I am having a db names products where i wanted to select the price of each product based on the id, but the price that i stored in the table is from different sources. So i want one latest price from each of the source.
My table looks like this
id | name | source | updated_at | price
1 | ace | vanil | ... | 100
2 | vax | vanil | ... | 101
3 | tax | sunyil | ... | 200
1 | ace | sunyil | latest | 99.5
2 | vax | sunyil | latest | 100.5
3 | tax | vanil | latest | 199.5
3 | tax | vanil | ... | 220
3 | tax | vanil | ... | 211
3 | tax | vanil | ... | 205
3 | tax | sunyil | ... | 211
3 | tax | vanil | ... | 220
3 | tax | sunyil |latest_time | 220
1 | ace | sunyil | ... | 101
i want the output to be like this when my where condition is for id=3
id | name | source | updated_at | price
3 | tax | vanil | latest time| 199.5
3 | tax | sunyil | latest time| 220
i tried running the
select * from products WHERE id= '3' ORDER BY updated_at DESC LIMIT 1
but this one brings only one row irrespective of the source
could any one help me out with this. I am extremely new to postgres and sql queries. I would really appreciate your help.
It's not really clear what you want to do. If you would like to sum the price for the product with id 3 not having the text "..." in the column "updated_at", you can do this query:
SELECT id, name, source, updated_at, SUM(price) FROM products
WHERE id = 3 and updated_at != '...'
GROUP BY id, name, source, updated_at ORDER BY updated_at;
See this example and try out: db<>fiddle
Modify the query to your desires if necessary.
Using DISTINCT ON:
SELECT DISTINCT ON (id, source) *
FROM products
WHERE id = 3
ORDER BY id, source, updated_at DESC;
Related
query which calculates the total amount in dollars of stolen goods for each month for restricted and neutral items.
I have 2 tables
first
| UPC | item | in_stock | price | ship_day | class |
1 | 101 | 'generator' | 16 | 5999 | '12-1-2065'| 'restricted'
2 | 102 | 'blank tape' | 30 | 3000 | '12-1-2065'| 'neutral'
second
| UPC | unit_stolen |
1 | 101 | 4 |
1 | 401 | 2 |
If I understand correctly, this is basically a join and group by:
select date_trunc('mon', f.ship_day) as yyyymm,
sum(f.price * s.unit_stolen) filter (where f.class = 'restricted'),
sum(f.price * s.unit_stolen) filter (where f.class = 'neutral')
from first f join
second s
on f.upc = s.upc
group by date_trunc('mon', f.ship_day)
I have a system to track orders and related expenditures. This is a Rails app running on PostgreSQL. 99% of my app gets by with plain old Rails Active Record call etc. This one is ugly.
The expenditures table look like this:
+----+----------+-----------+------------------------+
| id | category | parent_id | note |
+----+----------+-----------+------------------------+
| 1 | order | nil | order with no invoices |
+----+----------+-----------+------------------------+
| 2 | order | nil | order with invoices |
+----+----------+-----------+------------------------+
| 3 | invoice | 2 | invoice for order 2 |
+----+----------+-----------+------------------------+
| 4 | invoice | 2 | invoice for order 2 |
+----+----------+-----------+------------------------+
Each expenditure has many expenditure_items and can the orders can be parents to the invoices. That table looks like this:
+----+----------------+-------------+-------+---------+
| id | expenditure_id | cbs_item_id | total | note |
+----+----------------+-------------+-------+---------+
| 1 | 1 | 1 | 5 | Fuit |
+----+----------------+-------------+-------+---------+
| 2 | 1 | 2 | 15 | Veggies |
+----+----------------+-------------+-------+---------+
| 3 | 2 | 1 | 123 | Fuit |
+----+----------------+-------------+-------+---------+
| 4 | 2 | 2 | 456 | Veggies |
+----+----------------+-------------+-------+---------+
| 5 | 3 | 1 | 34 | Fuit |
+----+----------------+-------------+-------+---------+
| 6 | 3 | 2 | 76 | Veggies |
+----+----------------+-------------+-------+---------+
| 7 | 4 | 1 | 26 | Fuit |
+----+----------------+-------------+-------+---------+
