I created a query in Microsoft Access such as the one below:
SELECT LoanType
,Avg(Loan Amount)
,Avg(Loan Rate)
FROM Table1
GROUP BY LoanType
The output is as you would expect, the average loan amount and the average loan rate for each loan type.
However, I'd like for my Access Report to calculate the average of all the loans, regardless of loan type, and place this row at the very bottom. Using the Report view in Access, you can add a "Totals" row where you can write a formula such as COUNT(), SUM(), AVG(). But as you know, calculating an average of an average goes against basic math.
I'm assuming I have to create this "Totals" row at the SQL/Query level. But I can't seem to figure it out. Any input would be greatly appreciated!
You can use UNION ALL to add a row with a similar query, just without the GROUP BY and a NULL for LoanType (or any other value you like as long as it's implicitly castable to the data type of LoanType).
SELECT LoanType,
Avg(Loan Amount)
Avg(Loan Rate)
FROM Table1
GROUP BY LoanType
UNION ALL
SELECT NULL,
Avg(Loan Amount)
Avg(Loan Rate)
FROM Table1;
Of yourse you can do exactly what you described: Build a query that calculates the averages by LoanType, build a report on this query and calculate an average in the report footer. Unfortunately, this "total average" will be an average of averages, but I guess you want an average over all records. To achieve this:
Base your report on Table1.
Create a group to group by LoanType.
Calculate the averages by LoanType in the group footer.
If you don't want to see the details, set the details section to be invisible.
Calculate the "total averages" in the report footer.
Related
I have a table where each row is a vendor with a sale made on some date.
I'm trying to compute average daily sales per vendor for the year 2019, and get a single number. Which I think means I want to compute an average of averages.
This is the query I'm considering, but it takes a very long time on this large table. Is there a smarter way to compute this average without this much nesting? I have a feeling I'm scanning rows more times than I need to.
-- Average of all vendor's average daily sale counts
SELECT AVG(vendor_avgs.avg_daily_sales) avg_of_avgs
FROM (
-- Get average number of daily sales for each vendor
SELECT vendor_daily_totals.memberdeviceid, AVG(vendor_daily_totals.cnt)
avg_daily_sales
FROM (
-- Get total number of sales for each vendor
SELECT vendorid, COUNT(*) cnt
FROM vendor_sales
WHERE year = 2019
GROUP BY vendorid, month, day
) vendor_daily_totals
GROUP BY vendor_daily_totals.vendorid
) vendor_avgs;
I'm curious if there is in general a way to compute an average of averages more efficiently.
This is running in Impala, by the way.
I think you can just do the calculation in one shot:
SELECT AVG(t.avgs)
FROM (
SELECT vendorid,
COUNT(*) * 1.0 / COUNT(DISTINCT month, day) as avgs
FROM vendor_sales
WHERE year = 2019
GROUP BY vendorid
) t
This gets the total and divides by the number of days. However, COUNT(DISTINCT) might be even slower than nested GROUP BYs in Impala, so you need to test this.
I have a query that I am currently using to find counts
select Name, Count(Distinct(ID)), Status, Team, Date from list
In addition to the counts, I need to calculate a goal based on weighted average of counts per status and team, for each day.
For example, if Name 1 counts are divided into 50% Status1-Team1(X) and 50% Status2-Team2(Y) yesterday, then today's goal for Name1 needs to be (X+Y)/2.
The table would look like this, with the 'Goal' field needed as the output:
What is the best way to do this in the same query?
I'm almost guessing here since you did not provide more details but maybe you want to do this:
SELECT name,status,team,data,(select sum(data)/(select count(*) from list where name = q.name)) FROM (SELECT Name, Count(Distinct(ID)) as data, Status, Team, Date FROM list) as q
I have a pivot table with multiple rows dimensions (District, Region, Shop) and months in columns. I need to calculate sales Growth ((sales this month - sales previous month)/sales previous month). As You can see from formula, i need a value from previous month (previous column). I have a formula for testing:
Sum(Total {<District={'District1'}, [Month]={'2015 09'}>} Quantity)
With this formula i am able to get the value from previous column (lets say i am calculating growth in month 2015 10 and District1). The problem is, that i get a wrong value, when this formula is used in a row with different District.
Is there any way to get district value of current row and use it in a formula? I tried multiple variations like:
Sum(Total {<District={$(District)}, [Month]={'2015 09'}>} Quantity)
Sum(Total {<District={$<=District>}, [Month]={'2015 09'}>} Quantity)
but none of them work
There is no need to add District in the calculation. QV will aggregate to it automatically since District is dimension already.
If you want to aggregate all rows under each District to show the total quantity for the whole District then you can use the following expression:
sum( total <District> Quantity )
The picture below demonstrate the result:
Also you can check the QV help (c:\Program Files\QlikView\English.chm) for the Aggr() function as well. With Aggr() function the same result can be achieved with:
aggr( NoDistinct sum( Quantity ), District )
I am looking for a solution to convert the individual monthly averages to monthly averages from the beginning of the year. In other words from January to said month.
I used the cross tab wizard to group the rating of an employee into months in the column header. Employees are in the row header. The values of the ratings is then averaged.
My issue is this just shows the average rating of an employee for each month. I need a solution that would show me the average of each month if it included all results from the begging of the year (i.e. February would include January's and February's ratings).
TRANSFORM Avg(CSS_Table.[Emp_Rating]) AS AvgOfEmp_Rating
SELECT CSS_Table.[Emp]
FROM Rating_Table
GROUP BY Rating_Table.[Emp]
PIVOT Format([Survey_Date],"mmm") In ("Jan","Feb","Mar","Apr","May","Jun","Jul","Aug","Sep","Oct","Nov","Dec");
One possible strategy to attack this
Create one query for each month that calculates the monthly YTD Average.
Create a Union query that joins them all together (i.e. make sure to use the same column names for each query).
Feed the union query into the Pivot.
I am in a situation where I need to calculate Percentage for every fiscal year depending on distinct count of the rows.
I have achieved the distinct count (fairly simple task) for each year city-wise and reached till these 2 listings in cube.
The first listing is state wide distinct count for given year.
Second listing is city wise distinct count for given year with percentage based on state-wide count for that year for that city.
My problem is that I need to prepare a calculated member for the percentage column for each given year.
For eg, In year 2009, City 1 has distinct count of 2697 and percentage raise of 32.94%. (Formula used= 2697/8187 ).
I tried with ([Measures].[Distinct Count])/(SUM(ROOT(),[Measures].[Distinct Count])) but no luck.
Any help is highly appreciated.
Thanks in advance.
PS: City wide sum of year 2009 can never be equal to statewide distinct count of that year. This is because we are calculating the distinct count for city and state both.
You need to create a Region Hierarchy for this, like State -> City. The create a calculation like below. Then in the browser put your Hierarchy on the left and the sales and calculated percentage in values.
([Dim].[Region].CurrentMember, [Measures].[Salesamt]) /
iif(
([Dim].[Region].CurrentMember.Parent, [Measures].[Salesamt]) = 0,
([Dim].[Region].CurrentMember, [Measures].[Salesamt]),
([Dim].[Region].CurrentMember.Parent, [Measures].[Salesamt])
)