SQL query to identify seasonal sales items - sql

I need a SQL query that will identify seasonal sales items.
My table has the following structure -
ProdId WeekEnd Sales
234 23/04/09 543.23
234 30/04/09 12.43
432 23/04/09 0.00
etc
I need a SQL query that will return all ProdId's that have 26 weeks consecutive 0 sales. I am running SQL server 2005. Many thanks!
Update: A colleague has suggested a solution using rank() - I'm looking at it now...

Here's my version:
DECLARE #NumWeeks int
SET #NumWeeks = 26
SELECT s1.ProdID, s1.WeekEnd, COUNT(*) AS ZeroCount
FROM Sales s1
INNER JOIN Sales s2
ON s2.ProdID = s1.ProdID
AND s2.WeekEnd >= s1.WeekEnd
AND s2.WeekEnd <= DATEADD(WEEK, #NumWeeks + 1, s1.WeekEnd)
WHERE s1.Sales > 0
GROUP BY s1.ProdID, s1.WeekEnd
HAVING COUNT(*) >= #NumWeeks
Now, this is making a critical assumption, namely that there are no duplicate entries (only 1 per product per week) and that new data is actually entered every week. With these assumptions taken into account, if we look at the 27 weeks after a non-zero sales week and find that there were 26 total weeks with zero sales, then we can deduce logically that they had to be 26 consecutive weeks.
Note that this will ignore products that had zero sales from the start; there has to be a non-zero week to anchor it. If you want to include products that had no sales since the beginning, then add the following line after `WHERE s1.Sales > 0':
OR s1.WeekEnd = (SELECT MIN(WeekEnd) FROM Sales WHERE ProdID = s1.ProdID)
This will slow the query down a lot but guarantees that the first week of "recorded" sales will always be taken into account.

SELECT DISTINCT
s1.ProdId
FROM (
SELECT
ProdId,
ROW_NUMBER() OVER (PARTITION BY ProdId ORDER BY WeekEnd) AS rownum,
WeekEnd
FROM Sales
WHERE Sales <> 0
) s1
INNER JOIN (
SELECT
ProdId,
ROW_NUMBER() OVER (PARTITION BY ProdId ORDER BY WeekEnd) AS rownum,
WeekEnd
FROM Sales
WHERE Sales <> 0
) s2
ON s1.ProdId = s2.ProdId
AND s1.rownum + 1 = s2.rownum
AND DateAdd(WEEK, 26, s1.WeekEnd) = s2.WeekEnd;

Related

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

simple sql query highest sales

There are 2 tables - Products and Sales
Products
prod_id
prod_nm
Sales
prod_id
cust_id
sls_dt
sls_amt
Write a query selecting ALL the products. For each product show total of sales amounts in the past 30 days or 0 if not sold in 30 day withoug using subqueries.
Since different RDBMS have different date functions, you can filter by date using the following pseudo code - sls_dt > now() - 30.
Im new to sql and im trying it like this as i found this online.
Select prod_id, prod_nm from(
Select sls_amt
From Sales) as t
Where t.rank = 1
However, this isnt' working. Any help is appreciated
Try below:
select p.prod_id,
p.prod_nm,
sum(s.sls_amt)
from products p
left outer join Sales s on p.prod_id = s.prod_id
and s.sls_dt > now() - 30
group by p.prod_id,
p.prod_nm;

Query to get top product gainers by sales over previous week

I have a database table with three columns.
WeekNumber, ProductName, SalesCount
Sample data is shown in below table. I want top 10 gainers(by %) for week 26 over previous week i.e. week 25. The only condition is that the product should have sales count greater than 0 in both the weeks.
In the sample data B,C,D are the common products and C has the highest % gain.
Similarly, I will need top 10 losers also.
What I have tried till now is to make a inner join and get common products between two weeks. However, I am not able to get the top gainers logic.
The output should be like
Product PercentGain
C 400%
D 12.5%
B 10%
This will give you a generic answer, not just for any particular week:
select top 10 product , gain [gain%]
from
(
SELECT product, ((curr.salescount-prev.salescount)/prev.salescount)*100 gain
from
(select weeknumber, product, salescount from tbl) prev
JOIN
(select weeknumber, product, salescount from tbl) curr
on prev.weeknumber = curr.weeknumber - 1
AND prev.product = curr.product
where prev.salescount > 0 and curr.salescount > 0
)A
order by gain desc
If you are interested in weeks 25 and 26, then just add the condition below in the WHERE clause:
and prev.weeknumber = 25
If you are using SQL-Server 2012 (or newer), you could use the lag function to match "this" weeks sales with the previous week's. From there on, it's just some math:
SELECT TOP 10 product, sales/prev_sales - 1 AS gain
FROM (SELECT product,
sales,
LAG(sales) OVER (PARTITION BY product
ORDER BY weeknumber) AS prev_sales
FROM mytable) t
WHERE weeknumber = 26 AND
sales > 0 AND
prev_sales > 0 AND
sales > prev_sales
ORDER BY sales/prev_sales
this is the Query .
select top 10 product , gain [gain%]
from
(
SELECT curr.Product, ( (curr.Sales - prev.Sales ) *100)/prev.Sales gain
from
(select weeknumber, product, sales from ProductInfo where weeknumber = 25 ) prev
JOIN
(select weeknumber, product, sales from ProductInfo where weeknumber = 26 ) curr
on prev.product = curr.product
where prev.Sales > 0 and curr.Sales > 0
)A
order by gain desc