| 8 | 4 | 2 | 98 | Veggies |
+----+----------------+-------------+-------+---------+
I need to track a few things:
amounts left to be invoiced on orders (thats easy)
above but rolled up for each cbs_item_id (this is the ugly part)
The cbs_item_id is basically an accounting code to categorize the money spent etc. I have visualized what my end result would look like:
+-------------+----------------+-------------+---------------------------+-----------+
| cbs_item_id | expenditure_id | order_total | invoice_total | remaining |
+-------------+----------------+-------------+---------------------------+-----------+
| 1 | 1 | 5 | 0 | 5 |
+-------------+----------------+-------------+---------------------------+-----------+
| 1 | 2 | 123 | 60 | 63 |
+-------------+----------------+-------------+---------------------------+-----------+
| | | | Rollup for cbs_item_id: 1 | 68 |
+-------------+----------------+-------------+---------------------------+-----------+
| 2 | 1 | 15 | 0 | 15 |
+-------------+----------------+-------------+---------------------------+-----------+
| 2 | 2 | 456 | 174 | 282 |
+-------------+----------------+-------------+---------------------------+-----------+
| | | | Rollup for cbs_item_id: 2 | 297 |
+-------------+----------------+-------------+---------------------------+-----------+
order_total is the sum of total for all the expenditure_items of the given order ( category = 'order'). invoice_total is the sum of total for all the expenditure_items with parent_id = expenditures.id. Remaining is calculated as the difference (but not greater than 0). In real terms the idea here is you place and order for $1000 and $750 of invoices come in. I need to calculate that $250 left on the order (remaining) - broken down into each category (cbs_item_id). Then I need the roll-up of all the remaining values grouped by the cbs_item_id.
So for each cbs_item_id I need group by each order, find the total for the order, find the total invoiced against the order then subtract the two (also can't be negative). It has to be on a per order basis - the overall aggregate difference will not return the expected results.
In the end looking for a result something like this:
+-------------+-----------+
| cbs_item_id | remaining |
+-------------+-----------+
| 1 | 68 |
+-------------+-----------+
| 2 | 297 |
+-------------+-----------+
I am guessing this might be a combination of GROUP BY and perhaps a sub query or even CTE (voodoo to me). My SQL skills are not that great and this is WAY above my pay grade.
Here is a fiddle for the data above:
http://sqlfiddle.com/#!17/2fe3a
Alternate fiddle:
https://dbfiddle.uk/?rdbms=postgres_11&fiddle=e9528042874206477efbe0f0e86326fb
This query produces the result you are looking for:
SELECT cbs_item_id, sum(order_total - invoice_total) AS remaining
FROM (
SELECT cbs_item_id
, COALESCE(e.parent_id, e.id) AS expenditure_id -- ①
, COALESCE(sum(total) FILTER (WHERE e.category = 'order' ), 0) AS order_total -- ②
, COALESCE(sum(total) FILTER (WHERE e.category = 'invoice'), 0) AS invoice_total
FROM expenditures e
JOIN expenditure_items i ON i.expenditure_id = e.id
GROUP BY 1, 2 -- ③
) sub
GROUP BY 1
ORDER BY 1;
db<>fiddle here
① Note how I assume a saner table definition with expenditures.parent_id being integer, and true NULL instead of the string 'nil'. This allows the simple use of COALESCE.
② About the aggregate FILTER clause:
Aggregate columns with additional (distinct) filters
③ Using short syntax with ordinal numbers of an SELECT list items. Example:
Select first row in each GROUP BY group?
can I get the total of all the remaining for all rows or do I need to wrap that into another sub select?
There is a very concise option with GROUPING SETS:
...
GROUP BY GROUPING SETS ((1), ()) -- that's all :)
db<>fiddle here
Related:
Converting rows to columns
I am still very new to SQL and Tableau however I am trying to work myself towards achieving a personal project of mine.
