I have a int field in my database which represent year and month like 201501 stands for 2015 Jan,
i need to group by reporting_date field and showcase the quarterly data .The table is in the following format .Reporting_date is an int field rather than a datetime and interest_payment is float
reporting_date interest_payment
200401 5
200402 10
200403 25
200404 15
200406 5
200407 20
200408 25
200410 10
the output of the query should like this
reporting_date interest_payment
Q1 -2004 40
Q2 -2004 20
Q3 -2004 40
Q4 -2004 10
i tried using the normal group by statement
select reporting_date , sum(interest_payment) as interest_payment from testTable
group by reporting_date
but got different result output.Any help would be appreciated
Thanks
before grouping you need to calculate report_quarter, which is equal to
(reporting_date%100-1)/3
then do select
select report_year, 'Q'+cast(report_quarter+1 as varchar(1)), SUM (interest_payment)
from
(
select
*,
(reporting_date%100 - 1)/3 as report_quarter,
reporting_date/100 as report_year
from #x
) T
group by report_year, report_quarter
order by report_year, report_quarter
I see two problems here:
You need to convert reporting_date into a quarter.
You need to SUM() the values in interest_payment for each quarter.
You seem to have the right idea for (2) already, so I'll just help with (1).
If the numbers are all 6 digits (see my comment above) you can just do some numeric manipulation to turn them into quarters.
First, convert into months by dividing by 100 and keeping the remainder: MOD(reporting_date/100).
Then, convert that into a quarter: MOD(MOD(reporting_date/100)/4)+1
Add a Q and the year if desired.
Finally, use that value in your GROUP BY.
You didn't specify which DBMS you are using, so you may have to convert the functions yourself.
Related
I have several CSV's stored to query against. Each CSV represents a month of data. I would like to count all the records in each CSV and save that data to a table as a row in the table. For instance, the table that represents May should return something that looks like this with June following. The data starts in Feb 2018 and continues to Feb 2019 so year value would be needed as well.
Month Results
----------------
May 18 1170
June 18 1167
I want to run the same query against all the tables for purposes of efficiency. I also want the query to work with all future updates eg. a March 19 table gets added, and the query will still work.
So far, I have this query.
SELECT COUNT(*)
FROM `months_data.*`
I am querying in Google Big Query using Standard SQL.
It sounds like you just want an aggregation that counts rows for each month:
SELECT
DATE_TRUNC(DATE(timestamp), MONTH) AS Month,
COUNT(*) AS Results
FROM `dataset.*`
GROUP BY month
ORDER BY month
You can use the DATE_FORMAT function if you want to control the formatting.
You seem to need union all:
select 2018 as yyyy, 2 as mm, count(*) as num
from feb2018
union all
select 2018 as yyyy, 3 as mm, count(*)
from mar2018
union all
. . .
Note that you have a poor data model. You should be storing all the data in a single table with a date column.
How do I average the last 6 months of sales within SQL?
Here are my tables and fields:
IM_ItemWhseHistoryByPeriod.FISCALCALPERIOD,
IM_ItemWhseHistoryByPeriod.FISCALCALYEAR,
And I need to average these fields
IM_ItemWhseHistoryByPeriod.DOLLARSSOLD,
IM_ItemWhseHistoryByPeriod.QUANTITYSOLD,
The hard part I'm having is understanding how to average the last whole 6 months, ie. fsicalcalperiod 2-6(inside fiscalcalyear 2017).
I'm hoping for some help on what the SQL command text should look like since I'm very new to manipulating SQL outside of the UI.
Sample Data
My Existing SQL String:
SELECT IM_ItemWhseHistoryByPeriod.ITEMCODE,
IM_ItemWhseHistoryByPeriod.DOLLARSSOLD,
IM_ItemWhseHistoryByPeriod.QUANTITYSOLD,
IM_ItemWhseHistoryByPeriod.FISCALCALPERIOD,
IM_ItemWhseHistoryByPeriod.FISCALCALYEAR
FROM MAS_AME.dbo.IM_ItemWhseHistoryByPeriod
IM_ItemWhseHistoryByPeriod
ScaisEdge Attempt #1
if fiscalyear and fiscalperiod are number you could use
select avg(IM_ItemWhseHistoryByPeriod.DOLLARSSOLD) ,
avg(IM_ItemWhseHistoryByPeriod.QUANTITYSOLD)
from my_table
where IM_ItemWhseHistoryByPeriod.FISCALCALYEAR = 2017
and IM_ItemWhseHistoryByPeriod.FISCALCALPERIOD between 2 and 6
or for each item code
select itemcode, avg(IM_ItemWhseHistoryByPeriod.DOLLARSSOLD) ,
avg(IM_ItemWhseHistoryByPeriod.QUANTITYSOLD)
from my_table
where IM_ItemWhseHistoryByPeriod.FISCALCALYEAR = 2017
and IM_ItemWhseHistoryByPeriod.FISCALCALPERIOD between 2 and 6
group by itemcode
Try the following solution and see if it works for you:
select avg(DOLLARSSOLD) as AvgDollarSod,
avg(QUANTITYSOLD) as AvgQtySold
from IM_ItemWhseHistoryByPeriod
where FISCALCALYEAR = '2017
and FISCALCALPERIOD between 2 and 6
I need find the number Sum of orders over a 3 day range. so imagine a table like this
Order Date
300 1/5/2015
200 1/6/2015
150 1/7/2015
250 1/5/2015
400 1/4/2015
350 1/3/2015
50 1/2/2015
100 1/8/2015
So I want to create a Group by Clause that Groups anything with a date that has the same Month, Year and a Day from 1-3 or 4-6, 7-9 and so on until I reach 30 days.