SQL Query: Calculating the deltas in a time series

For a development aid project I am helping a small town in Nicaragua improving their water-network-administration.
There are about 150 households and every month a person checks the meter and charges the houshold according to the consumed water (reading from this month minus reading from last month). Today all is done on paper and I would like to digitalize the administration to avoid calculation-errors.
I have an MS Access Table in mind - e.g.:
*HousholdID* *Date* *Meter*
0 1/1/2013 100
1 1/1/2013 130
0 1/2/2013 120
1 1/2/2013 140
...
From this data I would like to create a query that calculates the consumed water (the meter-difference of one household between two months)
*HouseholdID* *Date* *Consumption*
0 1/2/2013 20
1 1/2/2013 10
...
Please, how would I approach this problem?
This query returns every date with previous date, even if there are missing months:
SELECT TabPrev.*, Tab.Meter as PrevMeter, TabPrev.Meter-Tab.Meter as Diff
FROM (
SELECT
Tab.HousholdID,
Tab.Data,
Max(Tab_1.Data) AS PrevData,
Tab.Meter
FROM
Tab INNER JOIN Tab AS Tab_1 ON Tab.HousholdID = Tab_1.HousholdID
AND Tab.Data > Tab_1.Data
GROUP BY Tab.HousholdID, Tab.Data, Tab.Meter) As TabPrev
INNER JOIN Tab
ON TabPrev.HousholdID = Tab.HousholdID
AND TabPrev.PrevData=Tab.Data
Here's the result:
HousholdID Data PrevData Meter PrevMeter Diff
----------------------------------------------------------
0 01/02/2013 01/01/2013 120 100 20
1 01/02/2013 01/01/2012 140 130 10
The query above will return every delta, for every households, for every month (or for every interval). If you are just interested in the last delta, you could use this query:
SELECT
MaxTab.*,
TabCurr.Meter as CurrMeter,
TabPrev.Meter as PrevMeter,
TabCurr.Meter-TabPrev.Meter as Diff
FROM ((
SELECT
Tab.HousholdID,
Max(Tab.Data) AS CurrData,
Max(Tab_1.Data) AS PrevData
FROM
Tab INNER JOIN Tab AS Tab_1
ON Tab.HousholdID = Tab_1.HousholdID
AND Tab.Data > Tab_1.Data
GROUP BY Tab.HousholdID) As MaxTab
INNER JOIN Tab TabPrev
ON TabPrev.HousholdID = MaxTab.HousholdID
AND TabPrev.Data=MaxTab.PrevData)
INNER JOIN Tab TabCurr
ON TabCurr.HousholdID = MaxTab.HousholdID
AND TabCurr.Data=MaxTab.CurrData
and (depending on what you are after) you could only filter current month:
WHERE
DateSerial(Year(CurrData), Month(CurrData), 1)=
DateSerial(Year(DATE()), Month(DATE()), 1)
this way if you miss a check for a particular household, it won't show.
Or you might be interested in showing last month present in the table (which can be different than current month):
WHERE
DateSerial(Year(CurrData), Month(CurrData), 1)=
(SELECT MAX(DateSerial(Year(Data), Month(Data), 1))
FROM Tab)
(here I am taking in consideration the fact that checks might be on different days)
I think the best approach is to use a correlated subquery to get the previous date and join back to the original table. This ensures that you get the previous record, even if there is more or less than a 1 month lag.
So the right query looks like:
select t.*, tprev.date, tprev.meter
from (select t.*,
(select top 1 date from t t2 where t2.date < t.date order by date desc
) prevDate
from t
) join
t tprev
on tprev.date = t.prevdate
In an environment such as the one you describe, it is very important not to make assumptions about the frequency of reading the meter. Although they may be read on average once per month, there will always be exceptions.
Testing with the following data:
HousholdID Date Meter
0 01/12/2012 100
1 01/12/2012 130
0 01/01/2013 120
1 01/01/2013 140
0 01/02/2013 120
1 01/02/2013 140
The following query:
SELECT a.housholdid,
a.date,
b.date,
a.meter,
b.meter,
a.meter - b.meter AS Consumption
FROM (SELECT *
FROM water
WHERE Month([date]) = Month(Date())
AND Year([date])=year(Date())) a
LEFT JOIN (SELECT *
FROM water
WHERE DateSerial(Year([date]),Month([date]),Day([date]))
=DateSerial(Year(Date()),Month(Date())-1,Day([date])) ) b
ON a.housholdid = b.housholdid
The above query selects the records for this month Month([date]) = Month(Date()) and compares them to records for last month ([date]) = Month(Date()) - 1)
Please do not use Date as a field name.
Returns the following result.
housholdid a.date b.date a.meter b.meter Consumption
0 01/02/2013 01/01/2013 120 100 20
1 01/02/2013 01/01/2013 140 130 10
Try
select t.householdID
, max(s.theDate) as billingMonth
, max(s.meter)-max(t.meter) as waterUsed
from myTbl t join (
select householdID, max(theDate) as theDate, max(meter) as meter
from myTbl
group by householdID ) s
on t.householdID = s.householdID and t.theDate <> s.theDate
group by t.householdID
This works in SQL not sure about access
You can use the LAG() function in certain SQL dialects. I found this to be much faster and easier to read than joins.
Source: http://blog.jooq.org/2015/05/12/use-this-neat-window-function-trick-to-calculate-time-differences-in-a-time-series/

