Forum Discussion
% Changes Using 4 4 5 week Calendar Month
BryanWhellams wrote:
Hi there
I need to be able to calculate the % Changes in a number of measures using the 4 4 5 Calendar Month.
I have two tables as follows:
One called AppointmentData which includes Appointment Dates and Appointments (either a 1 or a 0).
Another called YMW Date that includes the Week Number, Quarter Number, Month Number and Month Name for the 4 4 5 week calendar month, ie. 2nd Jan 2017 is week 1701, 9th Jan is week 1702 and so on, 2nd to 29th Jan is Month 1, 30th Jan is Month 2 and so on in 4 4 5 week month patterns.
I need to be able to get % Changes for Week on Week, Month on Month and Quarter on Quarter using the dates in the 4 4 5 week calendar month.
I'm finding this really challenging so any help greatly appreciated.
Thanks
Bryan
Since you've already have that 4-4-5 calendar, you can create individual index column for Week, Month and Quarter. eg, for Week
WeekIndex = RANKX('calendar','calendar'[Week Number],,ASC,Dense)
Then create measures as below.
current Week Appnmts = SUM(AppointmentData[Appointments])
previous Week Appnmts =
SUMX (
FILTER (
ALLSELECTED ( AppointmentData ),
Calendar[WeekIndex]
= MAX ( Calendar[WeekIndex] ) - 1
),
AppointmentData[Appointments]
)
% change = DIVEDE([current Week Appnmts]-[previous Week Appnmts],[previous Week Appnmts])
Then put the column [Week Number](1702,1703 etc) as a X-Axis and the [% change] as value field.
Thanks for this
The data table is called DSS Data Cleaned, the dates table is called YMWDate.
I have already got columns in the Dates table for Week No, Date of First Day Of Week, etc.
I have created a measure for Appointments Current Week as follows:
Appointments Current Week = SUM('DSS Data Cleaned'[Appointment])
I have also created a measure for Appointments Previous Week as follows:
Appointment Previous Week = SUMX (
FILTER (
ALLSELECTED ('DSS Data Cleaned'),
'DSS Data Cleaned'[WeekNo]
= MAX ('DSS Data Cleaned'[WeekNo]) - 1
),
SUM('DSS Data Cleaned'[Appointment])
)
but it is returning figures which are way too high.
Could you tell me where I might be going wrong please?
Thanks