Need to add total # of orders to summary query - sql

In the following, I need to add here the total of orders per order type which is IHORDT. I tried count(t01.ihordt), but its not a valid. I need this order total to get average amount per order.
Data expected:
Current:
IHORDT current year previous year
RTR 100,000 90,000
INT 2,000,000 1,500,000
New change: add to the above one column:
Total orders
RTR 100
INT 1000
SELECT T01.IHORDT
-- summarize by current year and previous year
,SUM( CASE WHEN YEAR(IHDOCD) = YEAR(CURRENT TIMESTAMP) - 1
THEN (T02.IDSHP#*T02.IDNTU$) ELSE 0 END) AS LastYear
,SUM( CASE WHEN YEAR(IHDOCD) = YEAR(CURRENT TIMESTAMP)
THEN (T02.IDSHP#*T02.IDNTU$) ELSE 0 END) AS CurYear
FROM ASTDTA.OEINHDIH
T01 INNER JOIN
ASTDTA.OEINDLID T02
ON T01.IHORD# = T02.IDORD#
WHERE T01.IHORDT in ('RTR', 'INT')
--------------------------------------------------------
AND ( YEAR(IHDOCD) = YEAR(CURRENT TIMESTAMP) - 1
OR YEAR(IHDOCD) = YEAR(CURRENT TIMESTAMP))
GROUP BY T01.IHORDT


To receive a count of records in a group you need to use count(*).
So here is a generic example:
select order_type,
sum(order_amount) as total_sales,
count(*) as number_of_orders
from order_header
group by order_type;

Related

SQL Divide previous row balance by current row balance and insert that value into current rows column "Growth"

I have a table where like this.
Year
ProcessDate
Month
Balance
RowNum
Calculation
2022
20220430
4
22855547
1
2022
20220330
3
22644455
2
2022
20220230
2
22588666
3
2022
20220130
1
33545444
4
2022
20221230
12
22466666
5
I need to take the previous row of each column and divide that amount by the current row.
Ex: Row 1 calculation should = Row 2 Balance / Row 1 Balance (22644455/22855547 = .99% )
Row 2 calculation should = Row 3 Balance / Row 2 Balance etc....
Table is just a Temporary table I created titled #MonthlyLoanBalance2.
Now I just need to take it a step further.
Let me know what and how you would go about doing this.
Thank you in advance!
Insert into #MonthlytLoanBalance2 (
Year
,ProcessDate
,Month
,Balance
,RowNum
)
select
--CloseYearMonth,
left(ProcessDate,4) as 'Year',
ProcessDate,
--x.LOANTypeKey,
SUBSTRING(CAST(x.ProcessDate as varchar(38)),5,2) as 'Month',
sum(x.currentBalance) as Balance
,ROW_NUMBER()over (order by ProcessDate desc) as RowNum
from
(
select
distinct LoanServiceKey,
LoanTypeKey,
AccountNumber,
CurrentBalance,
OpenDateKey,
CloseDateKey,
ProcessDate
from
cu.LAFactLoanSnapShot
where LoanStatus = 'Open'
and LoanTypeKey = 0
and ProcessDate in (select DateKey from dimDate
where IsLastDayOfMonth = 'Y'
and DateKey > convert(varchar, getdate()-4000, 112)
)
) x
group by ProcessDate
order by ProcessDate desc;``

I am assuming your data is already prepared as shown in the table. Now you can try Lead() function to resolve your issue. Remember format() function is used for taking only two precision.
SELECT *,
FORMAT((ISNULL(LEAD(Balance,1) OVER (ORDER BY RowNum), 1)/Balance),'N2') Calculation
FROM #MonthlytLoanBalance2

