I have 2 tables
sales table
weekly sales, store, date
store table
store, type, size
my sales table has multiple years, multiple stores and multiple types. I'm trying to get the avg sales by sqft for each store type per year. I have a sub query that shows the sales by sqft for each store but Im having trouble then rolling it up into my main query to get the avg by type
Anything jumps out with my final query?
SELECT
date_part('year', sales.date) AS year,
stores.type,
AVG(sales_by_sqft)
FROM
(SELECT
SUM((sales.weekly_sales)/stores.size) AS sales_by_sqft
FROM SALES
INNER JOIN stores ON sales.store = stores.store
GROUP BY sales.store) AS sq
FROM sales
INNER JOIN stores ON sales.store = stores.store
WHERE date_part('year', date) = 2012
GROUP BY year, stores.type;
getting a syntax error on the second FROM statement
I figured it out. AVG doesn't work on money. Once I changed that data type to integer, it all fell in place
SELECT
year,
type,
ROUND(AVG(sales_by_sqft),2)AS avg_sales_by_sqft
FROM
(SELECT
date_part('year', sales.date) AS year,
stores.type,
sales.store,
stores.size,
SUM(sales.weekly_sales) AS total_sales,
SUM(sales.weekly_sales)/ AVG(stores.size) AS sales_by_sqft
FROM sales
INNER JOIN stores ON sales.store = stores.store
GROUP BY year, stores.type, sales.store, stores.size) AS sq
GROUP BY 1,2
ORDER BY 1,3 DESC;
Related
I have a table that contains employee names, sales from current year, and sales from last year. Lets call the two sales columns 2022 and 2021. Im looking to sort my table by the highest difference between this year and last years sales. For example, the highest difference would be at the top.
Currently I have it as
SELECT
DISTINCT customerid,
full_name,
"2012 Sales",
"2013 Sales"
FROM
customer_loyalty
ORDER BY "2013 Sales" DESC
limit 10;
Can i just insert a where conditon like 2013-2012 ASC?
This should work:
SELECT
DISTINCT customerid,
full_name,
`2012 Sales`,
`2013 Sales`
FROM
customer_loyalty
ORDER BY
`2013 Sales` - `2012 Sales` DESC
LIMIT 10;
I am trying to create a table with the average amount of sales divided by a cohort of users that signed up for an account in a certain month, however, I can only figure out to divide by the number of people that made a purchase in that specific month which is lower than the total amount of the cohort. How do I change the query below to make each of the avg_sucessful_transacted amounts divide by cohort 0 for each month?
thank you.
select sum (t.amount_in_dollars)/ count (distinct u.id) as Avg_Successful_Transacted, (datediff(month,[u.created:month],[t.createdon:month])) as Cohort, [u.created:month] as Months,
count (distinct u.id) as Users
from [transaction_cache as t]
left join [user_cache as u] on t.owner = u.id
where t.type = 'savings' and t.status = 'successful' and [u.created:year] > ['2017-01-01':date:year]
group by cohort, months
order by Cohort, Months
You will need to break out the cohort sizing into its own subquery or CTE in order to calculate the total number of distinct users who were created during the month which matches the cohort's basis month.
I approached this by bucketing users by the month they were created using the date_trunc('Month', <date>, <date>) function, but you may wish to approach it differently based on the specific business logic that generates your cohorts.
I don't work with Periscope, so the example query below is structured for pure Redshift, but hopefully it is easy to translate the syntax into Periscope's expected format:
WITH cohort_sizes AS (
SELECT date_trunc('Month', created)::DATE AS cohort_month
, COUNT(DISTINCT(id)) AS cohort_size
FROM user_cache u
GROUP BY 1
),
cohort_transactions AS (
SELECT date_trunc('Month', created)::DATE AS cohort_month
, createdon
, owner
, type
, status
, amount_in_dollars
, id
, created
FROM transaction_cache t
LEFT JOIN user_cache u ON t.owner = u.id
WHERE t.type = 'savings'
AND t.status = 'successful'
AND u.created > '2017-01-01'
)
SELECT SUM(t.amount_in_dollars) / s.cohort_size AS Avg_Successful_Transacted
, (datediff(MONTH, u.created, t.createdon)) AS Cohort
, u.created AS Months
, count(DISTINCT u.id) AS Users
FROM cohort_transactions t
JOIN cohort_sizes s ON t.cohort_month = s.cohort_month
LEFT JOIN user_cache AS u ON t.owner = u.id
GROUP BY s.cohort_size, Cohort, Months
ORDER BY Cohort, Months
;
Suppose, I have following tables
product_prices
product|price|date
-------+-----+----------
apple |10 |2014-03-01
-------+-----+----------
apple |20 |2014-05-02
-------+-----+----------
egg |2 |2014-03-03
-------+-----+----------
egg |4 |2015-10-12
purchases:
user|product|date
----+-------+----------
John|apple |2014-03-02
----+-------+----------
John|apple |2014-06-03
----+-------+----------
John|egg |2014-08-13
----+-------+----------
John|egg |2016-08-13
What I need is table similar to this:
name|product|purchase date |price date|price
----+-------+--------------+----------+-----
John|apple |2014-03-02 |2014-03-01|10
----+-------+--------------+----------+-----
John|apple |2014-06-03 |2014-05-02|20
----+-------+--------------+----------+-----
John|egg |2014-08-13 |2014-08-13|2
----+-------+--------------+----------+-----
John|egg |2016-08-13 |2015-10-12|4
Or "what is the price for product at this day". Where price is calculated based on date from products table.
