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Anonymous
Not applicable

Faster Division/Multiplication using Merge same table Query - Power Query

I have a table of Columns containing Attribute counts. I have added a column that does row-wise summation of the Attribute column (denoted by Numbers) values. I want to Divide the Attribute columns by the "Count" column, in-place (replace values) i.e. do a `Percentage of Row-Total`. I don't want to add new columns, then do the calculation, then delete the original column.

 

"ID"  "CD"     "6"    "5"     "4"    "3"   "1"   "Count"

1RJ.14512453755302
2RJ.2436636579211
3RJ.32910441768258
4RJ.42646233411140
5RJ.53451412213161
6RJ.63363265813193
7RJ.7225640418167
8RJ.83493405411232
9RJ.93469345011198
10RJ.10274633428156
11RJ.113270264215185
12RJ.12225735455164
13RJ.13258339439199
14RJ.14316926508184
15RJ.152462393510170
16RJ.16117543576192
17RJ.17214521238118
18RJ.182051303212145
19RJ.19286034379168
20RJ.20263829414138
21RJ.212164234211161
22RJ.223361353811178
23RJ.23195136368150
24RJ.242265323611166
25RJ.252885354511204
26RJ.262656282711148
27RJ.27294341337153
28RJ.282257154311148
29RJ.29143022359110
30RJ.30193525278114
31RJ.311830282612114
32RJ.321354364410157
33RJ.33205919409147
34RJ.34243438235124
35RJ.35266737398177
36RJ.36274631347145
37RJ.372426273613126
38RJ.38142424211093
39RJ.393158342810161
40RJ.401845253710135

 

In one of my searches, someone had suggested that the values for multiple columns could be calculated in a faster way (avoid row level context evaluation) by merging the table with itself and with some M-code. But not shared the code example.

Is it possible?

1 ACCEPTED SOLUTION
Jimmy801
Community Champion
Community Champion

Hello @Anonymous 

 

here some dynamic solution. Uses Unpivoting, Grouping and twice transforming of columns. The only parameter you have to change is the list in the Unpivot other (in case you have some additional columns). As you can see you can also remove the column "count" from your table.

let
    Origine = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("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", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [ID = _t, CD = _t, #"6" = _t, #"5" = _t, #"4" = _t, #"3" = _t, #"1" = _t, Count = _t]),
    ChangeType = Table.TransformColumnTypes(Origine,{{"6", Int64.Type}, {"5", Int64.Type}, {"4", Int64.Type}, {"3", Int64.Type}, {"1", Int64.Type}}),
    #"Removed Columns" = Table.RemoveColumns(ChangeType,{"Count"}),
    #"Unpivoted Other Columns" = Table.UnpivotOtherColumns(#"Removed Columns", {"ID", "CD"}, "Attribute", "Value"),
    #"Grouped Rows" = Table.Group(#"Unpivoted Other Columns", {"CD"}, {{"AllRows", each _, type table [ID=text, CD=text, Attribute=text, Value=number]}}),
    TransformAllRows = Table.TransformColumns
    (
        #"Grouped Rows",
        {
            {
                "AllRows",
                (tbl)=> 
                let
                    SumValue = List.Sum(tbl[Value]),
                    TransformTbl = Table.TransformColumns
                    (
                        tbl,
                        {
                            {
                                "Value",
                                each _ / SumValue
                            }
                        }
                    )
                in 
                    TransformTbl

            }
        }
    ),
    #"Expanded AllRows" = Table.ExpandTableColumn(TransformAllRows, "AllRows", {"ID", "Attribute", "Value"}, {"ID", "Attribute", "Value"}),
    #"Pivoted Column" = Table.Pivot(#"Expanded AllRows", List.Distinct(#"Expanded AllRows"[Attribute]), "Attribute", "Value", List.Sum),
    #"Changed Type" = Table.TransformColumnTypes(#"Pivoted Column",{{"ID", Int64.Type}}),
    #"Sorted Rows" = Table.Sort(#"Changed Type",{{"ID", Order.Ascending}})
in
    #"Sorted Rows"

 

Copy paste this code to the advanced editor in a new blank query to see how the solution works.

If this post helps or solves your problem, please mark it as solution (to help other users find useful content and to acknowledge the work of users that helped you)
Kudoes are nice too

Have fun

Jimmy

 

View solution in original post

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