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])
Related
Tried to see if this was asked anywhere else but doesn't seem like it. Trying to create a sql query to give me the date difference in days between '2022-10-01' and the date when our impression sum hits our cap of 5.
For context, we may see duplicate dates because someone revisit our website that day so we'll get a different session number to pair with that count. Here's an example table of one individual and how many impressions logged.
My goal is to get the number of days it takes to hit an impression cap of 5. So for this individual, they would hit the cap on '2022-10-07' and the days between '2022-10-01' and '2022-10-07' is 6. I am also calculating the difference before/after '2023-01-01' since I need this count for Q4 of '22 and Q1 of '23 but will not include in the example table. I have other individuals to include but for the purpose of asking here, I kept it to one.
Current Query:
select
click_date,
case
when date(click_date) < date('2023-01-01') and sum(impression_cnt = 5) then datediff('day', '2022-10-01', click_date)
when date(click_date) >= date('2023-01-01') and sum(impression_cnt = 5) then datediff('day', '2023-01-01', click_date)
else 0
end days_to_capped
from table
group by customer, click_date, impression_cnt
customer
click date
impression_cnt
123456
2022-10-05
2
123456
2022-10-05
1
123456
2022-10-06
1
123456
2022-10-07
1
123456
2022-10-11
1
123456
2022-10-11
3
Result Table
customer
days_to_cap
123456
6
I'm currently only getting 0 days and then 81 days once it hits 2022-12-21 (last date) for this individual so i know I need to fix my query. Any help would be appreciated!
Edited: This is in snowflake!
So, the issue with your query is that the sum is being calculated at the level that you are grouping by, which is every field, so it will always just be the value of the impressions field every time.
What you need to do is a running sum, which is a SUM() OVER (PARTITION BY...) statement. And then qualify the results of that:
First, just to get the data that you have:
with x as (
select *
from values
(123456,'2022-10-05'::date,2),
(123456,'2022-10-05'::date,1),
(123456,'2022-10-06'::date,1),
(123456,'2022-10-07'::date,1),
(123456,'2022-10-11'::date,1),
(123456,'2022-10-11'::date,3) x (customer,click_date,impression_cnt)
)
Then, I query the CTE to do the running sum with a QUALIFY statement to choose the record that actually has the value I'm looking for
select
customer,
case
when click_date < '2023-01-01'::date and sum(impression_cnt) OVER (partition by customer order by click_date) = 5 then datediff('day', '2022-10-01', click_date)
when click_date >= '2023-01-01'::date and sum(impression_cnt) OVER (partition by customer order by click_date) = 5 then datediff('day', '2023-01-01', click_date)
else 0
end days_to_capped
from x
qualify days_to_capped > 0;
The qualify filters your results to just the record that you cared about.
I'm working on this query, but I have Error_code:ORA-00979 beacuse i dont want group by for a.year that i use in condition:
Any tips?
Thanks
select
a.provincia_desc,
a.VOLTAGE_LEVEL,
sum(cnt) / decode(mod(to_number(a.year),4),0,1464,1460) avg
--case
--when mod(to_number(a.year),4)=0 then sum(cnt)/1464
--else sum(cnt)/1460
--end avg
from
(select year ....)a
group by a.provincia_desc,a.VOLTAGE_LEVEL--, a.year
order by avg desc
Hmm... The query as you wrote it doesn't make any sense. You sum a quantity cnt over all of subquery a, then you divide by a number that is either 1464 or 1460 depending on whether a "year" is a leap year or not, but the "year" is not included in the result. So imagine you have years 2001 and 2004 in your subquery a. In the result set you don't have a row for 2001 and another for 2004; you want everything grouped together. So what should be the denominator - 1460 or 1464?
Now, 1460 and 1464 are the numbers of six-hour periods in leap and non-leap years. I suspect you didn't want to divide by 1464 or 1460 (if you DON'T want the result broken down by year - if you do, then the query with a.year in group by is fine, but you said that's not what you want.) Instead, to compute the correct average you must SUM 1460 and 1464 for non-leap and leap years in your table. So, the denominator shouldn't be what you put in there; instead, it should be
sum(case when mod(to_number(a.year), 4) = 0 then 1464 else 1460 end)
so the complete expression should be
sum(cnt) / sum(case when mod(to_number(a.year), 4) = 0 then 1464 else 1460 end)
With this change you will not need to include a.year in group by, because you are in fact aggregating over all years (albeit through a complex formula).
This assumes your base data is for full years. What if your data only starts on March 23, 2001? In that case, it would be much better to compute the number of days by max(row_date) - min(row_date) from the base table, and then multiply by 4 to get the number of six-hour periods. This will work even better if the data starts at 9:00 AM on March 23; then you will have fractional periods.
Two more notes: Not all years divisible by 4 are leap years. You may be OK but only by luck, since 2000 was in fact a leap year and your data probably doesn't go back to 1900 or forward to 2100, but it may (or may not) be important to keep that in mind. And, you shouldn't use reserved Oracle words, like year, for object names or aliases. Use yr or other similar names.
Good luck!
