Select aggregrate and date range - sql

I can't figure this query out and it should be easy. But I'm at a loss.
How do you query using an aggregate SUM bound by a date range?
Given this table:
ID EmployeeID PayAmount PayDate
1 48 289.0000 2003-12-22 00:00:00.000
2 251 458.0000 2003-12-30 00:00:00.000
3 48 248.0000 2003-12-30 00:00:00.000
4 167 255.5000 2003-12-30 00:00:00.000
5 48 100.00 2004-01-31 00:00:00.000
6 251 100.00 2004-01-31 00:00:00.000
7 251 300.00 2004-02-14 00:00:00:000
I would like to run a query to see how much each employee earned during a given year. So for 2003, the results would like this:
EmployeeID TotalPaid
48 537.00
167 255.50
251 458.00
For 2004 the results would be:
EmployeeID TotalPaid
48 100.00
251 400.00

In Microsoft SQL Server you can do like this.
Grouping the data based on the Year for each EmployeeID
The data can be filtered for a particular year using HAVING clause WITH YEAR function.
This query gives data for the year 2004
SELECT EmployeeID,
SUM(PayAmount) as TotalPaid,
DATEADD(YEAR, DATEDIFF(YEAR,0, Paydate), 0) as Year
FROM Table1
GROUP BY EmployeeID, DATEADD(YEAR, DATEDIFF(YEAR,0, Paydate), 0)
HAVING YEAR(DATEADD(YEAR, DATEDIFF(YEAR,0, Paydate), 0)) =2004

Related

Price Change History in SQL Server [duplicate]

This question already has answers here:
Is there a way to access the "previous row" value in a SELECT statement?
(9 answers)
Closed 7 months ago.
I have a table in SQL Server with sales price data of items on different dates like this:
Item
Date
Price
1
2021-05-01
200
1
2021-06-11
210
1
2021-06-27
225
1
2021-08-01
250
2
2021-02-10
600
2
2021-04-21
650
2
2021-06-17
675
2
2021-07-23
700
I'm creating a table that specifies the start and end date of prices as below:
Item
DateStart
Price
DateEnd
1
2021-05-01
200
2021-06-10
1
2021-06-11
210
2021-06-26
1
2021-06-27
225
2021-07-31
1
2021-08-01
250
Today date
2
2021-02-10
600
2021-04-20
2
2021-04-21
650
2021-06-16
2
2021-06-17
675
2021-07-22
2
2021-07-23
700
Today date
As you can see, the end date is one day less than the next price change date. I also have a calendar table called "DimDates" with one row per day. I had hoped to use joins but it doesn't do what I thought it would do. Any suggestions on how to write the query? I'm using SQL Server 2016.
We can use LEAD() here along with DATEADD():
WITH cte AS (
SELECT *, DATEADD(day, -1, LEAD(Date, 1, GETDATE())
OVER (PARTITION BY Item
ORDER BY Date)) AS LastDate
FROM yourTable
)
SELECT Item, Date AS DateStart, Price, LastDate AS DateEnd
FROM cte
ORDER BY Item, Date;
Demo

