Fixing chart scaling.

[Anonymous]

I am currently trying to fix the automatic scalling of a chart if 'forced 0' is deactivated. I am using a 'line chart' more speciffic the stacked line chart (image).

If I deactivate 'forced 0' the effect is like I want it. Thing is it zooms in so much that some data is not shown anymore.

I believe I need to fix this by adding a dynamic 'Static min' value.

I need to get the minimal value of the first Dimension of the largest, combined by first dimension, second  dimension (Yeah I know, but I have no idea how to describe my problem in a better way)

With  'forced 0':

Deactivated 'forced 0':

And thats what it's supossed to look:

Long story short, I am not able to write a sufficient line of code to get the min value of any given date from the largest  in 2nd dimension.

[marcus_sommer]

In the top right area of the tab axis you could define the min/max/interval values of your scale whereby min/max is usually something like:

min(TOTAL value)

     or maybe

min(aggr(sum(value), Dim))

The interval might be set manually if the span between min/max could be estimated and didn't change much by different selections. If not you need to set something like this: round((max - min) / NoOfInterval).

Beside this removing the time-part from the dimension and/or using a different and shorter formatting of the dimension-values will increase the space for the lines and with this the readability of the information.

- Marcus

[Anonymous]

Yeah I'm aware of the static min max values. What I need is a dynamic min scalling so that all groups(2nd Dim) will be shown. I sorted those by size, the largest is at the bottom going all the way up to the smallest. I'm not however able to generate a function that gives me the min value of the largest group.

Setting those value static will not work as there are huge differences(10^5).

PS: The testdata has no time. However the real data will.

[Anonymous]

I tried MIN(AGGR(MAX(value), time_dim)).  This however results in the wrong result

[Anonymous]

Thanks for your help. The culprit of my problem was one value in my test data which resulted in seemingly wrong results. Your solution is correct "MIN(AGGR(MAX(value), time_dim))". Sorry for the inconvinience.