Calculated column - crate ID number

[Anonymous]

Hi i am trying to crate 2 Calculated columns:

1) Sprint ID 

2) Sprint Time - start from 0 untill velocity is less the 15

i tried this formula but no luck....

Sprint ID =

IF(Data[Helper]=1,

CALCULATE(COUNTROWS(Data),

FILTER(Data,

Data[Index] <= EARLIER(Data[Index]) && Data[Date]=EARLIER(Data[Date]) )) ,BLANK())

Date	Time	Seconds	Velocity	Acceleration	Index	Sprint Time	Sprint ID
02/03/2019	18:19:00	3	13.51	0.01	0
02/03/2019	18:19:00	3	13.51	0.01	1
02/03/2019	18:19:00	3	13.74	0.17	2
02/03/2019	18:19:00	4	14.06	0.35	3
02/03/2019	18:19:00	4	13.63	0.07	4
02/03/2019	18:19:00	4	13.84	0.2	5
02/03/2019	18:19:00	4	13.98	0.24	6
02/03/2019	18:19:00	4	14.36	0.45	7
02/03/2019	18:19:00	4	14.82	0.65	8
02/03/2019	18:19:00	4	15.16	0.73	9	0	1
02/03/2019	18:19:00	4	15.39	0.71	10	1	1
02/03/2019	18:19:00	5	15.46	0.58	11	2	1
02/03/2019	18:19:00	5	15.46	0.58	12	3	1
02/03/2019	18:19:00	5	15.81	0.67	13	4	1
02/03/2019	18:19:00	5	16.04	0.67	14	5	1
02/03/2019	18:19:00	5	16.29	0.68	15	6	1
02/03/2019	18:20:00	5	17.1	0.87	16	7	1
02/03/2019	18:20:00	5	17.1	0.87	17	8	1
02/03/2019	18:20:00	5	17.06	0.62	18	9	1
02/03/2019	18:20:00	5	17.49	0.77	19	10	1
02/03/2019	18:20:00	5	17.69	0.71	20	11	1
02/03/2019	18:20:00	6	17.67	0.52	21	12	1
02/03/2019	18:20:00	6	17.62	0.36	22	13	1
02/03/2019	18:20:00	6	17.54	0.21	23	14	1
02/03/2019	18:20:00	6	17.73	0.29	24	15	1
02/03/2019	18:20:00	6	17.44	0.02	25	16	1
02/03/2019	18:20:00	6	17.52	0.08	26	17	1
02/03/2019	18:20:00	6	17.45	0.01	27	18	1
02/03/2019	18:20:00	11	10.16	0.56	28
02/03/2019	18:20:00	12	10.15	0.32	29
02/03/2019	18:20:00	12	10.29	0.34	30
02/03/2019	18:20:00	12	10.8	0.61	31
02/03/2019	18:20:00	12	10.56	0.29	32
02/03/2019	18:20:00	12	10.18	0.01	33
02/03/2019	18:20:00	12	10.7	0.36	34
02/03/2019	18:20:00	13	10.79	0.34	35
02/03/2019	18:20:00	13	14.71	2.07	99
02/03/2019	18:20:00	13	15.78	2.3	100	0	2
02/03/2019	18:20:00	13	16.39	2.14	101	1	2
02/03/2019	18:20:00	13	17.58	1.91	102	2	2
02/03/2019	18:20:00	13	17.58	1.91	103	3	2
02/03/2019	18:20:00	13	17.86	1.62	104	4	2
02/03/2019	18:20:00	13	18.56	1.7	105	5	2
02/03/2019	18:20:00	14	19.14	1.68	106	6	2
02/03/2019	18:20:00	14	19.45	1.48	107	7	2
02/03/2019	18:20:00	14	20.08	1.54	108	8	2
02/03/2019	18:20:00	14	20.19	1.24	109	9	2
02/03/2019	18:20:00	14	20.77	1.33	110	10	2
02/03/2019	18:20:00	14	21.07	1.2	111	11	2

[vanessafvg]

@Anonymous  i dont feel like you have explained this clearly, you already have a sprint id, what sprint id are you trying to calcualted.

sprint time?   are you wanting to sum all the time up until velocity < 15

also in your calculation you have helper?  Data[Helper]=1

where is that in this data? 