Showing Two Fields With Different Timeline in the Same Date Structure

In the project I am currently working on in my company, I would like to show sales related KPIs together with Customer Score metric on SQL / Tableau / BigQuery
The primary key is order id in both tables. However, order date and the date we measure Customer Score may be different. For example the the sales information for an order that is released in Feb 2020 will be aggregated in Feb 2020, however if the customer survey is made in March 2020, the Customer Score metric must be aggregated in March 2020. And what I would like to achieve in the relational database is as follows:
Sales:
Order ID
Order Date(m/d/yyyy)
Sales ($)
1000
1/1/2021
1000
1001
2/1/2021
2000
1002
3/1/2021
1500
1003
4/1/2021
1700
1004
5/1/2021
1800
1005
6/1/2021
900
1006
7/1/2021
1600
1007
8/1/2021
1900
Customer Score Table:
Order ID
Customer Survey Date(m/d/yyyy)
Customer Score
1000
3/1/2021
8
1001
3/1/2021
7
1002
4/1/2021
3
1003
6/1/2021
6
1004
6/1/2021
5
1005
7/1/2021
3
1006
9/1/2021
1
1007
8/1/2021
7
Expected Output:
KPI
Jan-21
Feb-21
Mar-21
Apr-21
May-21
June-21
July-21
Aug-21
Sep-21
Sales($)
1000
2000
1500
1700
1800
900
1600
1900
AVG Customer Score
7.5
3
5.5
3
7
1
I couldn't find a way to do this, because order date and survey date may/may not be the same.
For sample data and expected output, click here.
I think what you want to do is aggregate your results to the month (KPI) first before joining, as opposed to joining on the ORDER_ID
For example:
with order_month as (
select date_trunc(order_date, MONTH) as KPI, sum(sales) as sales
from `testing.sales`
group by 1
),
customer_score_month as (
select date_trunc(customer_survey_date, MONTH) as KPI, avg(customer_score) as avg_customer_score
from `testing.customer_score`
group by 1
)
select coalesce(order_month.KPI,customer_score_month.KPI) as KPI, sales, avg_customer_score
from order_month
full outer join customer_score_month
on order_month.KPI = customer_score_month.KPI
order by 1 asc
Here, we aggregate the total sales for each month based on the order date, then we aggregate the average customer score for each month based on the date the score was submitted. Now we can join these two on the month value.
This results in a table like this:
KPI
sales
avg_customer_score
2021-01-01
1000
null
2021-02-01
2000
null
2021-03-01
1500
7.5
2021-04-01
1700
3.0
2021-05-01
1800
null
2021-06-01
900
5.5
2021-07-01
1600
3.0
2021-08-01
1900
7.0
2021-09-01
null
1.0
You can pivot the results of this table in Tableau, or leverage a case statement to pull out each month into its own column - I can elaborate more if that will be helpful

SQL how to count but only count one instance if two columns match?

Wondering how to select from a table:
FIELDID personID purchaseID dateofPurchase
--------------------------------------------------
2 13 147 2014-03-21 00:00:00
3 15 165 2015-03-23 00:00:00
4 13 456 2018-03-24 00:00:00
5 1 133 2018-03-21 00:00:00
6 23 123 2013-03-22 00:00:00
7 25 456 2013-03-21 00:00:00
8 25 456 2013-03-23 00:00:00
9 22 456 2013-03-28 00:00:00
10 25 589 2013-03-21 00:00:00
11 82 147 1991-10-22 00:00:00
12 82 453 2003-03-22 00:00:00
I'd like to get a result table of two columns: weekday and the number of purchases of each weekday, but only count the distinct days of purchases if done by the same person on the same day - for example since personID 25 purchased two things on 2013-03-21, that should only count as one 'thursday' instead of 2.
Basically, if the personID and the dateofPurchase are the same for more than one row, only count it once is what I want.
Here is what I have currently: It does everything correctly except it will count the above scenario under the thursday twice, when I would only want to add one:
SELECT v.wkday as day, COUNT(*) as 'absences'
FROM dbo.AttendanceRecord pr CROSS APPLY
(VALUES (CASE WHEN DATEPART(WEEKDAY, date) IN (1, 7)
THEN 'Weekend'
ELSE DATENAME(WEEKDAY, date)
END)
) v(wkday)
GROUP BY v.wkday;
to clarify:
If an item is purchased for at least one puchaseID on a specific day they will be counted as purchased for that day, and do not need to be counted again for each new purchase ID on that day.
I think you want to count distinct persons, so that would be:
COUNT(DISTINCT personid) as absences
Note that single quotes are not appropriate around column aliases. If you need to escape them, use square braces.
EDIT:
If you want to count distinct person-days, then you can use:
COUNT(DISTINCT CONCAT(personid, ':', dateofpurchase) as absences

