Calculating Growth in crosstab Cognos. I need to bring the previous year's value to the current year column. Please help me.
-322,129,132.49 should be coming the PY1 column in the Year of 2018.
Missing information:
version of Cognos
sample data
column names
What should PY1 be for 2017?
...but I'll try.
I think what you are saying is that the 2017 PY1 should be 0 and 2018 PY1 should be -322,129,132.49. If that is correct...
Adjust your query to return PY1 in the correct year. This may involve multiple queries joined together. Here is sample SQL to consider:
select a.[year]
, a.unnamed_code_value
, coalesce(b.PY1, 0) as PY1
, a.en_Amount
from (
select [year]
, unnamed_code_value
, sum(en_Amount) as en_Amount
from table1
group by [year]
, unnamed_code_value
) a
left outer join (
select [year] + 1 as 'year'
, unnamed_code_value
, sum(en_Amount) as PY1
from table1
group by [year] + 1
, unnamed_code_value
) b on b.[year] = a.[year]
and b.unnamed_code_value = a.unnamed_code_value
Related
Excel
I'm creating a pivot table and need a column to describe 'average number of orders' made by customers each year.
I have:
Order date
Customer ID
Year
I'm thinking calculated feild, and using COUNT(Order date) to determine number of orders. But I need to be able to use that to get the average number of orders for each customer.
Any help would be appreciated.
Date set example:
Customer ID Order date
Xh015046 12/04/2016
X7615777 03/06/2016
X10062024 20/04/2017
X7615777 25/06/2016
X7615777 05/01/2017
Xh015046 15/04/2017
X10062024 09/07/2018
X7615777 10/07/2018
Xh015046 11/07/2018
X10062024 12/07/2018
Pivot table I want:
Year Average Number of orders per customer
2016 1.5
2017 1
2018 1.333333333
Within the Data Model (Power Pivot), create a new measure:
AverageOrders :=
VAR MyTable =
SUMMARIZE (
Table1,
[Customer ID],
"Order Count", CALCULATE ( COUNTROWS ( Table1 ) )
)
RETURN
AVERAGEX ( MyTable, [Order Count] )
Amend the table (Table1) and column (Customer ID) names in the above as required.
Then create a Pivot Table within the worksheet with Year in the Rows section and the above measure AverageOrders in the Values section.
I am working on a matrix in Power BI and I am not figuring out how to sum each column recursively until the total:
And this should be the resulting matrix (as an example, rows):
Some clarifications:
The months (columns) are dynamically generated based on the transaction month. I could filter the data to get the same data for only three months.
"Nombre proveedor" stands for "Vendor name".
I don't care about "Total" row.
These are my values:
So, I think I should create a measure with DAX to replace "Accounting Balance" to sum the previous column (month) or show nothing (to avoid zeroes).
Searching on internet I found several sites to get the running totals by rows, but not by columns.
Any suggestions?
Try Something like this:
Maesure =
CALCULATE (
[Accounting Balance],
FILTER (
ALL ( 'table' ),
'table'[Transaction month] <= MAX ( 'table'[Transaction month] )
)
)
My question is that I'd like to calculate a daily average taking into account days with zeroes.
Let me clarify it:
I'd like to calculate the average daily value of units for each category, with the following table:
When I sum up the values for each day and category, I get:
I'd like to include in the average calculation the zeroes.
I use the following code:
SUMMARIZE(
Data,
Data[Category],
"Average",
AVERAGEX(
SUMMARIZE(
Data,
Data[Date],
"Sum of Units",
SUM(Data[Units])
),
[Sum of Units]
)
)
But the problem is that for category B it doesn't take into account those days with 0s.
Could you please guide me how to solve it?
Thanks in advance!
Jorge
One way to solve it would be to create a calendar table, which can then be used to count the number of days in any of your grouping periods. This also means you can use non standard calendars, for example something like a 4-4-5
With a calendar table created you can leverage the FIRSTDATE and LASTDATE functions in DAX.
I recommend adding a past dates column to the calendar table, which can be created using DAX with the following formula. The today function in DAX when used in a calculated column will only evaluate when the model is updated.
In my example I created a calculated column in the date table called Past_Dates
Past_dates =IF( TODAY() > [Date], TRUE(), BLANK())
So for example if I create the following measures, the Today one just being used for illustration.
Start_date:=FIRSTDATE( Dates[Date] )
End_Date:=LASTDATE( Dates[Date])
Today:=TODAY()
EndPhased:=CALCULATE( LASTDATE( Dates[Date] ), Dates[Past_dates] = TRUE())
Which when added to an empty pivot table evaluate to the following.
Note that you would want to have year somewhere in the pivot if you have multiple years of data.
The idea of having the Past flag is to keep from counting days where they would not be any data due to being in the future. So for example in September it would only use 11 days of sales and not the full 30.
As the below example shows, the finding of the start and end date even work on a Quarter basis.
So now that we have a way to get the Start and End date of a period, the next step is adding it into our Calculated measure.
In the below example, we are iterating though every unique Category name. Within the category, we are summing the units sold, and then dividing by the number of days between EndPhased and Start_Date + 1. Then averaging the results by the number of categories that have data in that period.
