, 1, 50, 2017 from dual union
select 1, 2, 70, 2018 from dual union
select 2, 1, 10, 2017 from dual union
select 2, 1, 10, 2017 from dual union
select 2, 1, 200, 2018 from dual union
select 2, 2, 60, 2018 from dual union
select 2, 2, 60, 2018 from dual union
select 3, 1, 25, 2017 from dual union
select 3, 2, 200, 2017 from dual union
select 3, 2, 200, 2018 from dual;
Select
StoreId,
SUM(CASE WHEN Year = '2017'
THEN AmountSpent
ELSE 0
End) Year17,
SUM(CASE WHEN Year = '2018'
THEN AmountSpent
ELSE 0
End) Year18
FROM table_name
GROUP BY StoreId;
STOREID YEAR17 YEAR18
---------- ---------- ----------
1 145 200
2 200 330
Would someone be able to make an output like this? I think some numbers might be wrong, but it seems like most of the people get the gist of where I'm going.
+----+---------+------------+---------------------+-------------------+---------------------+---------------------+------------+-------------------+---------------------+
| | STOREID | Y17_INCOME | Y17_SPENT_BELOW_100 | Y17_SPENT_100_150 | Y17_SPENT_ABOVE_150 | Y18_INCOME | Y18_SPENT_BELOW_100 | Y18_SPENT_100_150 | Y18_SPENT_ABOVE_150 |
+----+---------+------------+---------------------+-------------------+---------------------+------------+---------------------+-------------------+---------------------+
| 1 | 1 | 145 | 2 | 1 | 0 | 200 | 2 | 0 | 1 |
+----+---------+------------+---------------------+-------------------+---------------------+---------------------+------------+-------------------+---------------------+
| 2 | 2 | 200 | 0 | 0 | 1 | 330 | 0 | 0 | 1 |
+----+---------+------------+---------------------+-------------------+---------------------+------------+---------------------+-------------------+---------------------+
Not sure if this is possible, but it would be great if so!

Answer 1

I don't think your data matches your expected output.
You need a subquery where you sum spendings of each person yearly for each store ( grouping by store & person). Then you will need to group only by store and use sum to retrieve income for given year. count + case + distinct is the key to count unique person ids that have spent money and assign them to amount spending group (one of three columns for each year).
Notice that yearXX_spending column already holds sum of amount spent by a person for a given store and year (and this is coming from subquery):
select
storeid
, sum(year17_spending) as y17_income
, count(distinct case when year17_spending < 100 then personid end) as y17_spent_below_100
, count(distinct case when year17_spending between 100 and 150 then personid end) as y17_spent_100_150
, count(distinct case when year17_spending > 150 then personid end) as y17_spent_above_150
, sum(year18_spending) as y18_income
, count(distinct case when year18_spending < 100 then personid end) as y18_spent_below_100
, count(distinct case when year18_spending between 100 and 150 then personid end) as y18_spent_100_150
, count(distinct case when year18_spending > 150 then personid end) as y18_spent_above_150
from (
select
storeid
, personid
, sum(case when year = 2017 then amountspent end) as year17_spending
, sum(case when year = 2018 then amountspent end) as year18_spending
from table_name
group by storeid, personid
) t
group by storeid
Output for your sample data:
+----+---------+------------+---------------------+-------------------+---------------------+---------------------+------------+-------------------+---------------------+
| | STOREID | Y17_INCOME | Y17_SPENT_BELOW_100 | Y17_SPENT_100_150 | Y17_SPENT_ABOVE_150 | Y18_INCOME | Y18_SPENT_BELOW_100 | Y18_SPENT_100_150 | Y18_SPENT_ABOVE_150 |
+----+---------+------------+---------------------+-------------------+---------------------+------------+---------------------+-------------------+---------------------+
| 1 | 1 | 145 | 2 | 1 | 0 | 200 | 2 | 0 | 1 |
+----+---------+------------+---------------------+-------------------+---------------------+---------------------+------------+-------------------+---------------------+
| 2 | 2 | 200 | 0 | 0 | 1 | 330 | 0 | 0 | 1 |
+----+---------+------------+---------------------+-------------------+---------------------+------------+---------------------+-------------------+---------------------+
Also note that by doing UNION when you are building sample data, you're getting rid of duplicates so that line:
select 2, 1, 10, 2017
goes to the table only once (not twice). If you mean to include everything without removing duplicates, use UNION ALL instead.