It seems like what I would want to do is create a case for the grouping that includes a loop of some type but I am not sure if this is the best way or if it is even possible to combine them.
An alternative might be create a case statement that creates a new column that assigns group number and then grouping by that number, month, and Year.
Unfortunately I've never used a case statement so I am not sure which method is best or how to execute them especially with a loop.
EDIT: I am using Access so it looks like I will be using IIF instead of Case
Consider the Partition Function and a crosstab, so, for example:
TRANSFORM Sum(Calendar.Order) AS SumOfOrder
SELECT Month([CalDate]) AS TheMonth, Partition(Day([Caldate]),1,31,3) AS DayGroup
FROM Calendar
GROUP BY Month([CalDate]), Partition(Day([Caldate]),1,31,3)
PIVOT Year([CalDate]);
As an aside, I hope you have not named a field / column as Date.
How about the following:
COUNT OF ORDERS
select year([Date]) as yr,
month([Date]) as monthofyr,
sum(iif((day([Date])>=1) and (day([Date])<=3),1,0)) as days1to3,
sum(iif((day([Date])>=4) and (day([Date])<=6),1,0)) as days4to6,
sum(iif((day([Date])>=7) and (day([Date])<=9),1,0)) as days7to9,
sum(iif((day([Date])>=10) and (day([Date])<=12),1,0)) as days10to12,
sum(iif((day([Date])>=13) and (day([Date])<=15),1,0)) as days13to15,
sum(iif((day([Date])>=16) and (day([Date])<=18),1,0)) as days16to18,
sum(iif((day([Date])>=19) and (day([Date])<=21),1,0)) as days19to21,
sum(iif((day([Date])>=22) and (day([Date])<=24),1,0)) as days22to24,
sum(iif((day([Date])>=25) and (day([Date])<=27),1,0)) as days25to27,
sum(iif((day([Date])>=28) and (day([Date])<=31),1,0)) as days28to31
from tbl
where [Date] between x and y
group by year([Date]),
month([Date])
Replace x and y with your date range.
The last group is days 28 to 31 of the month, so it may contain 4 days' worth of orders, for months that have 31 days.
THE ABOVE IS A COUNT OF ORDERS.
If you want the SUM of the order amounts:
SUM OF ORDER AMOUNTS
select year([Date]) as yr,
month([Date]) as monthofyr,
sum(iif((day([Date])>=1) and (day([Date])<=3),order,0)) as days1to3,
sum(iif((day([Date])>=4) and (day([Date])<=6),order,0)) as days4to6,
sum(iif((day([Date])>=7) and (day([Date])<=9),order,0)) as days7to9,
sum(iif((day([Date])>=10) and (day([Date])<=12),order,0)) as days10to12,
sum(iif((day([Date])>=13) and (day([Date])<=15),order,0)) as days13to15,
sum(iif((day([Date])>=16) and (day([Date])<=18),order,0)) as days16to18,
sum(iif((day([Date])>=19) and (day([Date])<=21),order,0)) as days19to21,
sum(iif((day([Date])>=22) and (day([Date])<=24),order,0)) as days22to24,
sum(iif((day([Date])>=25) and (day([Date])<=27),order,0)) as days25to27,
sum(iif((day([Date])>=28) and (day([Date])<=31),order,0)) as days28to31
from tbl
where [Date] between x and y
group by year([Date]),
month([Date])
I want to group a set of dated records by year, when the date is to the day. Something like:
SELECT venue, YEAR(date) AS yr, SUM(guests) AS yr_guests
FROM Events
...
GROUP BY venue, YEAR(date);
The above is giving me results instead of an error, but the results are not grouping by year and venue; they do not appear to be grouping at all.