Distinct count for entire dataset, grouped by month

I am dealing with a sales order table (ORDER) that looks roughly like this (updated 2018/12/20 to be closer to my actual data set):
SOID SOLINEID INVOICEDATE SALESAMOUNT AC
5 1 2018-11-30 100.00 01
5 2 2018-12-05 50.00 02
4 1 2018-12-12 25.00 17
3 1 2017-12-31 75.00 03
3 2 2018-01-03 25.00 05
2 1 2017-11-25 100.00 17
2 2 2017-11-27 35.00 03
1 1 2017-11-20 15.00 08
1 2 2018-03-15 30.00 17
1 3 2018-04-03 200.00 05
I'm able to calculate the average sales by SOID and SOLINEID:
SELECT SUM(SALESAMOUNT) / COUNT(DISTINCT SOID) AS 'Total Sales per Order ($)',
SUM(SALESAMOUNT) / COUNT(SOLINEID) AS 'Total Sales per Line ($)'
FROM ORDER
This seems to provide a perfectly good answer, but I was then given an additional constraint, that this count be done by year and month. I thought I could simply add
GROUP BY YEAR(INVOICEDATE), MONTH(MONTH)
But this aggregates the SOID and then performs the COUNT(DISTINCT SOID). This becomes a problem with SOIDs that appears across multiple months, which is fairly common since we invoice upon shipment.
I want to get something like this:
Year Month Total Sales Per Order Total Sales Per Line
2018 11 0.00
The sore thumb sticking out is that I need some way of defining in which month and year an SOID will be aggregated if it spans across multiple ones; for that purpose, I'd use MAX(INVOICEDATE).
From there, however, I'm just not sure how to tackle this. WITH? A subquery? Something else? I would appreciate any help, even if it's just pointing in the right direction.
You should select Year() and month() for invocedate and group by
SELECT YEAR(INVOICEDATE) year
, MONTH(INVOICEDATE) month
, SUM(SALESAMOUNT) / COUNT(DISTINCT SOID) AS 'Total Sales per Order ($)'
, SUM(SALESAMOUNT) / COUNT(SOLINEID) AS 'Total Sales per Line ($)'
FROM ORDER
GROUP BY YEAR(INVOICEDATE), MONTH(INVOICEDATE)
Here are the results, but the data sample does not have enuf rows to show Months...
SELECT
mDateYYYY,
mDateMM,
SUM(SALESAMOUNT) / COUNT(DISTINCT t1.SOID) AS 'Total Sales per Order ($)',
SUM(SALESAMOUNT) / COUNT(SOLINEID) AS 'Total Sales per Line ($)'
FROM DCORDER as t1
left join
(Select
SOID
,Year(max(INVOICEDATE)) as mDateYYYY
,Month(max(INVOICEDATE)) as mDateMM
From DCOrder
Group By SOID
) as t2
On t1.SOID = t2.SOID
Group by mDateYYYY, mDateMM
mDateYYYY mDateMM Total Sales per Order ($) Total Sales per Line ($)
2018 12 87.50 58.33
I have used new SQL still MAX(INVOICEDATE)(not above), with new 12/20 data, and excluded AC=17.
YYYY MM Total Sales per Order ($) Total Sales per Line ($)
2017 11 35.00 35.00
2018 1 100.00 50.00
2018 4 215.00 107.50
2018 12 150.00 75.00

Need help on Query

Table_Name : Order_trans_detail
Order_id Order_date Order_qty Item_id order_amount
100 12-Jan-16 1 1001 20
101 13-Feb-15 4 1001 80
103 14-Mar-16 3 1001 60
104 16-Dec-15 9 1001 180
105 17-Jan-16 1 1001 20
106 18-Feb-16 4 1001 80
107 19-Feb-16 3 1001 60
108 20-Jan-15 9 1001 180
109 21-Mar-15 3 1001 60
110 21-Apr-15 3 1001 60
Need Query to identify how many orders placed in Month of Feb-2016 as to display Month Name and count.
You need to use DATENAME and YEAR function to extract Month name and Year from date and use it in Group by to get the count
select DATENAME(MONTH,Order_date ),YEAR(Order_date), Count(*)
From Order_trans_detail
Group by DATENAME(MONTH,Order_date ),YEAR
To filter the records add Where clause
Where DATENAME(MONTH,Order_date ) = 'february' and YEAR(Order_date) = 2016
To get the result in Mon-year format use this in Select
DATENAME(MONTH,Order_date )+'-'+cast(YEAR(Order_date) as char(4))
If you are using SQL Server 2012+ to concatenate month and year use CONCAT function
CONCAT(DATENAME(MONTH,Order_date ),'-',YEAR(Order_date))
Advantage of using CONCAT is that you don't need to perform explicit conversion when concatenating Int with Varchar