Answer 2

You can do store/person totals in an inline view, which on its own produces:
SELECT
StoreId,
PersonId,
Year,
SUM(AmountSpent) AS TotalSpent
FROM table_name
GROUP BY
StoreId,
PersonId,
Year
ORDER BY
StoreId,
Year,
PersonId;
STOREID PERSONID YEAR TOTALSPENT
---------- ---------- ---------- ----------
1 1 2017 110
1 2 2017 10
1 3 2017 25
1 2 2018 200
2 3 2017 200
2 1 2018 70
2 2 2018 60
2 3 2018 200
and then use multiple separate case expressions and aggregates in an outer query:
SELECT
StoreId,
SUM(CASE WHEN Year = '2017'
THEN TotalSpent
ELSE 0
END) Year17,
COUNT(CASE WHEN Year = '2017'
AND TotalSpent < 100
THEN TotalSpent
END) AS Year17lt100,
COUNT(CASE WHEN Year = '2017'
AND TotalSpent >= 100
AND TotalSpent < 150
THEN TotalSpent
END) AS Year17gte100lt150,
COUNT(CASE WHEN Year = '2017'
AND TotalSpent >= 150
THEN TotalSpent
END) AS Year17gte150,
SUM(CASE WHEN Year = '2018'
THEN TotalSpent
ELSE 0
END) Year18,
COUNT(CASE WHEN Year = '2018'
AND TotalSpent < 100
THEN TotalSpent
END) AS Year18lt100,
COUNT(CASE WHEN Year = '2018'
AND TotalSpent >= 100
AND TotalSpent < 150
THEN TotalSpent
END) AS Year18gte100lt150,
COUNT(CASE WHEN Year = '2017'
AND TotalSpent >= 150
THEN TotalSpent
END) AS Year18gte150
FROM (
SELECT
StoreId,
PersonId,
Year,
SUM(AmountSpent) AS TotalSpent
FROM table_name
GROUP BY
StoreId,
PersonId,
Year
)
GROUP BY StoreId
ORDER BY StoreId;
which gets:
STOREID YEAR17 YEAR17LT100 YEAR17GTE100LT150 YEAR17GTE150 YEAR18 YEAR18LT100 YEAR18GTE100LT150 YEAR18GTE150
---------- ---------- ----------- ----------------- ------------ ---------- ----------- ----------------- ------------
1 145 2 1 0 200 0 0 0
2 200 0 0 1 330 2 0 1
That doesn't match the output in your image, but I think that's wrong...
I've also changed the buckets slightly from what your column headings suggested, but you can tweak those if you do really want what you showed.
You could also reduce the code and repetition by using a pivot() clause, if you're on a version of Oracle which supports that; which can provide multiple outputs and allows conditional aggregation too:
SELECT *
FROM (
SELECT
StoreId,
Year,
SUM(AmountSpent) AS TotalSpent
FROM table_name
GROUP BY
StoreId,
PersonId,
Year
)
PIVOT (
SUM(TotalSpent) as total,
COUNT(CASE WHEN TotalSpent < 100 THEN TotalSpent END) as lt100,
COUNT(CASE WHEN TotalSpent >= 100 AND TotalSpent < 150 THEN TotalSpent END) as gte100lt150,
COUNT(CASE WHEN TotalSpent >= 150 THEN TotalSpent END) as gte150
FOR Year IN (2017 as year17, 2018 as year18)
)
ORDER BY StoreId;
STOREID YEAR17_TOTAL YEAR17_LT100 YEAR17_GTE100LT150 YEAR17_GTE150 YEAR18_TOTAL YEAR18_LT100 YEAR18_GTE100LT150 YEAR18_GTE150
---------- ------------ ------------ ------------------ ------------- ------------ ------------ ------------------ -------------
1 145 2 1 0 200 0 0 1
2 200 0 0 1 330 2 0 1
Oracle will expand that under the hood to look like the original longer query above, but it's easier to maintain.
Updated SQL Fiddle.