SQL - Calculate the difference in number of orders by month

I am working on the orders table provided by this site, it has its own editor where you can test your SQL statements.
The order table looks like this
order_id
customer_id
order_date
1
7000
2016/04/18
2
5000
2016/04/18
3
8000
2016/04/19
4
4000
2016/04/20
5
NULL
2016/05/01
I want to get the difference in the number of orders for subsequent months.
To elaborate, the number of orders each month would be like this
SQL Statement
SELECT
MONTH(order_date) AS Month,
COUNT(MONTH(order_date)) AS Total_Orders
FROM
orders
GROUP BY
MONTH(order_date)
Result:
Month
Total_Orders
4
4
5
1
Now my goal is to get the difference in subsequent months which would be
Month
Total_Orders
Total_Orders_Diff
4
4
4 - Null = Null
5
1
1 - 4 = -3
My strategy was to self-join following this answer
This was my attempt
SELECT
MONTH(a.order_date),
COUNT(MONTH(a.order_date)),
COUNT(MONTH(b.order_date)) - COUNT(MONTH(a.order_date)) AS prev,
MONTH(b.order_date)
FROM
orders a
LEFT JOIN
orders b ON MONTH(a.order_date) = MONTH(b.order_date) - 1
GROUP BY
MONTH(a.order_date)
However, the result was just zeros (as shown below) which suggests that I am just subtracting from the same value rather than from the previous month (or subtracting from a null value)
MONTH(a.order_date)
COUNT(MONTH(a.order_date))
prev
MONTH(b.order_date)
4
4
0
NULL
5
1
0
NULL
Do you have any suggestions as to what I am doing wrong?

You have to use LAG window function in your SELECT statement.
LAG provides access to a row at a given physical offset that comes
before the current row.
So, this is what you need:
SELECT
MONTH(order_date) as Month,
COUNT(MONTH(order_date)) as Total_Orders,
COUNT(MONTH(order_date)) - (LAG (COUNT(MONTH(order_date))) OVER (ORDER BY (SELECT NULL))) AS Total_Orders_Diff
FROM orders
GROUP BY MONTH(order_date);
Here in an example on the SQL Fiddle: http://sqlfiddle.com/#!18/5ed75/1
Solution without using LAG window function:
WITH InitCTE AS
(
SELECT MONTH(order_date) AS Month,
COUNT(MONTH(order_date)) AS Total_Orders
FROM orders
GROUP BY MONTH(order_date)
)
SELECT InitCTE.Month, InitCTE.Total_Orders, R.Total_Orders_Diff
FROM InitCTE
OUTER APPLY (SELECT TOP 1 InitCTE.Total_Orders - CompareCTE.Total_Orders AS Total_Orders_Diff
FROM InitCTE AS CompareCTE
WHERE CompareCTE.Month < InitCTE.Month) R;

Something like the following should give you what you want - disclaimer, untested!
select *, Total_Orders - lag(Total_orders,1) over(order by Month) as Total_Orders_Diff
from (
select Month(order_date) as Month, Count(*) as Total_Orders
From orders
Group by Month(order_date)
)o

SQL sum over(partition) not subtracting negative values in SUM

I have the following query which outputs a list of transactions per user - units spent and units earned - column 'Amount'.
I have managed to group this per user and do a running total - column 'Running_Total_Spend'.
However it is ADDING the negative 'Amount' values rather than subtracting them. Sp pretty sure it is the SUM part of query not working.
WITH cohort AS(
SELECT DISTINCT userID FROM events_live WHERE startDate = '2018-07-26' LIMIT 50),
my_events AS (
SELET events_live.* FROM events_live WHERE eventDate >= '2018-07-26')
SELECT cohort.userID,
my_events.eventDate,
my_events.eventTimestamp,
CASE
--spent resource outputs a negative value ---working
WHEN transactionVector = 'SPENT' THEN -abs(my_events.productAmount)
--earned resource outputs a positive value ---working
WHEN transactionVector = 'RECEIVED' THEN my_events.productAmount END AS Amount,
ROW_NUMBER() OVER (PARTITION BY cohort.userID ORDER BY cohort.userID, eventTimestamp asc) AS row,
--sum the values in column 'Amount' for this partition
--should sum positive and negative values ---NOT WORKING--converting negatives into positive
--------------------------------------------------
SUM(CASE WHEN my_events.productAmount >= 0 THEN my_events.productAmount
WHEN my_events.productAmount <0 THEN -abs(my_events.productAmount) end) OVER(PARTITION BY cohort.userID ORDER BY cohort.userID, eventTimestamp asc) AS Running_Total_Spend
---------------------------------------------------
FROM cohort
INNER JOIN my_events ON cohort.userID=my_events.userID
WHERE productName = 'COINS' AND transactionVector IN ('SPENT','RECEIVED')

