I have a dataset which has customer information regarding the number of orders they have placed, their order value and their customer id.
I am trying to find out what is the average order value of the customers, how many orders they have placed and what is the total revenue they generated in the month of November. However, I also want to group this into quintiles to see what were these values for the top 5%, next 5% and so on. I want to group them into quintiles based on the customers total order values.
So far I have tried:
select customer_number , orders, amount,
percentile_cont(0.95) within group(order by amount) over(partition by customer_account_id) as ninetyfive,
percentile_cont(0.90) within group(order by amount) over(partition by customer_account_id) as ninety,
from(
select customer_number , count(ordernum) as orders, sum(amount_paid) as amount
from data_table
and date_part(month ,order_date) = 11
and date_part(year, order_date) =2021
group by customer_number
order by amount desc
)
group by customer_number, orders, amount
order by amount desc;
Related
Have customer payments , i want to calculate who are the top 10 customers per day based on sum of amount per day per customer. Eventually i want to display those 10 customers and their payment per hour (sum of the amount per hour)
I tried to create 2 window functions in bigquery one window function for per customer and per hour (Value_Hr) values, and one more window function for sum of values per customer (Value_customer).
with base as (
select Name, sum(amount) over W1 as Value_Hr, Hour, sum(amount) over w2 as Value_customer
from
(SELECT trim(cast(format('%t',Name) as string) ) as Name,
cast(round(amount) as numeric) as amount , extract(hour from SettlementTimestamp) as Hr
FROM Payments
where length(trim(Name))>0
)
qualify row_number() over (partition by Name,hr )=1
window w1 as (partition by Name,hr ),
w2 as (partition by Name)
)
select Name,Value_Hr,Hour ,Value_customer
from base
qualify row_number() over (partition by Value_customer order by Value_customer desc )<=10
I expect data as below
but row_number is calculating with in the group of customers and hourly amounts instead per customer and its total value
Can anyone help ?
I have the following query that shows total sales for each product on an hourly basis. However, it is very big data and I don't want to see all products, so would like to see the top 1000 product_id based on sales for each date, hour, and category_id dimensions.
SELECT date,
hour,
category_id,
product_id,
sum(sales) AS sales
FROM a
LEFT JOIN
ON a.product_id = b.product_id
WHERE date(date) >= date('2021-01-01')
GROUP BY 1, 2, 3, 4
How to do it in the Athena?
Thanks in advance.
You can use rank function on your result and then filter out corresponding ranks:
SELECT date,
hour,
category_id,
product_id,
sales
FROM
(
SELECT *,
rank() OVER (PARTITION BY date, hour, category_id
ORDER BY sales DESC) AS rnk
FROM (your query)
)
WHERE rnk <= 1000
I am given a database to use in SQL server.
The tables are:
Price (prodID, from, price)
Product (prodID, name, quantity)
PO (prodID, orderID, amount)
Order (orderID, date, address, status, trackingNumber, custID,
shipID)
Shipping (shipID, company, time, price)
Customer (custID, name)
Address (addrID, custID, address)
I need to Determine the ID and current price of each product.
The from attribute in the Price table are the dates that the prices were updated i.e. each ID in the table has multiple prices and dates associated with them but there is no common date between all of the IDs and the dates are in the 'YYYY-MM-DD' format and range is from 2018 to 2019-12-31.
My current query looks like:
select distinct p.prodID, p.price
from Price as p
where p.[from] >= '2019-12-23' and p.[from] in (select [from]
from Price
group by [from]
having max([from]) <= '2019-12-31')
order by p.prodID;
which returns a table with multiple prices for some of the IDs and also excludes other IDs altogether.
I was told that I needed a subquery to perform this.
I believe that I may be being too specific in my query to produce the desired results.
My main goal is to fix my current query to select one of each prodID and price from the most recent from date.
One option uses window functions:
select *
from (
select p.*, row_number() over(partition by p.prodid order by p.from desc) rn
from price p
where p.from <= convert(date, getdate())
) t
where rn = 1
This returns the latest row for each prodid where from is not greater that the current date.
As an alternative, you could also use with ties:
select top (1) with ties p.*
from price p
where p.from <= convert(date, getdate())
order by row_number() over(partition by p.prodid order by p.from desc)
I'm trying to output a top 3 products per quarter, that should be a total of 12 rows, since 3 top products per quarter.
Closest output is the one provided below i have no idea how to like partition it every quarter
SELECT * FROM (SELECT QUARTER, PRODUCT_NAME, SUM(QUANTITY) "QTY_SOLD", SALES, SUM(PROFIT) "PROFIT_GENERATED" FROM DELIVERIES_FACT
WHERE EXTRACT(YEAR from SHIP_DATE) = 2015 GROUP BY QUARTER, PRODUCT_NAME, SALES ORDER BY "PROFIT_GENERATED" DESC)
WHERE rownum <= 3
getting an output of
I've written this SQL extracting the calendar quarter from SHIP_DATE; you can adjust as needed.
Similarly, RANK(), ROW_NUMBER(), and DENSE_RANK() all are different; you may wish to experiment with each analytical function to see which best fits your data and handles ties the way you want them to.
