Tableau: Display Different Number Formats for the Same Measure - formatting
I have a field in my dashboard called outcome that displays the performance results for a doctor's office for multiple measures. A majority of the outcome values are rates and should be displayed as percentages. Unfortunately, there are two outcomes, "Utilization Management: Measure 3" and "Utilization Management: Measure 5" that are NOT rates, but actually number values.
Is there a way to display the outcome field in my table so that all 'Measures' that are NOT "Utilization Management: Measure 3" or "Utilization Management: Measure 5" get displayed as percentages, while the two aforementioned measures are displayed as number values?
Please do not get hung up on the appropriateness of combining rate and number values in the same field, as I've tried to have that conversation with my customer...they are insistent on this display ability and will not let it through UAT without it. Thanks.
Same question posed and packaged workbook attached for reference here.
One approach is to define a string valued calculated field that makes the number format part of the calculation logic. This solution does not play well with Measure Names and Measure Values, since you can't put string valued measures on the Measure Values shelf. But you can still build the view your customer wants, with a little effort.
First create a static set based on your field [Measure] (confusing choice of field name, by the way. You have a dimension named Measure.). Call it [Percentage Measures] and check off the ones you want displayed as percentages.
Then for each of your numeric measure fields that you want treated this way, make a corresponding calculated field that looks something like:
if attr([Percentage Measures]) then
str(round(sum([outcome]) * 100, 2)) + "%"
else
str(round(sum([outcome]),3))
end
This approach assumes you will use your calculation on views where your dimension named [Measure] is on some (non-filter) shelf. Adjust the round() function arguments as desired
I took a look at your workbook. It seems that it is not possible to dynamically format values. There is a feature idea here: https://community.tableau.com/ideas/1411 which I believe would allow you to do what you want.
Related
TABLEAU Totals not matching what's in view
I've been dealing with this issue in various ways throughout my time with this dataset in Tableau. As you can see, the Total count of properties for each city is including properties that have been successfully filtered out of view. Why? The dyn.RANKED Profitable Investments (grouped) variable on the Filter shelf is an attempt to double down on the same as the first line of the Calculated Field - to ignore the unwanted properties in each city. The view ignores them, but the totals do not. If the Watershed Property pill is removed from the Rows shelf, then the dyn.NumProps_in_City results shown on the table are each the same as the Totals you see here (i.e., despite the first line of the calculated field, properties that do not meet that opening condition are being counted)...despite the view with the Watershed pill knowing not to show them. Also if the Watershed Property pill is removed from the Rows shelf, then the dyn.RANKED Profitable Investments (grouped) variable on the Filter shelf suddenly only has one category to choose from (i.e., 'INVEST') if you go to edit the filter. Which would be great since that's the category I care about, but not if the counts are including things that are not in that category despite the filter. Messing around with Include, Exclude, and Fixed in the calculated field doesn't seem to work here since I can't figure out how to get around various aggregate/non-aggregate and/or ATTR errors no matter where I place them. Plus, my incorrect counts are not suffering from an LOD issue - the LOD is correct - it's an issue of not consistently filtering out the unwanted rows at the desired LOD. Please advise! Thanks, Christian
It seems that dyn.Ranked calculated field calculates the value prior to filtering. This may happen if you have used any LOD calculations in the syntax. Simply right click such fields on filters shelf and click add to context. This will cause LOD calculations to calculate after the filtering. see this link, the context filters are above the LOD calculations, in order of precedence; but measure filters are below the LOD calcs. Therefore if measures are used as filters, these have to be added to context so that their order of precedence is above such calculations
How to populate all possible combination of values in columns, using Spark/normal SQL