[Anonymous]

Hi sorry i was unclear, the table i attached was my dasire outcome what i have at the moment is 

Date   Time     Seconds   Velocity   Accelartion   

Date	Time	Seconds	Velocity	Acceleration
02/03/2019	18:19:00	3	13.51	0.01
02/03/2019	18:19:00	3	13.51	0.01
02/03/2019	18:19:00	3	13.74	0.17
02/03/2019	18:19:00	4	14.06	0.35
02/03/2019	18:19:00	4	13.63	0.07
02/03/2019	18:19:00	4	13.84	0.2
02/03/2019	18:19:00	4	13.98	0.24
02/03/2019	18:19:00	4	14.36	0.45
02/03/2019	18:19:00	4	14.82	0.65
02/03/2019	18:19:00	4	15.16	0.73
02/03/2019	18:19:00	4	15.39	0.71
02/03/2019	18:19:00	5	15.46	0.58
02/03/2019	18:19:00	5	15.46	0.58
02/03/2019	18:19:00	5	15.81	0.67
02/03/2019	18:19:00	5	16.04	0.67
02/03/2019	18:19:00	5	16.29	0.68
02/03/2019	18:20:00	5	17.1	0.87
02/03/2019	18:20:00	5	17.1	0.87
02/03/2019	18:20:00	5	17.06	0.62
02/03/2019	18:20:00	5	17.49	0.77
02/03/2019	18:20:00	5	17.69	0.71
02/03/2019	18:20:00	6	17.67	0.52
02/03/2019	18:20:00	6	17.62	0.36
02/03/2019	18:20:00	6	17.54	0.21
02/03/2019	18:20:00	6	17.73	0.29
02/03/2019	18:20:00	6	17.44	0.02
02/03/2019	18:20:00	6	17.52	0.08
02/03/2019	18:20:00	6	17.45	0.01
02/03/2019	18:20:00	11	10.16	0.56
02/03/2019	18:20:00	12	10.15	0.32
02/03/2019	18:20:00	12	10.29	0.34
02/03/2019	18:20:00	12	10.8	0.61

[BekahLoSurdo]

Hi @Anonymous,

I would do this in Power Query. Using your starting data in an Excel workbook, here is my code:

let
    Source = Excel.Workbook(File.Contents("C:\Users\rlosurdo\Desktop\SprintTime.xlsx"), null, true),
    Original_Sheet = Source{[Item="Original",Kind="Sheet"]}[Data],
    #"Promoted Headers" = Table.PromoteHeaders(Original_Sheet, [PromoteAllScalars=true]),
    #"Changed Type" = Table.TransformColumnTypes(#"Promoted Headers",{{"Date", type date}, {"Time", type datetime}, {"Seconds", Int64.Type}, {"Velocity", type number}, {"Acceleration", type number}}),
    #"Added Index" = Table.AddIndexColumn(#"Changed Type", "Index", 0, 1),
    Velocities = Table.FromColumns(
	Table.ToColumns(#"Added Index") & 
	Table.ToColumns(
		Table.InsertRows(Table.SelectColumns(#"Added Index","Velocity"),0,{[Velocity = null]})) &
	Table.ToColumns(
		Table.RemoveFirstN(Table.SelectColumns(#"Added Index","Velocity"),1)),
	Table.ColumnNames(#"Added Index") & {"PreviousVelocity", "NextVelocity"}),
    #"Removed Bottom Rows" = Table.RemoveLastN(Velocities,1),
    #"Added SprintAudit" = Table.AddColumn(#"Removed Bottom Rows", "SprintAudit", each if [Velocity] >= 15 then if [PreviousVelocity] < 15 then "Initial" else if [NextVelocity] < 15 or [NextVelocity] is null then "Completion" else "Continued" else null),
    #"Added Join Key 1" = Table.AddColumn(#"Added SprintAudit", "Join Key", each if [SprintAudit] <> null then 1 else 0),
    InitialIndexTable = Table.SelectRows(#"Added Join Key 1", each ([SprintAudit] = "Initial")),
    #"Added Initial Index" = Table.AddIndexColumn(InitialIndexTable, "Sprint Index", 1, 1),
    CompletionIndexTable = Table.SelectRows(#"Added Join Key 1", each ([SprintAudit] = "Completion")),
    #"Added Completion Index" = Table.AddIndexColumn(CompletionIndexTable, "Sprint Index", 1, 1),
    IndexTable = Table.Combine({#"Added Completion Index", #"Added Initial Index"}),
    #"Removed Other Columns" = Table.SelectColumns(IndexTable,{"SprintAudit", "Sprint Index", "Index"}),
    #"Pivoted Column" = Table.Pivot(#"Removed Other Columns", List.Distinct(#"Removed Other Columns"[SprintAudit]), "SprintAudit", "Index", List.Sum),
    #"Added Join Key" = Table.AddColumn(#"Pivoted Column", "Join Key", each 1),
    #"Merged Queries" = Table.NestedJoin(#"Added Join Key 1",{"Join Key"},#"Added Join Key",{"Join Key"},"IndexTable",JoinKind.LeftOuter),
    #"Expanded IndexTable" = Table.ExpandTableColumn(#"Merged Queries", "IndexTable", {"Sprint Index", "Completion", "Initial"}, {"Sprint Index", "Completion", "Initial"}),
    #"Added Sprint ID" = Table.AddColumn(#"Expanded IndexTable", "Sprint ID", each try if [Index] >= [Initial] and [Index] <= [Completion] then [Sprint Index] else 0 otherwise null),
    #"Filtered Rows" = Table.SelectRows(#"Added Sprint ID", each ([Sprint ID] <> 0)),
    Partition = Table.Group(#"Filtered Rows", {"Sprint ID"}, {{"Partition", each Table.AddIndexColumn(_, "Sprint Time Setup",0,1), type table}}),
    #"Expanded Partition" = Table.ExpandTableColumn(Partition, "Partition", {"Date", "Time", "Seconds", "Velocity", "Acceleration", "Index", "Sprint Time Setup"}, {"Date", "Time", "Seconds", "Velocity", "Acceleration", "Index", "Sprint Time Setup"}),
    #"Added Sprint Time" = Table.AddColumn(#"Expanded Partition", "Sprint Time", each if [Sprint ID] <> null then [Sprint Time Setup] else null),
    #"Sorted Rows" = Table.Sort(#"Added Sprint Time",{{"Index", Order.Ascending}}),
    #"Removed Columns" = Table.RemoveColumns(#"Sorted Rows",{"Sprint Time Setup"}),
    #"Reordered Columns" = Table.ReorderColumns(#"Removed Columns",{"Date", "Time", "Seconds", "Velocity", "Acceleration", "Index", "Sprint Time", "Sprint ID"})
in
    #"Reordered Columns"

