Forum Discussion
Conditionally transform multiple columns in single step
Hi All,
I need to implement the below requirement for a very large dataset (hence need a solution which would perform well).
Some mock-up data:
The requirement is when the status is 'AA' or 'ZZ', all the value fields should be 0.
So the result should look like below:
Would like to do it in power query editor (and not on desktop using DAX as the transformations would get applied on a fact table having nearly 100 millions of records. So multiple calculated columns would cause performance issues during refresh). Also don't want to rework on measures/visuals for changing references (this can't be done on datasource side as well).
Tried to do it by creating simple conditional columns like below (thought of renaming & removing the original value fields later):
but don't really want to create multiple addional steps for each numeric field (there's quite a few!). Also could not make it work in a single step with list.accumulate etc. (for example).
Please can someone help on how this can be done in the best possible way? (don't really want to create additional columns if the existing ones can be transformed)
Regards,
Rishi
BA_Pete AlexisOlson Anonymous mahoneypat amitchandak Samarth_18 TheoClbendlin parry2k bcdobbs
let Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45WMlTSUXJ0BBKGBkDC0hhImCjF6kQrGQFZTs4gMVMgYQZSZwqRAamJigIpBKmxsABpVoqNBQA=", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [id = _t, status = _t, value1 = _t, value2 = _t, value3 = _t]), #"Replaced Value" = Table.ReplaceValue(Source,each List.Contains({"AA","ZZ"},[status]),"0",(o,c,r)=> if c then r else o,{"value1","value2","value3"}) in #"Replaced Value"How to use this code: Create a new Blank Query. Click on "Advanced Editor". Replace the code in the window with the code provided here. Click "Done".
4 Replies
let Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45WMlTSUXJ0BBKGBkDC0hhImCjF6kQrGQFZTs4gMVMgYQZSZwqRAamJigIpBKmxsABpVoqNBQA=", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [id = _t, status = _t, value1 = _t, value2 = _t, value3 = _t]), #"Replaced Value" = Table.ReplaceValue(Source,each List.Contains({"AA","ZZ"},[status]),"0",(o,c,r)=> if c then r else o,{"value1","value2","value3"}) in #"Replaced Value"How to use this code: Create a new Blank Query. Click on "Advanced Editor". Replace the code in the window with the code provided here. Click "Done".
Hi,
you can try this:
let
Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("TY+xDcAgDAR3oaYIJgQogUgMkA7E/mvEH4noC06PT9hmTuOMNaUo3EFYdhrRWJsiBwKM19iqInoCzKlxDMUpBBg8H5jjAwHm0tgf3P+DcsRiaOU8ASbtxcQRYPIen4QA833s7igkwlov", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [id = _t, status = _t, Value1 = _t, Value2 = _t, Value3 = _t]),
#"Filtered Rows1" = Table.SelectRows(Source, each ([status] <> "AA" and [status] <> "ZZ")),
#"Filtered Rows" = Table.SelectRows(Source, each ([status] = "AA" or [status] = "ZZ")),
#"Multiplied Column" = Table.TransformColumns(#"Filtered Rows", {{"Value1", each Text.From( Number.FromText(_) * 0), type text},{"Value2", each Text.From( Number.FromText(_) * 0), type text},{"Value3", each Text.From( Number.FromText(_) * 0), type text}}),
#"Appended Query" = Table.Combine({#"Filtered Rows1", #"Multiplied Column"}),
#"Sorted Rows" = Table.Sort(#"Appended Query",{{"id", Order.Ascending}})
in
#"Sorted Rows"and from this
you get this
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= let cols = Table.ToColumns(your_tab), /*{"id","v1","v2","v3"}*/ set=List.Accumulate(lpo,List.Zip({cols{1},cols{2},cols{3}}),(s,c)=> List.ReplaceRange(s,c,1,{{0,0,0}})) in Table.FromColumns({cols{0}}&List.Zip(set), {"id","v1","v2","v3"})Perhaps for transforming large data frames Power Query is not the most suitable tool.
You should consider using other languages (JULIA's DataFrames.jl package for example solves the whole thing (100 million lines) in less than 10 sec with just one half line instruction)