I suspect you want that logic around transactionvector for the sum too as my_events.productamount seems to be always positive.
...
sum(CASE
WHEN transactionvector = 'SPENT' THEN
-my_events.productamount
WHEN transactionvector = 'RECEIVED' THEN
my_events.productamount
END) OVER (PARTITION BY cohort.userid
ORDER BY cohort.userid,
eventTimestamp) running_total_spend
...

Update your sum function to -
SUM(my_events.productAmount) OVER(PARTITION BY cohort.userID ORDER BY cohort.userID, eventTimestamp asc) AS Running_Total_Spend

How to get the discount number of customers in prior period?

I have a requirement where I supposed to roll customer data in the prior period of 365 days.
Table:
CREATE TABLE orders (
persistent_key_str character varying,
ord_id character varying(50),
ord_submitted_date date,
item_sku_id character varying(50),
item_extended_actual_price_amt numeric(18,2)
);
Sample data:
INSERT INTO orders VALUES
('01120736182','ORD6266073' ,'2010-12-08','100856-01',39.90),
('01120736182','ORD33997609' ,'2011-11-23','100265-01',49.99),
('01120736182','ORD33997609' ,'2011-11-23','200020-01',29.99),
('01120736182','ORD33997609' ,'2011-11-23','100817-01',44.99),
('01120736182','ORD89267964' ,'2012-12-05','200251-01',79.99),
('01120736182','ORD89267964' ,'2012-12-05','200269-01',59.99),
('01011679971','ORD89332495' ,'2012-12-05','200102-01',169.99),
('01120736182','ORD89267964' ,'2012-12-05','100907-01',89.99),
('01120736182','ORD89267964' ,'2012-12-05','200840-01',129.99),
('01120736182','ORD125155068','2013-07-27','201443-01',199.99),
('01120736182','ORD167230815','2014-06-05','200141-01',59.99),
('01011679971','ORD174927624','2014-08-16','201395-01',89.99),
('01000217334','ORD92524479' ,'2012-12-20','200021-01',29.99),
('01000217334','ORD95698491' ,'2013-01-08','200021-01',19.99),
('01000217334','ORD90683621' ,'2012-12-12','200021-01',29.990),
('01000217334','ORD92524479' ,'2012-12-20','200560-01',29.99),
('01000217334','ORD145035525','2013-12-09','200972-01',49.99),
('01000217334','ORD145035525','2013-12-09','100436-01',39.99),
('01000217334','ORD90683374' ,'2012-12-12','200284-01',39.99),
('01000217334','ORD139437285','2013-11-07','201794-01',134.99),
('01000827006','W02238550001','2010-06-11','HL 101077',349.000),
('01000827006','W01738200001','2009-12-10','EL 100310 BLK',119.96),
('01000954259','P00444170001','2009-12-03','PC 100455 BRN',389.99),
('01002319116','W02242430001','2010-06-12','TR 100966',35.99),
('01002319116','W02242430002','2010-06-12','EL 100985',99.99),
('01002319116','P00532470001','2010-05-04','HO 100482',49.99);
Using the query below I am trying to get the number of distinct customers by order_submitted_date:
select
g.order_date as "Ordered",
count(distinct o.persistent_key_str) as "customers"
from
generate_series(
(select min(ord_submitted_date) from orders),
(select max(ord_submitted_date) from orders),
'1 day'
) g (order_date)
left join
orders o on o.ord_submitted_date between g.order_date - interval '364 days'
and g.order_date
WHERE extract(year from ord_submitted_date) <= 2009
group by 1
order by 1
This is the output I expected.
Ordered Customers
2009-12-03 1
2009-12-10 1
When I execute the query above I get incorrect results.
How can I make this right?

