# Growth counts calculations

Hello,

I have a table. I am still wondering if it is structured in an incorrect way. I have been thinking of ways to restructure it but am currently running short on ideas. I am trying to calculate % growth for IDs taking both quarters’ assessments, % not taking the second quarter assessments based on each subject. I have tried to bring the data side to side but the merging is not going as planned. Is there a different way I could restructure this table so that I could bring the Qtr to Qtr comparison side to side.

Sample:

ID Qtr Sub Score
1 1 English 8
2 1 English 9
3 1 Math 5
4 1 Math 3
5 1 English 9
6 1 Math 10
7 1 Math 7
1 2 English 9
2 2 English 8
3 2 Math 8
4 2 Math 9
5 2 English 10

I did think of measures, however, I am unable to think of one that would suffice this. Any help or suggestion would be greatly appreciated.

No, your fact table structure is spot on. Long and thin is absolutely the way to go here.

Whenever I run into a grouping problem now, my first thought is Power Query, not DAX. The Group By/All Rows is such a powerful combo for doing this type of analysis. (Again, shout out to @Melissa’s M course, which really helped me navigate the selection/projection issues in the nested tables resulting from the Group By).

Here’s the M code:

let
Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45WMlTSAWPXvPSczOIMIMtCKVYnWskIQ9wSLG4MFfdNLAEJmoIFTVAFjcGCpjhMMENVbGgAFjVHFTUHC4IEjLAYYYQhbgF3nBHCEAu445AELeGOQzUB5I5YAA==", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [ID = _t, Qtr = _t, Sub = _t, Score = _t]),
#"Changed Type" = Table.TransformColumnTypes(Source,{{"ID", Int64.Type}, {"Qtr", Int64.Type}, {"Sub", type text}, {"Score", Int64.Type}}),
#"Grouped Rows" = Table.Group(#"Changed Type", {"ID", "Sub"}, {{"AllData", each _, type table [ID=nullable number, Qtr=nullable number, Sub=nullable text, Score=nullable number]}, {"Row Count", each Table.RowCount(_), Int64.Type}}),
#"Added Custom" = Table.AddColumn(#"Grouped Rows", "Both Qs", each if [Row Count] = 2 then "TRUE" else "FALSE"),
#"Changed Type1" = Table.TransformColumnTypes(#"Added Custom",{{"Both Qs", type logical}}),
#"Scores Table" = Table.AddColumn(#"Changed Type1", "Scores Table", each if [Row Count] = 2 then
Table.SelectColumns( [AllData], "Score" ) else null),
#"Extract First Score" = Table.AddColumn(#"Scores Table", "First Score", each if [Row Count]  = 2 then
Record.ToList( [Scores Table] {0}? ){0} else
null),
#"Extract Second Score" = Table.AddColumn(#"Extract First Score", "Second Score", each if [Row Count]  = 2 then
Record.ToList( [Scores Table] {1}? ){0} else
null),
#"Added Custom1" = Table.AddColumn(#"Extract Second Score", "Percent Growth", each (( [Second Score] - [First Score] ) / [First Score] )),
#"Changed Type2" = Table.TransformColumnTypes(#"Added Custom1",{{"Percent Growth", Percentage.Type}}),
#"Removed Other Columns" = Table.SelectColumns(#"Changed Type2",{"ID", "Sub", "AllData", "Both Qs", "Percent Growth"}),
#"Expanded AllData" = Table.ExpandTableColumn(#"Removed Other Columns", "AllData", {"Qtr", "Score"}, {"Qtr", "Score"})
in
#"Expanded AllData"

and here’s the result:

The PQ transformations make the DAX for the cards a piece of cake.

I hope this is helpful. Full solution file attached below.

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Hi @supergallagher25, we’ve noticed that no response has been received from you since @BrianJ. We just want to check if you still need further help with this post? In case there won’t be any activity on it in the next few days, we’ll be tagging this post as Solved.

Hi @supergallagher25, we’ve noticed that no response has been received from you since July 5th. We just want to check if you still need further help with this post? In case there won’t be any activity on it in the next few days, we’ll be tagging this post as Solved.

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Thank you so much Brian!