I have the following View in PostgreSQL:
idshipment idorder quantity_order date quantity_in_shipment percent_sent
50 1 1020 1.1.16 432 42
51 1 1020 17.1.16 299 71
51 1 1020 20.1.16 144 85
51 1 1020 45.1.16 145 100
52 2 1 3.1.17 5 100
This View shows shipments per order.
For example:
idorder=1 was sent by 4 shipments:
quantity in first shipment is 432 which means 42% of order was sent
quantity in second shipment is 299 which means 71% of order was sent
quantity in third shipment is 144 which means 85% of order was sent
quantity in forth shipment is 145 which means 100% of order was sent
I need a query which will show me the first date where each order was sent above 75%. meaning each order shows only one row.
For the above data I should see:
idorder date
1 20.1.16 (cause its 85% first time above 75%)
2 3.1.17 (cause its 100% first time above 75%)
How can i do that?
You can use distinct on:
select distinct on (t.idshipment) t.*
from t
where t.percent_sent >= 75
order by t.idshipment, t.percent_sent asc;
Try something like this:
SELECT iorder, MIN("date") AS "date"
FROM your_view
WHERE percent_sent >= 75
GROUP BY iorder
use group by to get only one record per idorder and MIN() to aggregate date by selecting the earliest date
I created a table call shipment that has data like you provided:
and execute this query
SELECT s.idorder, MIN(s.date) as date
FROM shipment s
WHERE percent_sent >= 75
GROUP BY s.idorder
result:
idorder date
----------- ----------
1 2016-01-20
2 2017-03-01
Related
I have a simple table that contains the customer email, their order count (so if this is their 1st order, 3rd, 5th, etc), the date that order was created, the value of that order, and the total order count for that customer.
Here is what my table looks like
Email Order Date Value Total
r2n1w#gmail.com 1 12/1/2016 85 5
r2n1w#gmail.com 2 2/6/2017 125 5
r2n1w#gmail.com 3 2/17/2017 75 5
r2n1w#gmail.com 4 3/2/2017 65 5
r2n1w#gmail.com 5 3/20/2017 130 5
ation#gmail.com 1 2/12/2018 150 1
ylove#gmail.com 1 6/15/2018 36 3
ylove#gmail.com 2 7/16/2018 41 3
ylove#gmail.com 3 1/21/2019 140 3
keria#gmail.com 1 8/10/2018 54 2
keria#gmail.com 2 11/16/2018 65 2
What I want to do is calculate the time average between purchase for each customer. So lets take customer ylove. First purchase is on 6/15/18. Next one is 7/16/18, so thats 31 days, and next purchase is on 1/21/2019, so that is 189 days. Average purchase time between orders would be 110 days.
But I have no idea how to make SQL look at the next row and calculate based on that, but then restart when it reaches a new customer.
Here is my query to get that table:
SELECT
F.CustomerEmail
,F.OrderCountBase
,F.Date_Created
,F.Total
,F.TotalOrdersBase
FROM #FullBase F
ORDER BY f.CustomerEmail
If anyone can give me some suggestions, that would be greatly appreciated.
And then maybe I can calculate value differences (in percentage). So for example, ylove spent $36 on their first order, $41 on their second which is a 13% increase. Then their second order was $140 which is a 341% increase. So on average, this customer increased their purchase order value by 177%. Unrelated to SQL, but is this the correct way of calculating a metric like this?
looking to your sample you clould try using the diff form min and max date divided by total
select email, datediff(day, min(Order_Date), max(Order_Date))/(total-1) as avg_days
from your_table
group by email
and for manage also the one order only
select email,
case when total-1 > 0 then
datediff(day, min(Order_Date), max(Order_Date))/(total-1)
else datediff(day, min(Order_Date), max(Order_Date)) end as avg_days
from your_table
group by email
The simplest formulation is:
select email,
datediff(day, min(Order_Date), max(Order_Date)) / nullif(total-1, 0) as avg_days
from t
group by email;
You can see this is the case. Consider three orders with od1, od2, and od3 as the order dates. The average is:
( (od2 - od1) + (od3 - od2) ) / 2
Check the arithmetic:
--> ( od2 - od1 + od3 - od2 ) / 2
--> ( od3 - od1 ) / 2
This pretty obviously generalizes to more orders.
Hence the max() minus min().
I looked at some SQL Server running total examples, but I can't manage thing like this.
I have a table where I have columns id, name, type of operation, date, value.
I want to calculate balance for each record. Balance should be calculated like this:
Starting balance must be 0 and then if operation type is IN there will be plus, if operation is OUT there will be minus. Each next record should see previous record balance and then +value or -value depending on operation Type.
This operation should be ordered by date (not Id).
For example, if the table looks like this:
ID Name Op_Type Date Value
1 box Out 2017-05-13 15
2 table In 2017-04-31 65
3 box2 In 2017-05-31 65
then result should look like this
ID Name Op_Type Date Value Balance
2 table In 2017-04-31 65 65
1 box Out 2017-05-13 15 50
3 box2 In 2017-05-31 65 115
result of this code :
select *,
sum(case when Op_Type = 'Out' then -Value else Value end)Over(Order by [Date]) as Balance
From Yourtable
is:
ID Date Type Value Balance
143 2016-12-31 In 980 664.75
89 2016-12-31 Out 300 664.75
90 2016-12-31 Out 80 664.75
But I expect the following result:
ID Date Type Value Balance
143 2016-12-31 In 980 980
89 2016-12-31 Out 300 680
90 2016-12-31 Out 80 600
The problem with answer by Prdp is that SUM(...) OVER (ORDER BY ...) by default uses RANGE option instead of ROW.
