I have 4 dimensions, which one of them is date. I need to calculate for each date, the average in the last 30 days, per each dimension value.
I have tried to run average over a partition by the 4 dimensions in a form of:
SELECT
Date, Produce,Company, Song, Revenues,
Average(case when Date between Date -Interval '31' day and Date - Interval '1' Day then Revenues else null End) over (partition by Date,Company,Song,Revenues order by Date) as "Running Average"
From
Base_Table
I get only nulls with every aggregation I tried.
Help is appreciated. Thanks
You can try below -
SELECT
Date, Produce,Company, Song, Revenues,
Average(Revenues) over (partition by Company,Song rows between 30 preceding and current row) as "Running Average"
From
Base_Table
Related
I'm trying to get the average repairs in the weekdays and weekends within the last 30 days. Each day is tagged whether it's a weekday or a weekend. Holidays are tagged as weekends.
If I use:
AVG(Completed_Repairs) OVER(PARTITION BY day_type ORDER BY UNIX_DATE(WORK_DT) RANGE BETWEEN 30 PRECEDING AND CURRENT ROW)
I only get either the average repairs for all weekdays or for all weekends in the last 30 days depending on what type of day the date is. But I also need the average for the opposite to compute a prorated monthly number. I basically would need another column with the value of the opposite day type.
If I understood correctly, not partitioning might be the way:
with
input as (
select cast('2022-10-11' as date) as WORK_DT, "weekday" as day_type, 307 as completed_repairs union all
select cast('2022-10-12' as date) as WORK_DT, "weekday" as day_type, 100 as completed_repairs union all
select cast('2022-10-09' as date) as WORK_DT, "weekend" as day_type, 750 as completed_repairs union all
select cast('2022-10-10' as date) as WORK_DT, "weekend" as day_type, 647 as completed_repairs
)
select
*,
avg(if(day_type = 'weekday', completed_repairs,0)) OVER(ORDER BY UNIX_DATE(WORK_DT) RANGE BETWEEN 30 PRECEDING AND CURRENT ROW) as avg_weekday,
avg(if(day_type = 'weekend', completed_repairs,0)) OVER(ORDER BY UNIX_DATE(WORK_DT) RANGE BETWEEN 30 PRECEDING AND CURRENT ROW) as avg_weekend,
from input
order by work_dt
You can replace the 0 by null if you don't want the weekends to impact the average of the weekdays and vice-versa.
If you'd rather have a column "matching" and a column "opposite" you can then use the result of this to write a condition depending on the day_type and the column name.
I'm trying to get the rolling 3 day average transaction amount for each day. I first grouped my data by day from the time stamp using cast:
select
cast(transaction_time as Date) As Date
, SUM(transaction_amount) as total_transaction_amount
from transactions
Group by cast(transaction_time as date)
order by cast(transaction_time as date)
now I want to get the rolling 3 day average:
select *,
avg(transaction_amount) OVER(ORDER BY transaction_time
ROWS BETWEEN 2 PRECEDING AND CURRENT ROW)
as moving_average
from transactions;
but don't know how to make both statements work together, any ideas?
You've basically done all the hard work, just need to stick them together and a CTE is great for this.
With transactions_by_day as(
select
cast(transaction_time as Date) As Date
, SUM(transaction_amount) as total_transaction_amount
from transactions
Group by cast(transaction_time as date)
order by cast(transaction_time as date))
select *,
avg(total_transaction_amount) OVER(ORDER BY date
ROWS BETWEEN 2 PRECEDING AND CURRENT ROW)
as moving_average
from transactions_by_day
I'd like to find the average monthly revenue for each sales owner--however my current query is taking the monthly total and just dividing it by the number of entries. Ultimately, I'd like to get the average by finding the total revenue for each month and then dividing it by the number of months and then eventually just finding the avg. of the past 6 months. Code as well as sample output below:
select activitydate, console_org_name, partneragency, partneradvertiser, org_sales_owner
,round(sum(gross_revenue_allocation)::numeric,2) as gross_revenue
,round(avg(sum(gross_revenue_allocation)) over (partition by org_sales_owner order by activitydate RANGE INTERVAL '5' MONTH PRECEDING)::numeric,2) as salesowner6monthavg
from data_provider_payout dpp
where activitydate >= '01/01/2019'
group by activitydate, console_org_name, partneragency, partneradvertiser, org_sales_owner
If I understand correctly, you need to aggregate by the month and the owner. That would be something like this:
select date_trunc('month', activitydate), org_sales_owner,
round(sum(gross_revenue_allocation)::numeric, 2) as gross_revenue,
round(avg(sum(gross_revenue_allocation)) over (
partition by org_sales_owner
order by min(activitydate)
range between interval '5 month' preceding and current_row
)
)::numeric, 2) as salesowner6monthavg
from data_provider_payout dpp
where activitydate >= '2019-01-01'
group by date_trunc('month', activitydate), org_sales_owner
Here is the snip of my database I want to calculate average energy consumption for the last three days in the exact hour. So if I have consumption at 24.10.2016. 10h, I want to add column with average consumption for the last three days at the same hour, so for 23.10.2016. 10h, 22.10.2016. 10h and 21.10.2016. 10h. My records are measured every hour, so in order to calculate this average I have to look at every 24th row and haven't found any way. How can I modify my query to get what I want:
select avg(consumption) over (order by entry_date rows between 72
preceding and 24 preceding) from my_data;
Or is there some other way?
Maybe try this one:
select entry_date, EXTRACT(HOUR FROM entry_date),
avg(consumption) over (PARTITION BY EXTRACT(HOUR FROM entry_date)
order by entry_date rows between 72 preceding and 24 preceding)
from my_data;
and you may use RANGE BETWEEN INTERVAL '72' HOUR PRECEDING AND INTERVAL '24' HOUR PRECEDING instead of ROWS. This covers situation when you have gaps or duplicate time values.
I think you can do this another way by using filters.
Select avg(consumption) from my_data
where
entry_date between #StartDate and #EndDate
and datepart(HOUR, entry_date)=#hour
If you're on MySQL
Select avg(consumption) from my_data
where
entry_date between #StartDate and #EndDate
and HOUR(entry_date)=#hour
I am trying to calculate the max of a value over a relative date range. Suppose I have these columns: Date, Week, Category, Value. Note: The Week column is the Monday of the week of the corresponding Date.
I want to produce a table which gives the MAX value within the last two weeks for each Date, Week, Category combination so that the output produces the following: Date, Week, Category, Value, 2WeeksPriorMAX.
How would I go about writing that query? I don't think the following would work:
SELECT Date, Week, Value,
MAX(Value) OVER (PARTITION BY Category
ORDER BY Week
ROWS BETWEEN 2 PRECEDING AND CURRENT ROW) as 2WeeksPriorMAX
The above query doesn't account for cases where there are missing values for a given Category, Week combination within the last 2 weeks, and therefore it would span further than 2 weeks when it analyzes the 2 preceding rows.
Left joining or using a lateral join/subquery might be expensive. You can do this with window functions, but you need to have a bit more logic:
select t.*,
(case when lag(date, 1) over (partition by category order by date) < date - interval '2 week'
then value
when lag(date, 2) over (partition by category order by date) < date - interval '2 week'
then max(value) over (partition by category order by date rows between 1 preceding and current row)
else max(value) over (partition by category order by date rows between 2 preceding and current row)
end) as TwoWeekMax
from t;