On real DB I tried to use something similar to:
SELECT name, product, pu.date, pp.date, pp.price
FROM purchases AS pu
LEFT JOIN product_prices AS pp
ON pu.date = (
SELECT date
FROM product_prices
ORDER BY date DESC LIMIT 1);
But I keep either getting only left part of table (with (null) instead of product dates and prices) or many rows with all the combinations of prices and dates.
I would suggest changing product_prices table to use a daterange column instead (or at least a start_date and an end_date).
You can use an exclusion constraint to make sure you never have overlapping ranges for one product and an insert trigger that "closes" the "current" prices and creates a new unbounded range for the newly inserted price.
A daterange can efficiently be indexed and with that in place the query gets as easy as:
SELECT name, product, pu.date, pp.valid_during, pp.price
FROM purchases AS pu
LEFT JOIN product_prices AS pp ON pu.date <# pp.valid_during
(assuming the range column is named valid_during)
The exclusion constraint would only work however if the product was an integer (not a varchar) - but I guess your real product_purchases table uses a foreign key to some product table anyway (which is an integer).
The new table definitions could look something like this:
create table purchase_prices
(
product_id integer not null references products,
price numeric(16,4) not null,
valid_during daterange not null
);
And the constraint that prevents overlapping ranges:
alter table purchase_prices
add constraint check_price_range
exclude using gist (product_id with =, valid_during with &&);
The constraint needs the btree_gist extension.
As always improving query speed comes with a price and in this case it's the higher maintenance costs for the GiST index. You would need to run some tests to see if the easier (and most probably much faster) query outweighs the slower insert performance on purchase_prices.
Look at your scalar sub-query very closely. It is not correlated back to the outer query. In other words, it will return the same result every time: the latest date in the product_prices table. Period. Think about the query out of context:
SELECT date
FROM product_prices
ORDER BY date DESC LIMIT 1
There are two problems with it:
It will return 2015-10-12 for every row in the join and ultimately, nothing was purchased on that date, hence, null.
Your approximation of closest is that the dates are equal. Unless you have a product_prices row for every product for every single date, you'll always have misses. "Closest" implies distance and ranking.
WITH close_prices_by_purchase AS (
SELECT
p.user,
p.product,
p.date pp.date,
pp.price,
row_number() over (partition by pp.product, order by pp.date desc) as distance -- calculate distance between purchase date and price date
FROM purchases AS p
INNER JOIN product_prices AS pp on pp.product = p.product
WHERE pp.date < p.date
)
SELECT user as name, product, pu.date as purchase_date, pp.date as price_date, price
FROM close_prices_by_purchase AS cpbp
WHERE distance = 1; -- shortest distance
You can try something like this, although I am sure there's a better way:
with diffs as (
select
a.*,
b."date" as bdate,
b.price,
b."date" - a."date" as diffdays,
row_number() over (
partition by "user", a."product", a."date"
order by "user", a."product", a."date", b."date" - a."date" desc
) as sr
from purchases a
inner join product_prices b on a.product = b.product
where b."date" - a."date" < 1
)
select
"user" as "name",
product,
"date" as "purchase date",
bdate as "price date",
price
from diffs
where sr = 1
Example: https://www.db-fiddle.com/f/dwQ9EXmp1SdpNpxyV1wc6M/0
Explanation
I attempted to join both tables and find the difference between dates of purchase and price, and ranked them by closest date prior to the purchase. Rank of 1 will go to the closest date. Then, data with rank of 1 was extracted.
This is a great place to use date ranges! We know the start date of the price range and we can use a window function to get the next date. At that point, it's really easy to figure out the price on any day.
with price_ranges as
(select product,
price,
date as price_date,
daterange(date, lead(date, 1)
OVER (partition by product order by date), '[)'
) as valid_price_range from product_prices
)
select "user" as name,
purchases.product,
purchases.date,
price_date,
price
from purchases
join price_ranges on purchases.product = price_ranges.product
and purchases.date <# price_ranges.valid_price_range
order by purchases.date;
I have a table called retail which stores items and their price along with date of purchase. I want to find out total monthly count of unique items sold.
