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Hi team,
I have a datasets which shows the transfer of commodity between different cells. What I want to see how this commodity is moving between different cells. I have data in tabular format and I want to convert it into something like pivot below.
Is this something that can be achieved in power query? Attached is the sample excel file data.
Solved! Go to Solution.
Hi @zubair242, another solution:
Output
let
Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("hdCxCoNQDAXQXylvFkzuS7TmF7p2EwcHO3aw/w/VpygGgtPNkMMN6fvU1tAa8ugMz1Sl9zx+f59pXkYhpbzkK8uRnIbqNExGTYx4T70iGHV3SAkecXjeuryleKR60wR4pKYcI91RvqLGgACVhi3ZI4m+VxrWZI9ao+i8snx8b/gD", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [Date = _t, Action = _t, ID = _t, Source = _t, Destination = _t]),
RenamedColumns = Table.SelectColumns(Table.RenameColumns(Source,{{"Source", "Parent"}, {"Destination", "Child"}}), {"Parent", "Child"}),
Buffer = Table.Buffer(RenamedColumns),
DistinctHighestParent = Table.Distinct(Table.SelectRows(Table.SelectColumns(Buffer, {"Parent"}), each not List.Contains(Buffer[Child], [Parent]))),
Ad_Hierarchy = Table.AddColumn(DistinctHighestParent, "Hierarchy", each
[ lg = List.Generate(
()=> [ i = 0, nextChild = List.Split(Table.SelectRows(Buffer, (x)=> x[Parent] = [Parent])[Child], 1) ],
each List.NonNullCount(List.Combine(List.Transform([nextChild], (x)=> List.Skip(x, [i])))) <> 0,
each [ i = [i] +1,
nextChild = List.Combine(List.Transform([nextChild], (y)=> List.Transform([ a = Table.SelectRows(Buffer, (x)=> x[Parent] = List.Last(y))[Child], b = if List.IsEmpty(a) then {null} else a ][b], (z)=> y & {z}))) ],
each [[nextChild]] ),
toTable = Table.FromRows(List.Last(lg)[nextChild])
][toTable] ),
ExpandedHierarchy = Table.ExpandTableColumn(Ad_Hierarchy, "Hierarchy", Table.ColumnNames(Ad_Hierarchy{0}[Hierarchy])),
ColNames = Table.ColumnNames(ExpandedHierarchy),
StepBack = ExpandedHierarchy,
ChangedType = Table.TransformColumnTypes(StepBack, List.Transform(ColNames, (x)=> {x, type text})),
RenamedColumns1 = Table.RenameColumns(ChangedType,
[ a = {"Parent"} & List.Transform({1..List.Count(ColNames)-1}, (x)=> "Child " & Text.From(x)),
b = List.Zip({ColNames, a})
][b] ),
Transformed = Table.FromColumns(List.Transform(Table.ToColumns(RenamedColumns1), List.Distinct), Value.Type(Table.FirstN(RenamedColumns1, 0)))
in
Transformed
Hi @zubair242 ,
Pls has your problem been solved? If possible, please accept the helpful replies as solutions. More people will benefit from it. Thanks.
Best Regards,
Stephen Tao
Hi @zubair242, another solution:
Output
let
Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("hdCxCoNQDAXQXylvFkzuS7TmF7p2EwcHO3aw/w/VpygGgtPNkMMN6fvU1tAa8ugMz1Sl9zx+f59pXkYhpbzkK8uRnIbqNExGTYx4T70iGHV3SAkecXjeuryleKR60wR4pKYcI91RvqLGgACVhi3ZI4m+VxrWZI9ao+i8snx8b/gD", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [Date = _t, Action = _t, ID = _t, Source = _t, Destination = _t]),
RenamedColumns = Table.SelectColumns(Table.RenameColumns(Source,{{"Source", "Parent"}, {"Destination", "Child"}}), {"Parent", "Child"}),
Buffer = Table.Buffer(RenamedColumns),
DistinctHighestParent = Table.Distinct(Table.SelectRows(Table.SelectColumns(Buffer, {"Parent"}), each not List.Contains(Buffer[Child], [Parent]))),
Ad_Hierarchy = Table.AddColumn(DistinctHighestParent, "Hierarchy", each
[ lg = List.Generate(
()=> [ i = 0, nextChild = List.Split(Table.SelectRows(Buffer, (x)=> x[Parent] = [Parent])[Child], 1) ],
each List.NonNullCount(List.Combine(List.Transform([nextChild], (x)=> List.Skip(x, [i])))) <> 0,
each [ i = [i] +1,
nextChild = List.Combine(List.Transform([nextChild], (y)=> List.Transform([ a = Table.SelectRows(Buffer, (x)=> x[Parent] = List.Last(y))[Child], b = if List.IsEmpty(a) then {null} else a ][b], (z)=> y & {z}))) ],
each [[nextChild]] ),
toTable = Table.FromRows(List.Last(lg)[nextChild])
][toTable] ),
ExpandedHierarchy = Table.ExpandTableColumn(Ad_Hierarchy, "Hierarchy", Table.ColumnNames(Ad_Hierarchy{0}[Hierarchy])),
ColNames = Table.ColumnNames(ExpandedHierarchy),
StepBack = ExpandedHierarchy,
ChangedType = Table.TransformColumnTypes(StepBack, List.Transform(ColNames, (x)=> {x, type text})),
RenamedColumns1 = Table.RenameColumns(ChangedType,
[ a = {"Parent"} & List.Transform({1..List.Count(ColNames)-1}, (x)=> "Child " & Text.From(x)),
b = List.Zip({ColNames, a})
][b] ),
Transformed = Table.FromColumns(List.Transform(Table.ToColumns(RenamedColumns1), List.Distinct), Value.Type(Table.FirstN(RenamedColumns1, 0)))
in
Transformed
hat is the logic for the levels??
Logic of levels is simply movements for commodity from one cell to other. As, I have provided the table, commodity is moved through different cells. We want to track the movement like if we have commodity K2204, what is the source/chain?
@zubair242 you lost K3502 -> K3504 in your sample
let
Source = Excel.CurrentWorkbook(){[Name="Table1"]}[Content],
pairs = List.Buffer(List.Zip({Source[Source], Source[Destination]})),
replace = (lst, pair) =>
[idx = List.PositionOf(lst, pair, Occurrence.First, (c, v) => List.Last(c) = pair{0}),
repl = if idx <> - 1
then List.ReplaceRange(lst, idx, 1, {lst{idx} & {pair{1}}})
else lst &
(
(z) => {List.Repeat({null}, z) & {pair{1}}}
)
(List.PositionOf(pairs, pair{0}, Occurrence.First, (c, v) => c{0} = v) + 1)
][repl],
gen = List.Generate(
() => [i = 0, pair = {pairs{0}}, res = pair],
(x) => x[i] < List.Count(pairs),
(x) => [i = x[i] + 1, pair = pairs{i}, res = replace(x[res], pair)],
(x) => x[res]
),
res = Table.FromColumns(List.Zip(List.Last(gen)))
in
res
@AlienSx Not only that but the dual pathways from K3401 to K3502 are lost as well.
I think this should he represented by a Network Graph chart rather than a Sankey. And definitely not by a table.
Have you considered using a Sankey Diagram chart instead?
Hi @lbendlin , thank you for providing a good idea to represent this in the sankey visual. However, it is an audit requirement, so user will be looking to see this in the tabular format. Thanks!
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