Table A; shows a table which contains the defect quantity per product category and when it was raised
+--------+-------------+--------------+-----------------+
| Issue# | Date_Raised | Category_ID# | Defect_Quantity |
+--------+-------------+--------------+-----------------+
| PCR12 | 11-Jan-2019 | Product#1 | 14 |
| PCR13 | 12-Jan-2019 | Product#1 | 54 |
| PCR14 | 5-Feb-2019 | Product#1 | 5 |
| PCR15 | 5-Feb-2019 | Product#2 | 7 |
| PCR16 | 20-Mar-2019 | Product#1 | 76 |
| PCR17 | 22-Mar-2019 | Product#2 | 5 |
| PCR18 | 25-Mar-2019 | Product#1 | 89 |
+--------+-------------+--------------+-----------------+
Table B; shows the consumption quantity of each product by month
+-------------+--------------+-------------------+
| Date_Raised | Category_ID# | Consumed_Quantity |
+-------------+--------------+-------------------+
| 5-Jan-2019 | Product#1 | 100 |
| 17-Jan-2019 | Product#1 | 200 |
| 5-Feb-2019 | Product#1 | 100 |
| 8-Feb-2019 | Product#2 | 50 |
| 10-Mar-2019 | Product#1 | 100 |
| 12-Mar-2019 | Product#2 | 50 |
+-------------+--------------+-------------------+
END RESULT
I would like to create a table/bar chart in tableau that shows that Defect_Quantity/Consumed_Quantity per month, per Category_ID#, so something like this below;
+----------+-----------+-----------+
| Month | Product#1 | Product#2 |
+----------+-----------+-----------+
| Jan-2019 | 23% | |
| Feb-2019 | 5% | 14% |
| Mar-2019 | 89% | 10% |
+----------+-----------+-----------+
WHAT I HAVE TRIED SO FAR
Unfortunately i have not really done anything, i am struggling to understand how do i get rid of the duplicates upon joining the tables based on Category_ID#.
Appreciate all the help I can receive here.
I can think of doing left joins on both product1 and 2.
select to_char(to_date(Date_Raised,'d-mon-yyyy'),'mon-yyyy')
, (p2.product1 - sum(case when category_id='Product#1' then Defect_Quantity else 0 end))/p2.product1 * 100
, (p2.product2 - sum(case when category_id='Product#2' then Defect_Quantity else 0 end))/p2.product2 * 100
from tableA t1
left join
(select to_char(to_date(Date_Raised,'d-mon-yyyy'),'mon-yyyy') Date_Raised
, sum(Comsumed_Quantity) as product1 tableB
where category_id = 'Product#1'
group by to_char(to_date(Date_Raised,'d-mon-yyyy'),'mon-yyyy')) p1
on p1.Date_Raised = t1.Date_Raised
left join
(select to_char(to_date(Date_Raised,'d-mon-yyyy'),'mon-yyyy') Date_Raised
, sum(Comsumed_Quantity) as product2 tableB
where category_id = 'Product#2'
group by to_char(to_date(Date_Raised,'d-mon-yyyy'),'mon-yyyy')) p2
on p2.Date_Raised = t1.Date_Raised
group by to_char(to_date(Date_Raised,'d-mon-yyyy'),'mon-yyyy')
By using ROW_NUMBER() OVER (PARTITION BY ORDER BY ) as RN, you can remove duplicate rows. As of your end result you should extract month from date and use pivot to achieve.
I would do this as:
select to_char(date_raised, 'YYYY-MM'),
(sum(case when product = 'Product#1' then defect_quantity end) /
sum(case when product = 'Product#1' then consumed_quantity end)
) as product1,
(sum(case when product = 'Product#2' then defect_quantity end) /
sum(case when product = 'Product#2' then consumed_quantity end)
) as product2
from ((select date_raised, product, defect_quantity, 0 as consumed_quantity
from a
) union all
(select date_raised, product, 0 as defect_quantity, consumed_quantity
from b
)
) ab
group by to_char(date_raised, 'YYYY-MM')
order by min(date_raised);
(I changed the date format because I much prefer YYYY-MM, but that is irrelevant to the logic.)
Why do I prefer this method? This will include all months where there is a row in either table. I don't have to worry that some months are inadvertently filtered out, because there are missing production or defects in one month.
I'm trying to select some information from a database.