To get your expected output ("the number of distinct customers") - only days with actual orders 2009:
SELECT ord_submitted_date, count(DISTINCT persistent_key_str) AS customers
FROM orders
WHERE ord_submitted_date >= '2009-1-1'
AND ord_submitted_date < '2010-1-1'
GROUP BY 1
ORDER BY 1;
Formulate the WHERE conditions this way to make the query sargable, and input easy.
If you want one row per day (from the earliest entry up to the latest in orders) - within 2009:
SELECT ord_submitted_date AS ordered
, count(DISTINCT o.persistent_key_str) AS customers
FROM (SELECT generate_series(min(ord_submitted_date) -- single query ...
, max(ord_submitted_date) -- ... to get min / max
, '1d')::date FROM orders) g (ord_submitted_date)
LEFT join orders o USING (ord_submitted_date)
WHERE ord_submitted_date >= '2009-1-1'
AND ord_submitted_date < '2010-1-1'
GROUP BY 1
ORDER BY 1;
SQL Fiddle.
Distinct customers per year
SELECT extract(year from ord_submitted_date) AS year
, count(DISTINCT persistent_key_str) AS customers
FROM orders
GROUP BY 1
ORDER BY 1;
SQL Fiddle.

Grouping multiple selects within a SQL query

I have a table Supplier with two columns, TotalStock and Date. I'm trying to write a single query that will give me stock totals by week / month / year for a list of suppliers.
So results will look like this..
SUPPLIER WEEK MONTH YEAR
SupplierA 50 100 2000
SupplierB 60 150 2500
SupplierC 15 25 200
So far I've been playing around with multiple selects but I can't get any further than this:
SELECT Supplier,
(
SELECT Sum(TotalStock)
FROM StockBreakdown
WHERE Date >= '2014-5-12'
GROUP BY Supplier
) AS StockThisWeek,
(
SELECT Sum(TotalStock)
FROM StockBreakdown
WHERE Date >= '2014-5-1'
GROUP BY Supplier
) AS StockThisMonth,
(
SELECT Sum(TotalStock)
FROM StockBreakdown
WHERE Date >= '2014-1-1'
GROUP BY Supplier
) AS StockThisYear
This query throws an error as each individual grouping returns multiple results. I feel that I'm close to the solution but can't work out where to go

You don't have to use subqueries to achieve what you want :
SELECT Supplier
, SUM(CASE WHEN Date >= CAST('2014-05-12' as DATE) THEN TotalStock END) AS StockThisWeek
, SUM(CASE WHEN Date >= CAST('2014-05-01' as DATE) THEN TotalStock END) AS StockThisMonth
, SUM(CASE WHEN Date >= CAST('2014-01-01' as DATE) THEN TotalStock END) AS StockThisYear
FROM StockBreakdown
GROUP BY Supplier

You may need to make the selects for the columns return only a single result. You could try this (not tested currently):
SELECT Supplier,
(
SELECT TOP 1 StockThisWeek FROM
(
SELECT Supplier, Sum(TotalStock) AS StockThisWeek
FROM StockBreakdown
WHERE Date >= '2014-5-12'
GROUP BY Supplier
) tmp1
WHERE tmp1.Supplier = Supplier
) AS StockThisWeek,
(
SELECT TOP 1 StockThisMonth FROM
(
SELECT Supplier, Sum(TotalStock) AS StockThisMonth
FROM StockBreakdown
WHERE Date >= '2014-5-1'
GROUP BY Supplier
) tmp2
WHERE tmp2.Supplier = Supplier
) AS StockThisMonth,
...
This selects the supplier and then tries to create two columns StockThisWeek and StockThisMonth by selecting the first entry from the select you created before. As through the GROUP BY there should only be one entry per supplier, so you don't lose and data.