Here is the resulting table in Power BI:

I basically created a few temporary tables so that I could define and index each sprint as its own entity. Then I used @ImkeF's partition magic (https://community.powerbi.com/t5/Desktop/Custom-column-Index-or-Ranking-by-other-column/td-p/33864) to add an index for each individual Sprint ID.

Let me know if you have any questions or would like me to send over my workbook.

[ImkeF · Accepted solution]

Hi @BekahLoSurdo ,

that's a good solution to the problem.

However, if you apply it to large data, it could could become slow. This will probably run much faster and is also a bit shorter:

let
    Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("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", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type text) meta [Serialized.Text = true]) in type table [Date = _t, Time = _t, Seconds = _t, Velocity = _t, Acceleration = _t, Index = _t]),
    #"Changed Type" = Table.TransformColumnTypes(Source,{{"Date", type date}, {"Time", type time}, {"Seconds", Int64.Type}, {"Velocity", type number}, {"Acceleration", type number}, {"Index", Int64.Type}}),
    #"Added Custom" = Table.AddColumn(#"Changed Type", "GreaterThan15", each [Velocity] > 15),
    #"Grouped Rows" = Table.Group(#"Added Custom", {"GreaterThan15"}, {{"All", each if List.First(_[GreaterThan15]) = true then Table.AddIndexColumn(_, "SprintTime",0,1) else _}}, GroupKind.Local),
    #"Added Index" = Table.AddIndexColumn(#"Grouped Rows", "Index1", 0, 1),
    #"Expanded All" = Table.ExpandTableColumn(#"Added Index", "All", {"Date", "Time", "Seconds", "Velocity", "Acceleration", "Index", "SprintTime"}, {"Date", "Time", "Seconds", "Velocity", "Acceleration", "Index", "SprintTime"}),
    AddSprintID = Table.AddColumn(#"Expanded All", "SprintID", each if [GreaterThan15] then Number.RoundUp([Index1]/2) else null),
    #"Removed Columns" = Table.RemoveColumns(AddSprintID,{"GreaterThan15", "Index1"})
in
    #"Removed Columns"

The key lies in the 4th parameter of the Table.Group-function, where you use GroupKind.Local. See this article on how it works: https://blog.crossjoin.co.uk/2014/01/03/aggregating-by-local-groups-in-power-query/ 

[BekahLoSurdo]

This is great @ImkeF. I did not know about GroupKind.Local and can see how it is the perfect thing to use here and also how it could be useful elsewhere - I appreciate the addition to my M toolkit!

[Anonymous]

Hi ImkeF thanks allot, it works perfect and the preferments are much batter.