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In the data, there are representatives for each block, and the same person appears multiple times depending on the date and time. I'd like to create a column that groups by block and representative, counting the number of representatives for each block and ranking them.
I will provide the source that was entered in "Data Input," so please feel free to use it if you like.
Source = 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 [rerepresentatives = _t, block = _t, datetime = _t])
This is a display of the final data that has been processed in Excel.
If anyone knows of any good ideas or methods to achieve a final result like this, could you please share them with me?
Best regards,
roxy
Solved! Go to Solution.
Hi @roxy12 ,
How about this:
Here the code in M:
let Source = 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 [rerepresentatives = _t, block = _t, datetime = _t]), #"Changed Type" = Table.TransformColumnTypes(Source,{{"rerepresentatives", type text}, {"block", type text}, {"datetime", type datetime}}), #"Grouped Rows 1" = Table.Group(#"Changed Type", {"rerepresentatives", "block"}, {{"Count", each Table.RowCount(_), Int64.Type}}), #"Grouped Rows 2" = Table.Group(#"Grouped Rows 1", {"block"}, {{"AllRows", each SubGroupAddIndex(_), type table [block=nullable text, rerepresentatives=text, Count=number, Index=number]}}), SubGroupAddIndex = (Table as table) as table => let #"Sorted Rows" = Table.Sort(Table,{{"Count", Order.Descending}}), #"Added Index" = Table.AddIndexColumn(#"Sorted Rows", "Index", 1, 1, Int64.Type) in #"Added Index", #"Expanded AllRows" = Table.ExpandTableColumn(#"Grouped Rows 2", "AllRows", {"rerepresentatives", "Count", "Index"}, {"rerepresentatives", "Count", "IndexDense"}), #"Grouped Rows 3" = Table.Group(#"Expanded AllRows", {"block", "Count"}, {{"Index", each List.Min([IndexDense]), type nullable number}}), #"Merged Queries" = Table.NestedJoin(#"Expanded AllRows", {"block", "Count"}, #"Grouped Rows 3", {"block", "Count"}, "Grouped Rows", JoinKind.LeftOuter), #"Expanded Grouped Rows" = Table.ExpandTableColumn(#"Merged Queries", "Grouped Rows", {"Index"}, {"Grouped Rows.Index"}), #"Removed Columns" = Table.RemoveColumns(#"Expanded Grouped Rows",{"IndexDense"}) in #"Removed Columns"
Let me know if this helps 🙂
/Tom
https://www.tackytech.blog/
https://www.instagram.com/tackytechtom/
Did I answer your question❓➡️ Please, mark my post as a solution ✔️ |
Also happily accepting Kudos 🙂 |
Feel free to connect with me on LinkedIn! |
#proudtobeasuperuser |
Genearlly speaking, PQ was designed for data cleansing instead of calculation. DAX solution is way more elegant.
Thanks to the great efforts by MS engineers to simplify syntax of DAX! Most beginners are SUCCESSFULLY MISLED to think that they could easily master DAX; but it turns out that the intricacy of the most frequently used RANKX() is still way beyond their comprehension! |
DAX is simple, but NOT EASY! |
Hi @roxy12 ,
How about this:
Here the code in M:
let Source = 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 [rerepresentatives = _t, block = _t, datetime = _t]), #"Changed Type" = Table.TransformColumnTypes(Source,{{"rerepresentatives", type text}, {"block", type text}, {"datetime", type datetime}}), #"Grouped Rows 1" = Table.Group(#"Changed Type", {"rerepresentatives", "block"}, {{"Count", each Table.RowCount(_), Int64.Type}}), #"Grouped Rows 2" = Table.Group(#"Grouped Rows 1", {"block"}, {{"AllRows", each SubGroupAddIndex(_), type table [block=nullable text, rerepresentatives=text, Count=number, Index=number]}}), SubGroupAddIndex = (Table as table) as table => let #"Sorted Rows" = Table.Sort(Table,{{"Count", Order.Descending}}), #"Added Index" = Table.AddIndexColumn(#"Sorted Rows", "Index", 1, 1, Int64.Type) in #"Added Index", #"Expanded AllRows" = Table.ExpandTableColumn(#"Grouped Rows 2", "AllRows", {"rerepresentatives", "Count", "Index"}, {"rerepresentatives", "Count", "IndexDense"}), #"Grouped Rows 3" = Table.Group(#"Expanded AllRows", {"block", "Count"}, {{"Index", each List.Min([IndexDense]), type nullable number}}), #"Merged Queries" = Table.NestedJoin(#"Expanded AllRows", {"block", "Count"}, #"Grouped Rows 3", {"block", "Count"}, "Grouped Rows", JoinKind.LeftOuter), #"Expanded Grouped Rows" = Table.ExpandTableColumn(#"Merged Queries", "Grouped Rows", {"Index"}, {"Grouped Rows.Index"}), #"Removed Columns" = Table.RemoveColumns(#"Expanded Grouped Rows",{"IndexDense"}) in #"Removed Columns"
Let me know if this helps 🙂
/Tom
https://www.tackytech.blog/
https://www.instagram.com/tackytechtom/
Did I answer your question❓➡️ Please, mark my post as a solution ✔️ |
Also happily accepting Kudos 🙂 |
Feel free to connect with me on LinkedIn! |
#proudtobeasuperuser |
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