This is why you see unexpected results when dates are not unique. This is how the default RANGE option works.
To get results that you expect spell it our explicitly:
SELECT
*
,SUM(CASE WHEN Op_Type = 'Out'
THEN -Value ELSE Value END)
OVER(ORDER BY [Date], Op_Type, ID
ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS Balance
FROM YourTable
ORDER BY [Date], Op_Type, ID;
I also added Op_Type into the ORDER BY to add positive values first in cases when there are several rows with the same date.
I added ID into the ORDER BY to make results stable in cases when there are several rows with the same date.
I have table called VoucherEntry
These are my records,
ID VoucherOnlineID TransactionNumber Store Amount
-------------------------------------------------------------
120 137 26 1001 100
126 137 22 2000 -56
128 137 30 3000 -20
133 137 11 2000 -5
Now I want to add 2 columns which is having carry amount and Balance amount. If the VoucherEntry.Amount = 100 Then carry column should be 0, other wise it should display like below
Expecting output
ID VoucherOnlineID TransactionNumber Store Carry Amount Balance
---------------------------------------------------------------------------------
120 137 26 1001 0 100 100
126 137 22 2000 100 -56 44
128 137 30 3000 44 -20 24
133 137 11 2000 24 -5 19
Update
we can sort the record By ID column or Date column, after you sort the records will display in above order
You need two variations of a Cumulative Sum:
SELECT
VoucherOnlineID
,TransactionNumber
,Store
,Coalesce(Sum(Amount) -- Cumulative Sum of previous rows
Over (PARTITION BY VoucherOnlineID
ORDER BY DATE -- or whatever determines correct order
ROWS BETWEEN Unbounded Preceding AND 1 Preceding), 0) AS Carry
,Amount
,Sum(Amount) -- Cumulative Sum including current row
Over (PARTITION BY VoucherOnlineID
ORDER BY DATE -- or whatever determines correct order
ROWS Unbounded Preceding) AS Balance
FROM VoucherEntry
sql Server 2008 and below
declare #t table(ID int,VoucherOnlineID int,TransactionNumber int,Store int,Amount int)
insert into #t VALUES
(120,137,26,1001,100)
,(126,137,22,2000,-56)
,(128,137,30,3000,-20)
,(133,137,11,2000,-5 )
select *
,isnull((Select sum(Amount) from #t t1
where t1.VoucherOnlineID=t.VoucherOnlineID
and t1.id<t.id ) ,0)Carry
,isnull((Select sum(Amount) from #t t1
where t1.VoucherOnlineID=t.VoucherOnlineID
and t1.id<=t.id ) ,0)Balance
from #t t
I have a table which contain _id, underSubheadId, wefDate, price.
Whenever a product is created or price is edited an entry is made in this table also.
What I want is if I enter a date, I get the latest price of all distinct UnderSubheadIds before the date (or on that date if no entry found)
_id underHeadId wefDate price
1 1 2016-11-01 5
2 2 2016-11-01 50
3 1 2016-11-25 500
4 3 2016-11-01 20
5 4 2016-11-11 30
6 5 2016-11-01 40
7 3 2016-11-20 25
8 5 2016-11-15 52
If I enter 2016-11-20 as date I should get
1 5
2 50
3 25
4 30
5 52
I have achieved the result using ROW NUMBER function in SQL SERVER, but I want this result in Sqlite which don't have such function.
Also if a date like 2016-10-25(which have no entries) is entered I want the price of the date which is first.
Like for 1 we will get price as 5 as the nearest and the 1st entry is 2016-11-01.
This is the query for SQL SERVER which is working fine. But I want it for Sqlite which don't have ROW_NUMBER function.
select underSubHeadId,price from(
select underSubHeadId,price, ROW_NUMBER() OVER (Partition By underSubHeadId order by wefDate desc) rn from rates
where wefDate<='2016-11-19') newTable
where newTable.rn=1
Thank You
This is a little tricky, but here is one way:
select t.*
from t
where t.wefDate = (select max(t2.wefDate)
from t t2
where t2.underSubHeadId = t.underSubHeadId and
t2.wefdate <= '2016-11-20'
);
select underHeadId, max(price)
from t
where wefDate <= "2016-11-20"
group by underHead;
Currently I have this table in sql database sorted by Account#.
Account# Charge_code PostingDate Balance
12345 35 1/18/2016 100
**12345 35 1/20/2016 200**
12345 61 1/23/2016 250
12345 61 1/22/2016 300
12222 41 1/20/2016 200
**12222 41 1/21/2016 250**
12222 42 1/23/2016 100
12222 42 1/25/2016 600
How do I select last row prior to the change in the charge_code column for each Account#. I highlighted the rows that I am trying to return.
The query should execute quickly with the table having tens of thousands of records.
In SQL Server 2012+, you would use lead():
select t.*
from (select t.*,
lead(charge_code) over (partition by account order by postingdate) as next_charge_code
from t
) t
where charge_code <> next_charge_code;
In earlier versions of SQL Server, you can do something similar with apply.