I get a database with columns like:
Ident,Name,Length,Width,Quantity,Planned
Table data is as follow
+-----------+-----------+---------+---------+------------+---------+
| Ident | Name | Length | Width | Quantity | Planned |
+-----------+-----------+---------+---------+------------+---------+
| 12345 | Name1 | 1500 | 1000 | 20 | 5 |
| 23456 | Name1 | 1500 | 1000 | 30 | 13 |
| 34567 | Name1 | 2500 | 1000 | 10 | 2 |
| 45678 | Name1 | 2500 | 1000 | 10 | 4 |
| 56789 | Name1 | 1500 | 1200 | 20 | 3 |
+-----------+-----------+---------+---------+------------+---------+
my desired result, would be to group rows where "Name,Length and Width" are equal, sum the "Quantity" and reduce it by the sum of "Planned"
e.g:
- Name1,1500,1000,32 --- (32 because (20+30)-(5+13))
- Name1,2500,1000,14 --- (14 because (10+10)-(2+4)))
- Name1,1500,1200,17
now I got problems how to group or join these information to get the wished select. may be some you of can help me.. if further information's required, please write it in comment.
You can achieve it by grouping your table and subtract sums of Quantity and Planned.
select
Name
,Length
,Width
,sum(Quantity) - sum(Planned)
from yourTable
group by Name,Length,Width
select
A1.Name,A1.Length,A1.Width,((A1.Quantity + A2.Quantity) -(A1.Planned+A2.Planned))
from `Table` AS A1, `Table` AS A2
where A1.Name = A2.Name and A1.Length = A2.Length and A1.Width = A2.Width
group by (whatever)
So you are comparing these columns form the same table?
I have a source table that has a few different prices for each product (depending on the order quantity). Those prices are listed vertically, so each product could have more than one row to display its prices.
Example:
ID | Quantity | Price
--------------------------
001 | 5 | 100
001 | 15 | 90
001 | 50 | 80
002 | 10 | 20
002 | 20 | 15
002 | 30 | 10
002 | 40 | 5
The other table I have is the result table in which there is only one row for each product, but there are five columns that each could contain the quantity and price for each row of the source table.
Example:
ID | Quantity_1 | Price_1 | Quantity_2 | Price_2 | Quantity_3 | Price_3 | Quantity_4 | Price_4 | Quantity_5 | Price_5
---------------------------------------------------------------------------------------------------------------------------
001 | | | | | | | | | |
002 | | | | | | | | | |
Result:
ID | Quantity_1 | Price_1 | Quantity_2 | Price_2 | Quantity_3 | Price_3 | Quantity_4 | Price_4 | Quantity_5 | Price_5
---------------------------------------------------------------------------------------------------------------------------
001 | 5 | 100 | 15 | 90 | 50 | 80 | | | |
002 | 10 | 20 | 20 | 15 | 30 | 10 | 40 | 5 | |
Here is my Python/SQL solution for this (I'm fully aware that this could not work in any way, but this was the only way for me to show you my interpretation of a solution to this problem):
For Each result_ID In result_table.ID:
Subselect = (SELECT * FROM source_table WHERE source_table.ID = result_ID ORDER BY source_table.Quantity) # the Subselect should only contain rows where the IDs are the same
For n in Range(0, len(Subselect)): # n (index) should start from 0 to last row - 1
price_column_name = 'Price_' & (n + 1)
quantity_column_name = 'Quantity_' & (n + 1)
(UPDATE result_table
SET result_table.price_column_name = Subselect[n].Price, # this should be the price of the n-th row in Subselect
result_table.quantity_column_name = Subselect[n].Quantity # this should be the quantity of the n-th row in Subselect
WHERE result_table.ID = Subselect[n].ID)
I honestly have no idea how to do this with only SQL or VBA (those are the only languages I'd be able to use -> MS-Access).
This is a pain in MS Access. If you can enumerate the values, you can pivot them.
If we assume that price is unique (or quantity or both), then you can generate such a column:
select id,
max(iif(seqnum = 1, quantity, null)) as quantity_1,
max(iif(seqnum = 1, price, null)) as price_1,
. . .
from (select st.*,
(select count(*)
from source_table st2
where st2.id = st.id and st2.price >= st.price
) as seqnum
from source_table st
) st
group by id;
I should note that another solution would use data frames in Python. If you want to take that route, ask another question and tag it with the appropriate Python tags. This question is clearly a SQL question.