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Hi All;
Newbie here and of course on a tight schedule. Been working this issue for 30 hours alreday, and my brian is now too twisted to figure this out. Hope there is help out there.
I first tried to work with a bell curve - have the curve, but don't know how to plot my data on it so I switched to working on a Histogarm - But I only have 1/2 my data (all the positive ratios, none of the negative ratios).
The histogram should assume the shape of the bell curve.
My ratios range from -2000 to positive 400
Bins should be...open to suggestions, but right now I'm using -2000 to -37, -36.99 to -25, -24.99 to -13, -12.99 to -0.01, 0-12.99, 13 to 24.99, 25 to 36.99, 37 to 2000
here's my Catagory table:
Category | LL | UL |
Neg 37 -2000 | -37.00% | -2000.00% |
Neg 25 -36 | -25.00% | -36.99% |
Neg 13 -24 | -13.00% | -24.99% |
Neg 0 -12 | 0.00% | -12.99% |
Pos 0-12 | 0.00% | 12.99% |
Pos 13-24 | 13.00% | 24.99% |
Pos 25-36 | 25.00% | 36.99% |
Pos 37-2000 | 37.00% | 2000.00%
|
And here's my column:
ROE | RankCategory |
-41.02% | |
-30.87% | |
-27.33% | |
-26.75% | |
-25.87% | |
-22.26% | |
-9.87% | |
-6.89% | |
-5.51% | |
-2.41% | |
-1.65% | |
0.11% | Pos 0-12 |
0.32% | Pos 0-12 |
4.82% | Pos 0-12 |
5.47% | Pos 0-12 |
7.00% | Pos 0-12 |
8.37% | Pos 0-12 |
9.52% | Pos 0-12 |
10.56% | Pos 0-12 |
12.34% | Pos 0-12 |
15.40% | Pos 13-24 |
15.90% | Pos 13-24 |
17.09% | Pos 13-24 |
25.98% | Pos 25-36 |
26.38% | Pos 25-36 |
26.41% | Pos 25-36 |
26.59% | Pos 25-36 |
40.81% | Pos 37-2000 |
Solved! Go to Solution.
Hi @Anonymous ,
RankCategory = VAR CatVar = [ROE] RETURN IF ( CatVar > 0, CALCULATE ( VALUES ( 'benchmark'[Category] ), CatVar > 'benchmark'[LL], CatVar <= 'benchmark'[UL] ), CALCULATE ( VALUES ( 'benchmark'[Category] ), CatVar <= 'benchmark'[LL], CatVar > 'benchmark'[UL] ) )
Best regards,
Yuliana Gu
Hi @Anonymous ,
RankCategory = VAR CatVar = [ROE] RETURN IF ( CatVar > 0, CALCULATE ( VALUES ( 'benchmark'[Category] ), CatVar > 'benchmark'[LL], CatVar <= 'benchmark'[UL] ), CALCULATE ( VALUES ( 'benchmark'[Category] ), CatVar <= 'benchmark'[LL], CatVar > 'benchmark'[UL] ) )
Best regards,
Yuliana Gu
You're nearly there with your classification function. However, the reason it's only working for half the data is that you switch the way values are categorised in the category table. +ve number categories are mirrored by -ve number categories when they should be treated just the same. UL (upper Level) of the -ve numbers is actually the lower level. Example -25% is a LL and -36.99% is an UL (They should be switched. Maybe the best way to think about this is to draw a number line)
To summarise, swap your UL and LL values for all negative numbers in the category table,
Thank you so much!! I had a feeling I was close, but just couldn't figure it out. Thanks again.
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