So i am trying to display the previous 52 Weeks from Todays Date at anytime on a Column Chart. I managed to achieve the ability to return the last 52 weeks using the following DAX:
52Weeks = IF(AND(TML_CUBE_01[Dim Date.Date] >= TODAY()-364,TML_CUBE_01[Dim Date.Date]<=TODAY()),1,0)
However, from the below, you can see that i am experiencing the issue of not being able to display all the bars (52 Weeks) in the Column Chart, without having a scroll bar display.
On the X-Axis i have the Fiscal Week selected, which is a string. I am looking for the option to select Categorical vs Continious however this does not display, which i am sure is due to the Data Type of Fiscal Week not being either a Date or Numeric.
However, when i remove Fiscal Week from the X-Axis and add the Date, I get the expected outcome. The entire columns are displayed without the need to scroll, therefore no Scroll Bar displays. Here i do have the option to select Type: Continous vs Categorical.
So far i have tried adding the Fiscal Week and Date into a single Column Chart and drill down, but this returns the Scrioll Bar.
Any help would be much appreciated.
Thanks for the reply @philipplenz, however i undertand that making more space for the visual would show all the columns without the scroll bar, but that defeats the purpose of what i am trying to achieve. Also, if i filter down the values (which i assume you mean on the x-axis), this will display the incorrect data, as i am trying to return the previous 52 Fiscal Week from todays date.
The result i am looking for is doable in Excel, hence i know a solution must exist in Power BI. When i add Fiscal Week to the X-Axis, it now displays everyhting without a Scroll Bar after changing it from Data Type: String to Numerical. However, as you can see from the below image, as i have selected Continous, it now introduced a new challenge of filling in the gaps between Fiscal Week 1852 and 1901, when in fact it should.
Hope this explains it more. In fact, i will update my intial post with more detail in order to explain it all better
However, as you can see now,