I think this would work:
select
a.provincia_desc,
a.VOLTAGE_LEVEL,
sum(cnt / decode(mod(to_number(a.year),4),0,1464,1460)) avg
--case
--when mod(to_number(a.year),4)=0 then sum(cnt)/1464
--else sum(cnt)/1460
--end avg
from
(select year ....)a
group by a.provincia_desc,a.VOLTAGE_LEVEL--, a.year
order by avg desc
Changed the summation to include the decode.
I think you are going to need to do the aggregation twice to get accurate results:
select a.provincia_desc, a.VOLTAGE_LEVEL,
sum(sumcnt) / sum(numperiods) as avg
from (select a.provincia_desc, a.VOLTAGE_LEVEL,
sum(cnt) as sumcnt,
(case when mod(to_number(a.year), 4) = 0 then 1464 else 1460 end) as numperiods
from (select year ....) a
group by a.provincia_desc, a.VOLTAGE_LEVEL, a.year
) t
group by a.provincia_desc, a.VOLTAGE_LEVEL
order by avg desc
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.
I have a pretty huge table with columns dates, account, amount, etc. eg.
date account amount
4/1/2014 XXXXX1 80
4/1/2014 XXXXX1 20
4/2/2014 XXXXX1 840
4/3/2014 XXXXX1 120
4/1/2014 XXXXX2 130
4/3/2014 XXXXX2 300
...........
(I have 40 months' worth of daily data and multiple accounts.)
The final output I want is the average amount of each account each month. Since there may or may not be record for any account on a single day, and I have a seperate table of holidays from 2011~2014, I am summing up the amount of each account within a month and dividing it by the number of business days of that month. Notice that there is very likely to be record(s) on weekends/holidays, so I need to exclude them from calculation. Also, I want to have a record for each of the date available in the original table. eg.
date account amount
4/1/2014 XXXXX1 48 ((80+20+840+120)/22)
4/2/2014 XXXXX1 48
4/3/2014 XXXXX1 48
4/1/2014 XXXXX2 19 ((130+300)/22)
4/3/2014 XXXXX2 19
...........
(Suppose the above is the only data I have for Apr-2014.)
I am able to do this in a hacky and slow way, but as I need to join this process with other subqueries, I really need to optimize this query. My current code looks like:
<!-- language: lang-sql -->
select
date,
account,
sum(amount/days_mon) over (partition by last_day(date))
from(
select
date,
-- there are more calculation to get the account numbers,
-- so this subquery is necessary
account,
amount,
-- this is a list of month-end dates that the number of
-- business days in that month is 19. similar below.
case when last_day(date) in ('','',...,'') then 19
when last_day(date) in ('','',...,'') then 20
when last_day(date) in ('','',...,'') then 21
when last_day(date) in ('','',...,'') then 22
when last_day(date) in ('','',...,'') then 23
end as days_mon
from mytable tb
inner join lookup_businessday_list busi
on tb.date = busi.date)
So how can I perform the above purpose efficiently? Thank you!
This approach uses sub-query factoring - what other RDBMS flavours call common table expressions. The attraction here is that we can pass the output from one CTE as input to another. Find out more.
The first CTE generates a list of dates in a given month (you can extend this over any range you like).
The second CTE uses an anti-join on the first to filter out dates which are holidays and also dates which aren't weekdays. Note that Day Number varies depending according to the NLS_TERRITORY setting; in my realm the weekend is days 6 and 7 but SQL Fiddle is American so there it is 1 and 7.
with dates as ( select date '2014-04-01' + ( level - 1) as d
from dual
connect by level <= 30 )
, bdays as ( select d
, count(d) over () tot_d
from dates
left join holidays
on dates.d = holidays.hol_date
where holidays.hol_date is null
and to_number(to_char(dates.d, 'D')) between 2 and 6
)
select yt.account
, yt.txn_date
, sum(yt.amount) over (partition by yt.account, trunc(yt.txn_date,'MM'))
/tot_d as avg_amt
from your_table yt
join bdays
on bdays.d = yt.txn_date
order by yt.account
, yt.txn_date
/
I haven't rounded the average amount.
You have 40 month of data, this data should be very stable.
I will assume that you have a cold body (big and stable easily definable range of data) and hot tail (small and active part).
Next, I would like to define a minimal period. It is a data range that is a smallest interval interesting for Business.
It might be year, month, day, hour, etc. Do you expect to get questions like "what was averege for that account between 1900 and 12am yesterday?".
I will assume that the answer is DAY.
Then,
I will calculate sum(amount) and count() for every account for every DAY of cold body.
I will not create a dummy records, if particular account had no activity on some day.
and I will save day, account, total amount, count in a TABLE.
if there are modifications later to the cold body, you delete and reload affected day from that table.
For hot tail there might be multiple strategies:
Do the same as above (same process, clear to support)
always calculate on a fly
use materialized view as an averege between 1 and 2.
Cold body table totalc could also be implemented as materialized view, but if data never change - no need to rebuild it.
With this you go from (number of account) x (number of transactions per day) x (number of days) to (number of account)x(number of active days) number of records.
That should speed up all following calculations.
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