Average:=AVERAGEX (
VALUES ( Data[Category] ),
CALCULATE ( DIVIDE ( SUM ( Data[Units] ), [EndPhased] - [Start_date] + 1 ) )
)
It seems to me that you need to have an underlying row with the zero value in it (in your initial Data table). Right now, you don't actually have a zero value for B on 02/01/2017. If you add a row with the values | 02/01/2017 | B | 0 | I believe you will see that the average accounts for it. As things stand for you right now, I believe the pivot table actually reflects no value (blank) rather than zero value, so the zero isn't currently counted for the average.
I think the best way is to add the missing zeroes, using UNION function:
SUMMARIZE(
Data,
Data[Category],
"Average",
AVERAGEX(
UNION(
SUMMARIZE(
Data,
Data[Date],
"Sum of Units",
SUM(Data[Units])
),
ADDCOLUMNS(
EXCEPT(
ALL(Data[Date]),
VALUES(Data[Date])
),
"Sum of Units",
0
)
),
[Sum of Units]
)
)
I'm trying to retrieve rows from a table where a subquery matches an variable. However, it seems as if the WHERE clause only lets me compare fields of the selected tables against a constant, variable or subquery.
I would expect to write something like this:
DATA(lv_expected_lines) = 5.
SELECT partner contract_account
INTO TABLE lt_bp_ca
FROM table1 AS tab1
WHERE lv_expected_lines = (
SELECT COUNT(*)
FROM table2
WHERE partner = tab1~partner
AND contract_account = tab1~contract_account ).
But obviously this select treats my local variable as a field name and it gives me the error "Unknown column name "lv_expected_lines" until runtime, you cannot specify a field list."
But in standard SQL this is perfectly possible:
SELECT PARTNER, CONTRACT_ACCOUNT
FROM TABLE1 AS TAB1
WHERE 5 = (
SELECT COUNT(*)
FROM TABLE2
WHERE PARTNER = TAB1.PARTNER
AND CONTRACT_ACCOUNT = TAB1.CONTRACT_ACCOUNT );
So how can I replicate this logic in RSQL / Open SQL?
If there's no way I'll probably just write native SQL and be done with it.
The program below might lead you to an Open SQL solution. It uses the SAP demo tables to determines the plane types that are used on a specific number of flights.
REPORT zgertest_sub_query.
DATA: lt_planetypes TYPE STANDARD TABLE OF s_planetpp.
PARAMETERS: p_numf TYPE i DEFAULT 62.
START-OF-SELECTION.
SELECT planetype
INTO TABLE lt_planetypes
FROM sflight
GROUP BY planetype
HAVING COUNT( * ) EQ p_numf.
LOOP AT lt_planetypes INTO DATA(planetype).
WRITE: / planetype.
ENDLOOP.
It only works if you don't need to read fields from TAB1. If you do you will have to gather these with other selects while looping at your results.
For those dudes who found this question in 2020 I report that this construction is supported since ABAP 7.50. No workarounds are needed:
SELECT kunnr, vkorg
FROM vbak AS v
WHERE 5 = ( SELECT COUNT(*)
FROM vbap
WHERE kunnr = v~kunnr
AND vkorg = v~vkorg )
INTO TABLE #DATA(customers).
This select all customers who made 5 sales orders within some sales organization.
In ABAP there is no way to do the query as in NATIVE SQL.
I would advice not to use NATIVE SQL, instead give a try to SELECT/ENDSELECT statement.
DATA: ls_table1 type table1,
lt_table1 type table of table1,
lv_count type i.
SELECT PARTNER, CONTRACT_ACCOUNT
INTO ls_table1
FROM TABLE1.
SELECT COUNT(*)
INTO lv_count
FROM TABLE2
WHERE PARTNER = TAB1.PARTNER
AND CONTRACT_ACCOUNT = TAB1.CONTRACT_ACCOUNT.
CHECK lv_count EQ 5.
APPEND ls_table1 TO lt_table1.
ENDSELECT
Here you append to ls_table1 only those rows where count is equals to 5 in selection of table2.
Hope it helps.
SELECT BabyInformation.* , t1.*
FROM BabyInformation
LEFT JOIN
(SELECT * FROM BabyData
GROUP BY BabyID
ORDER By Date DESC ) AS t1 ON BabyInformation.BabyID=t1.BabyID
This is my query. I want to get the one most recent BabyData tuple based on date.
The BabyInformation should left join with babyData but one row per baby...
I tried TOP(1) but this worked only for the first baby
Here is one way to do it, there are other ways which can be faster, but I believe this one to be the clearest for a beginner.
SELECT BabyInformation.*, BabyData.*
FROM BabyInformation
JOIN
(SELECT BabyID, Max(Date) as maxDate FROM BabyData
GROUP BY BabyID
) AS t1
ON BabyInformation.BabyID=t1.BabyID
Join BabyData ON BabyData.BabyID = t1.BabyID and BabyData.Date = t1.maxDate
This should do it:
SELECT bi.* , bd.*
FROM BabyInformation [bi]
LEFT JOIN BabyData [bd]
on bd.BabyDataId = (select top 1 sub.BabyDataId from BabyData [sub] where sub.BabyId = bi.BabyId order by sub.Date desc)
I've assumed that there is a column called 'BabyDataId' in the BabyData table.