SELECT *
FROM (SELECT RANK() OVER (PARTITION BY SHIP_QUARTER
ORDER BY PROFIT_GENERATED desc) AS PROFIT_RANK_BY_Q,
ORIG.*
FROM
(SELECT EXTRACT(QUARTER from SHIP_DATE) AS SHIP_QUARTER,
PRODUCT_NAME,
SUM(QUANTITY) "QTY_SOLD", SALES, SUM(PROFIT) "PROFIT_GENERATED"
FROM DELIVERIES_FACT
WHERE EXTRACT(YEAR from SHIP_DATE) = 2015
GROUP BY EXTRACT(QUARTER from SHIP_DATE), PRODUCT_NAME, SALES
)
)
WHERE PROFIT_RANK_BY_Q <= 3
order by SHIP_QUARTER, PROFIT_RANK_BY_Q
I'm having an odd problem
I have a table with the columns product_id, sales and day
Not all products have sales every day. I'd like to get the average number of sales that each product had in the last 10 days where it had sales
Usually I'd get the average like this
SELECT product_id, AVG(sales)
FROM table
GROUP BY product_id
Is there a way to limit the amount of rows to be taken into consideration for each product?
I'm afraid it's not possible but I wanted to check if someone has an idea
Update to clarify:
Product may be sold on days 1,3,5,10,15,17,20.
Since I don't want to get an the average of all days but only the average of the days where the product did actually get sold doing something like
SELECT product_id, AVG(sales)
FROM table
WHERE day > '01/01/2009'
GROUP BY product_id
won't work
If you want the last 10 calendar day since products had a sale:
SELECT product_id, AVG(sales)
FROM table t
JOIN (
SELECT product_id, MAX(sales_date) as max_sales_date
FROM table
GROUP BY product_id
) t_max ON t.product_id = t_max.product_id
AND DATEDIFF(day, t.sales_date, t_max.max_sales_date) < 10
GROUP BY product_id;
The date difference is SQL server specific, you'd have to replace it with your server syntax for date difference functions.
To get the last 10 days when the product had any sale:
SELECT product_id, AVG(sales)
FROM (
SELECT product_id, sales, DENSE_RANK() OVER
(PARTITION BY product_id ORDER BY sales_date DESC) AS rn
FROM Table
) As t_rn
WHERE rn <= 10
GROUP BY product_id;
This asumes sales_date is a date, not a datetime. You'd have to extract the date part if the field is datetime.
And finaly a windowing function free version:
SELECT product_id, AVG(sales)
FROM Table t
WHERE sales_date IN (
SELECT TOP(10) sales_date
FROM Table s
WHERE t.product_id = s.product_id
ORDER BY sales_date DESC)
GROUP BY product_id;
Again, sales_date is asumed to be date, not datetime. Use other limiting syntax if TOP is not suported by your server.
Give this a whirl. The sub-query selects the last ten days of a product where there was a sale, the outer query does the aggregation.
SELECT t1.product_id, SUM(t1.sales) / COUNT(t1.*)
FROM table t1
INNER JOIN (
SELECT TOP 10 day, Product_ID
FROM table t2
WHERE (t2.product_ID=t1.Product_ID)
ORDER BY DAY DESC
)
ON (t2.day=t1.day)
GROUP BY t1.product_id
BTW: This approach uses a correlated subquery, which may not be very performant, but it should work in theory.
I'm not sure if I get it right but If you'd like to get the average of sales for last 10 days for you products you can do as follows :
SELECT Product_Id,Sum(Sales)/Count(*) FROM (SELECT ProductId,Sales FROM Table WHERE SaleDAte>=#Date) table GROUP BY Product_id HAVING Count(*)>0
OR You can use AVG Aggregate function which is easier :
SELECT Product_Id,AVG(Sales) FROM (SELECT ProductId,Sales FROM Table WHERE SaleDAte>=#Date) table GROUP BY Product_id
Updated
Now I got what you meant ,As far as I know it is not possible to do this in one query.It could be possible if we could do something like this(Northwind database):
select a.CustomerId,count(a.OrderId)
from Orders a INNER JOIN(SELECT CustomerId,OrderDate FROM Orders Order By OrderDate) AS b ON a.CustomerId=b.CustomerId GROUP BY a.CustomerId Having count(a.OrderId)<10
but you can't use order by in subqueries unless you use TOP which is not suitable for this case.But maybe you can do it as follows:
SELECT PorductId,Sales INTO #temp FROM table Order By Day
select a.ProductId,Sum(a.Sales) /Count(a.Sales)
from table a INNER JOIN #temp AS b ON a.ProductId=b.ProductId GROUP BY a.ProductId Having count(a.Sales)<=10
If this is a table of sales transactions, then there should not be any rows in there for days on which there were no Sales. I.e., If ProductId 21 had no sales on 1 June, then this table should not have any rows with productId = 21 and day = '1 June'... Therefore you should not have to filter anything out - there should not be anything to filter out
Select ProductId, Avg(Sales) AvgSales
From Table
Group By ProductId
should work fine. So if it's not, then you have not explained the problem completely or accurately.
Also, in yr question, you show Avg(Sales) in the example SQL query but then in the text you mention "average number of sales that each product ... " Do you want the average sales amount, or the average count of sales transactions? And do you want this average by Product alone (i.e., one output value reported for each product) or do you want the average per product per day ?
If you want the average per product alone, for just thpse sales in the ten days prior to now? or the ten days prior to the date of the last sale for each product?
If the latter then
Select ProductId, Avg(Sales) AvgSales
From Table T
Where day > (Select Max(Day) - 10
From Table
Where ProductId = T.ProductID)
Group By ProductId
If you want the average per product alone, for just those sales in the ten days with sales prior to the date of the last sale for each product, then
Select ProductId, Avg(Sales) AvgSales
From Table T
Where (Select Count(Distinct day) From Table
Where ProductId = T.ProductID
And Day > T.Day) <= 10
Group By ProductId