sql query to calculate monthly growth percentage

I need to build a query with 4 columns (sql 2005).
Column1: Product
Column2: Units sold
Column3: Growth from previous month (in %)
Column4: Growth from same month last year (in %)
In my table the year and months have custom integer values. For example, the most current month is 146 - but also the table has a year (eg 2011) column and month (eg 7) column.
Is it possible to get this done in one query or do i need to start employing temp tables etc??
Appreciate any help.
thanks,
KS
KS,
To do this on the fly, you could use subqueries.
SELECT product, this_month.units_sold,
(this_month.sales-last_month.sales)*100/last_month.sales,
(this_month.sales-last_year.sales)*100/last_year.sales
FROM (SELECT product, SUM(units_sold) AS units_sold, SUM(sales) AS sales
FROM product WHERE month = 146 GROUP BY product) AS this_month,
(SELECT product, SUM(units_sold) AS units_sold, SUM(sales) AS sales
FROM product WHERE month = 145 GROUP BY product) AS last_month,
(SELECT product, SUM(units_sold) AS units_sold, SUM(sales) AS sales
FROM product WHERE month = 134 GROUP BY product) AS this_year
WHERE this_month.product = last_month.product
AND this_month.product = last_year.product
If there's a case where a product was sold in one month but not another month, you will have to do a left join and check for null values, especially if last_month.sales or last_year.sales is 0.
I hope I got them all:
SELECT
Current_Month.product_name, units_sold_current_month,
units_sold_last_month * 100 / units_sold_current_month prc_last_month,
units_sold_last_year * 100 / units_sold_current_month prc_last_year
FROM
(SELECT product_id, product_name, sum(units_sold) units_sold_current_month FROM MyTable WHERE YEAR = 2011 AND MONTH = 7) Current_Month
JOIN
(SELECT product_id, product_name, sum(units_sold) units_sold_last_month FROM MyTable WHERE YEAR = 2011 AND MONTH = 6) Last_Month
ON Current_Month.product_id = Last_Month.product_id
JOIN
(SELECT product_id, product_name, sum(units_sold) units_sold_last_year FROM MyTable WHERE YEAR = 2010 AND MONTH = 7) Last_Year
ON Current_Month.product_id = Last_Year.product_id
I am slightly guessing as the structure of the table provided is the result table, right? You will need to do self-join on month-to-previous-month basis:
SELECT <growth computation here>
FROM SALES s1 LEFT JOIN SALES s2 ON (s1.month = s2.month-1) -- last month join
LEFT JOIN SALES s3 ON (s1.month = s3.month - 12) -- lat year join
where <growth computation here> looks like
((s1.sales - s2.sales)/s2.sales * 100),
((s1.sales - s3.sales)/s3.sales * 100)
I use LEFT JOIN for months that have no previous months. Change your join conditions based on actual relations in month/year columns.