My brute force solution would be a nested subquery: add the YEAR() AS yr as an extra column in the subquery, then do the grouping on yr in the outer query. I'm just trying to learn to do as much as possible without nesting, because nesting usually seems horribly inefficient.
I would tell you the exact SQL implementation I'm using, but I've had trouble discovering it. (I'm working through the problems on http://www.sql-ex.ru/ and if you can tell what they're using, I'd love to know.) Edited to add: Per test in comments, it is probably not SQL Server.
Edited to add the results I am getting (note the first two should be summed):
venue | yr | yr_guests
1 2012 15
1 2012 35
2 2012 12
1 2008 15
I expect those first two lines to instead be summed as
1 2012 50
Works Fine in SQL Server 2008.
See working Example here: http://sqlfiddle.com/#!3/3b0f9/6
Code pasted Below.
Create The Events Table
CREATE TABLE [Events]
( Venue INT NOT NULL,
[Date] DATETIME NOT NULL,
Guests INT NOT NULL
)
Insert the Rows.
INSERT INTO [Events] VALUES
(1,convert(datetime,'2012'),15),
(1,convert(datetime,'2012'),35),
(2,convert(datetime,'2012'),12),
(1,convert(datetime,'2008'),15);
GO
-- Testing, select newly inserted rows.
--SELECT * FROM [Events]
--GO
Run the GROUP BY Sql.
SELECT Venue, YEAR(date) AS yr, SUM(guests) AS yr_guests
FROM Events
GROUP BY venue, YEAR(date);
See the Output Results.
VENUE YR YR_GUESTS
1 2008 15
1 2012 50
2 2012 12
it depends of your database engine (or SQL)
to be sure (over different DB Systems & Versions), make a subquery
SELECT venue, theyear, SUM(guests) from (
SELECT venue, YEAR(date) AS theyear, guest
FROM Events
)
GROUP BY theyear
you make a subtable of
venue, date as theyear, guest
aaaa, 2001, brother
aaaa, 2001, bbrother
bbbb, 2001, nobody
... and so on
and then
count them
Given the following table (much simplified for the purposes of this question):
id perPeriod actuals createdDate
---------------------------------------------------------
1 14 22 2011-10-04 00:00:00.000
2 14 9 2011-10-04 00:00:00.000
3 14 3 2011-10-03 00:00:00.000
4 14 5 2011-10-03 00:00:00.000
I need a query that gives me the average daily "actuals" figure. Note, however, that there are TWO RECORDS PER DAY (often more), so I can't just do AVG(actuals).
Also, if the daily "actuals" average exceeds the daily "perPeriod" average, I want to take the perPeriod value instead of the "average" value. Thus, in the case of the first two records: The actuals average for 4th October is (22+9) / 2 = 15.5. And the perPeriod average for the same day is (14 + 14) / 2 = 14. Now, 15.5 is greater than 14, so the daily "actuals" average for that day should be the "perPeriod" average.
Hope that makes sense. Any pointers greatly appreciated.
EDIT
I need an overall daily average, not an average per date. As I said, I would love to just do AVG(actuals) on the entire table, but the complicating factor is that a particular day can occupy more than one row, which would skew the results.
Is this what you want?
First, if the second payperiod average needed to be the average across a different grouping (It doesn't in this case), then you would need to use a subquery like this:
Select t.CreatedDate,
Case When Avg(actuals) < p.PayPeriodAvg
Then Avg(actuals) Else p.PayPeriodAvg End Average
From table1 t Join
(Select CreatedDate, Avg(PayPeriod) PayPeriodAvg
From table1
Group By CreatedDate) as p
On p.CreatedDate = t.CreatedDate
Group By t.CreatedDate, p.PayPeriodAvg
or, in this case, since the PayPeriod Average is grouped on the same thing, (CreatedDate) as the actuals average, you don't need a subquery, so even easier:
Select t.CreatedDate,
Case When Avg(actuals) < Avg(PayPeriod)
Then Avg(actuals) Else Avg(PayPeriod) End Average
From table1 t
Group By t.CreatedDate
with your sample data, both of these return
CreatedDate Average
----------------------- -----------
2011-10-03 00:00:00.000 4
2011-10-04 00:00:00.000 14
SELECT DAY(createdDate), MONTH(createdDate), YEAR(createdDate), MIN(AVG(actuals), MAX(perPeriod))
FROM MyTable
GROUP BY Day(createdDate, MONTH(createdDate), YEAR(createdDate)
Try this out:
select createdDate,
case
when AVG(actuals) > max(perPeriod) then max(perPeriod)
else AVG(actuals)
end
from SomeTestTable
group by createdDate