This is the sql query I tried
select date_trunc('month', date) as month, sum(count(distinct(items))) as net_result from retail group by month order by date;
But I get the following error
ERROR: aggregate function calls cannot be nested
Now I searched for similar stackoverflow posts one of which is postgres aggregate function calls may not be nested and but I am unable to replicate it to create the correct sql query.
What am I doing wrong?
From your description, it doesn't seem like you need to nest the aggregate functions, the count(distinct item) construction will give you a count of distinct items sold, like so:
select date_trunc('month', date) as month
, count(distinct items) as unique_items_sold
, count(items) as total_items_sold
from retail
group by "month"
order by "month" ;
If you had a column called item_count (say if there was row in the table for each item sold, but a sale might include, say, three widgets)
select date_trunc('month', date) as month
, count(distinct items) as unique_items_sold
, sum(item_count) as total_items_sold
from retail
group by "month"
order by "month" ;
Use subqueries:
Select month, sum(citems) as net_result
from
(select
date_trunc('month', date) as month,
count(distinct(items)) as citems
from
retail
group by month
order by date
)
I am suspect your group by statement will throw an Error because your month column are condition column and you cannot put in the same level in your query so put your full expression instead.
select
month,
sum(disct_item) as net_results
from
(select
date_trunc('month', date) as month,
count(distinct items) as disct_item
from
retail
group by
date_trunc('month', date)
order by
date) as tbl
group by
month;
You cannot make nested aggregate so you wrap first count to subquery and after that in outer you make sum to do the operation.
I have a Table that I am using to pull order details in SSRS that has when the price of a product number was changed. It has Data Changed and Updated Cost.
I am pairing up two different tables to create a report that is the cost of the package at the time of the order. Here is how I am pulling my data:
SELECT
WAREHOUSE.ActPkgCostHist.ItemNo AS [ActPkgCostHist ItemNo]
,WAREHOUSE.ActPkgCostHist.ActPkgCostDate
,WAREHOUSE.ActPkgCostHist.ActPkgCost
,ORDER.OrderHist.OrderNo
,ORDER.OrderHist.ItemNo AS [OrderHist ItemNo]
,ORDER.OrderHist.DispenseDt
FROM
WAREHOUSE.ActPkgCostHist
INNER JOIN ORDER.OrderHist
ON WAREHOUSE.ActPkgCostHist.ItemNo = ORDER.OrderHist.ItemNo
Catalog=ShippedOrders
ActPkgCostHist Table has What the cost of an Item was and what date the cost was changed.
OrderHist Table has the complete details of the order except the ActPkgCost at the time of the purchase.
I am attempting to create a table that Has order number, the date of the order and the package cost at the time of the order.
The ROW_NUMBER function is very useful for cases like this.
SELECT WAREHOUSE.ActPkgCostHist.ItemNo AS [ActPkgCostHist ItemNo]
,WAREHOUSE.ActPkgCostHist.ActPkgCostDate
,WAREHOUSE.ActPkgCostHist.ActPkgCost
,ORDER.OrderHist.OrderNo
,ORDER.OrderHist.ItemNo AS [OrderHist ItemNo]
,ORDER.OrderHist.DispenseDt
FROM ORDER.OrderHist
INNER JOIN (
SELECT ItemNo, ActPkgCostDate, ActPkgCost
, ROW_NUMBER() OVER (PARTITION BY ItemNo ORDER BY ActPkgCostDate DESC) as RN
FROM WAREHOUSE.ActPkgCostHist
--if there are future dated changes, limit ActPkgCostDate to be <= the current date
) ActPkgCostHist on ActPkgCostHist.ItemNo = OrderHist.ItemNo
WHERE RN = 1
What this subquery does is group the cost history by ItemNo. Then for each one, it ranks the changes by recency with the most recent change being 1. Then in the main query you filter it to just rows with a 1.
For each item in each order you have to find the latest cost date and use it when joining with the cost table
SELECT C.ItemNo AS [ActPkgCostHist ItemNo],
C.ActPkgCostDate,
C.ActPkgCost,
O.OrderNo,
O.ItemNo AS [OrderHist ItemNo],
O.DispenseDt
FROM WAREHOUSE.ActPkgCostHist AS C
-- JOIN order detail with cost table in order to define the cost date per item/order
INNER JOIN (SELECT Max(CH.ActPkgCostDate) AS ItemCostDate,
OH.OrderNo,
OH.ItemNo,
OH.DispenseDt
FROM WAREHOUSE.ActPkgCostHist AS CH
INNER JOIN ORDER.OrderHist AS OH
ON CH.ItemNo = OH.ItemNo
-- Get the latest cost date only from dates before order date
WHERE CH.ActPkgCostDate <= OH.DispenseDt
GROUP BY OH.OrderNo,
OH.ItemNo,
OH.DispenseDt) AS O
ON C.ItemNo = O.ItemNo
AND C.ActPkgCostDate = O.ItemCostDate