I have a scenario, where my original dataset looks like below Data: Country,Commodity,Year,Type,Amount US,Vegetable,2010,Harvested,2.44 US,Vegetable,2010,Yield,15.8 US,Vegetable,2010,Production,6.48 US,Vegetable,2011,Harvested,6 US,Vegetable,2011,Yield,18 US,Vegetable,2011,Production,3 Argentina,Vegetable,2010,Harvested,15.2 Argentina,Vegetable,2010,Yield,40.5 Argentina,Vegetable,2010,Production,2.66 Argentina,Vegetable,2011,Harvested,15.2 Argentina,Vegetable,2011,Yield,40.5 Argentina,Vegetable,2011,Production,2.66 Bhutan,Vegetable,2010,Harvested,7 Bhutan,Vegetable,2010,Yield,35 Bhutan,Vegetable,2010,Production,5 Bhutan,Vegetable,2011,Harvested,2 Bhutan,Vegetable,2011,Yield,6 Bhutan,Vegetable,2011,Production,3 Image of the above csv: Now there is a very small country lookup table which has all possible countries the source data can come with, listed. PFB: I want to have the output data's number of columns always fixed (this is to ensure the reporting/visualization tool doesn't get dynamic number columns with every day's new source data ingestions depending on the varying distinct number of countries present). So, I've to somehow join the source data with the country_lookup csv and populate all those columns with default value as F. Every country column would be binary with T or F being the possible values. The original dataset from the above has to be converted into below: Data (I've kept the Amount field unsolved for column Type having Derived Yield as is, rather than calculating them below for a better understanding and for you to match with the formulae): Country,Commodity,Year,Type,Amount,US,Argentina,Bhutan,India,Nepal,Bangladesh US,Vegetable,2010,Harvested,2.44,T,F,F,F,F,F US,Vegetable,2010,Yield,15.8,T,F,F,F,F,F US,Vegetable,2010,Production,6.48,T,F,F,F,F,F US,Vegetable,2010,Derived Yield,(2.44+15.2)/(6.48+2.66),T,T,F,F,F,F US,Vegetable,2010,Derived Yield,(2.44+7)/(6.48+5),T,F,T,F,F,F US,Vegetable,2010,Derived Yield,(2.44+15.2+7)/(6.48+2.66+5),T,T,T,F,F,F US,Vegetable,2011,Harvested,6,T,F,F,F,F,F US,Vegetable,2011,Yield,18,T,F,F,F,F,F US,Vegetable,2011,Production,3,T,F,F,F,F,F US,Vegetable,2011,Derived Yield,(6+10)/(3+9),T,T,F,F,F,F US,Vegetable,2011,Derived Yield,(6+2)/(3+3),T,F,T,F,F,F US,Vegetable,2011,Derived Yield,(6+10+2)/(3+9+3),T,T,T,F,F,F Argentina,Vegetable,2010,Harvested,15.2,F,T,F,F,F,F Argentina,Vegetable,2010,Yield,40.5,F,T,F,F,F,F Argentina,Vegetable,2010,Production,2.66,F,T,F,F,F,F Argentina,Vegetable,2010,Derived Yield,(2.44+15.2)/(6.48+2.66),T,T,F,F,F,F Argentina,Vegetable,2010,Derived Yield,(15.2+7)/(2.66+5),F,T,T,F,F,F Argentina,Vegetable,2010,Derived Yield,(2.44+15.2+7)/(6.48+2.66+5),T,T,T,F,F,F Argentina,Vegetable,2011,Harvested,10,F,T,F,F,F,F Argentina,Vegetable,2011,Yield,90,F,T,F,F,F,F Argentina,Vegetable,2011,Production,9,F,T,F,F,F,F Argentina,Vegetable,2011,Derived Yield,(6+10)/(3+9),T,T,F,F,F,F Argentina,Vegetable,2011,Derived Yield,(10+2)/(9+3),F,T,T,F,F,F Argentina,Vegetable,2011,Derived Yield,(6+10+2)/(3+9+3),T,T,T,F,F,F Bhutan,Vegetable,2010,Harvested,7,F,F,T,F,F,F Bhutan,Vegetable,2010,Yield,35,F,F,T,F,F,F Bhutan,Vegetable,2010,Production,5,F,F,T,F,F,F Bhutan,Vegetable,2010,Derived Yield,(2.44+7)/(6.48+5),T,F,T,F,F,F Bhutan,Vegetable,2010,Derived Yield,(15.2+7)/(2.66+5),F,T,T,F,F,F Bhutan,Vegetable,2010,Derived Yield,(2.44+15.2+7)/(6.48+2.66+5),T,T,T,F,F,F Bhutan,Vegetable,2011,Harvested,2,F,F,T,F,F,F Bhutan,Vegetable,2011,Yield,6,F,F,T,F,F,F Bhutan,Vegetable,2011,Production,3,F,F,T,F,F,F Bhutan,Vegetable,2011,Derived Yield,(2.44+7)/(6.48+5),T,F,T,F,F,F Bhutan,Vegetable,2011,Derived Yield,(10+2)/(9+3),F,T,T,F,F,F Bhutan,Vegetable,2011,Derived Yield,(6+10+2)/(3+9+3),T,T,T,F,F,F The image of the above expected output data for a structured look at it: Part 1 - Part 2 - Formulae for populating Amount Field for Derived Type: Derived Amount = Sum of Harvested of all countries with T (True) grouped by Year and Commodity columns divided by Sum of Production of all countries with T (True)grouped by Year and Commodity columns. So, the target is to have a combination of all the countries from source and calculate the sum of respective Harvested and Production values which then has to be divided. The commodity can be more than one in the actual scenario for any given country, but that should not bother as the summation of amount happens on grouped commodity and year. Note: The users in the frontend can select any combination of countries. The sole purpose of doing it in the backend rather than dynamically doing it in the frontend is because AWS QuickSight (our visualisation tool), even though can populate sum on selected column filters but doesn't yet support calculation on those derived summed fields. Hence, the entire calculation of all combination of countries has to be pre-populated (very naive approach) in order to make it available in report on dynamic users selection of countries. Also if you've any better approach (than the above naive approach mentioned in note) to solve this problem, you are most welcome to guide me. I've also posted a question on the same problem without writing my expected approach for experts to show me the path on how we can solve this kind of a problem better than this naive approach. If you want to help solve it with some other technique, you're most welcome, here is the link to that question. Any help shall be greatly acknowledged.
SSAS OLAP Cube - Sum measure only works when keys are present
(This is a mock of my actual setup to help me figure out the problem.) I have one fact table and one dimension table, linked by an id field. My goal is to make a measure that sums up all "thing_count" (integer) values in my cube. If the user splits by nothing, it should show the total "thing_count" for all records in the fact table. If it's split by "category_name" from the dimension, it should show the total "thing_count" for each category. I tried to achieve this by creating a SUM measure in my cube: It works, but not in the way I intend it to It always shows (null) unless I drag in the "id" field from the dimension. Measure only: Measure and category: Measure, category, and id: How can I make the measure show the value without keys needing to be present? Edit: For GregGalloway's request (I've edited the names so the screenshots are easier to follow):
One common explanation for this behavior (no aggregation) is that you have inadvertently commented out the CALCULATE; statement in your MDX script in the cube. Please check that statement is still present.
Showing measure values as "not applicable" which are not related to dimensions
I have a requirement where report should show measures as "not applicable" if one selects a attribute which is not linked to that measure Group. 1) unrelateddimesnion= 'false' is not solving my problem because i have few default members. 2) I could able to show measure value as "not applicable " by Writing this MDX statement ([Customer].[customer name].[customer name], [measures].[sales forecast]) = 'not applicable' but with this i have to repeat the same line for each and every attribute present in the dimension ( and also for each and every measure present in the measure Group) can someone help me Writing the MDX for entire dimension instead for individual attribute. Thanks in advance. Kind Regards Mah
Bad news! An MDX script on your cube can't reference such a sub-cube in a simple way. You may have seen the LEAVES(dimension) function for a scope statement but that won't work when one attribute in a dimension has the [All] level and another has a selection. (That is to say the function returns the leaves of the dimension's key attribute). What you can do is use nested scope statements with the outer one filtering down to the list of measures you want to affect. That will at least save you typing a formula num_attributes * num_measures times. The scope statement may even accept the MEASUREGROUPMEASURES function. (When I last used that it only returned visible measures but that's probably what you want anyway.) It may be easier to link measure group and dimension and let your data sit on the UNKNOWN member. (Or an explicit dummy member.) Then filters against or slices to real customer hierarchy values will exclude your [Sales Forecast] rows and show it as null. That's not something I've done and it'll have ramifications for error processing and you'll have to allow users sight of the unknown or dummy member. So recommend you play with the idea before you rely on it. I hope this helps some.
VLOOKUP two different items, use whichever one has a number
I have a list of financial metrics in column A, rest of the columns are the time periods the financial data is for. Let's say I'm trying to calculate a ratio, but the financial metrics in A are not entirely unique, in the sense that a metric type may have more than one associated metric depending on how the company reports the metric. For example, let's say I need Depreciation Expense on the income statement... that item may be reported as Depreciation, or DepreciationAndAmortization, or something else. Any ideas how the formula in the ratio I'm trying to calculate can lookup the metric in A1, use the number immediately to the right as part of the formula... and if the metric Depreciation for example is 0, it would look for the next one I specify, like DepreciationAndAmortization, and use that one instead as the first one isn't reported.
If I understand correctly, this should do it:
=MAX(INDEX(B:B,MATCH("*depreciation*",A:A,)),INDEX(B:B,MATCH("*depreciation*",A:A,)+MATCH("*depreciation*",INDEX(A:A,1+MATCH("*depreciation*",A:A,)):INDEX(A:A,100+MATCH("*depreciation*",A:A,)),)))
If the alternatives are say in E2 and E3 then: =MAX(VLOOKUP(E2,A:B,2,0),VLOOKUP(E3,A:B,2,0)) ie try both and take whichever is larger.
About your concern on the answer of Excel Hero that returns Value error, you can use the function "iferror" and returns "0" if the value/date you're looking for isn't available.
=IFERROR(MAX(INDEX(B:B,MATCH("*depreciation*",$A:$A,)),INDEX(B:B,MATCH("*depreciation*",$A:$A,)+MATCH("*depreciation*",INDEX($A:$A,1+MATCH("*depreciation*",$A:$A,)):INDEX($A:$A,100+MATCH("*depreciation*",$A:$A,)),))),0)