Forum Discussion
Recuento de ciclos
Hola
Soy nuevo en power BI. No estoy seguro de si necesito usar DAX o M para lo que necesito.
Me gustaría crear un recuento cíclico en una nueva columna basada en lo siguiente:
*para cada dispositivo
*cambiar el ciclo cuando el estado alcanza "1"
*Cada dispositivo tiene sus propios recuentos de ciclos
*los ciclos aumentan en 1
*los ciclos deben estar en orden cronológico por "tiempo", para cada dispositivo
Intenté lo siguiente sin éxito:
| Hora | Dispositivo | m1 | m2 | m3 | Estado | Ciclos |
| 9/1/2020 0:01 | 4 | -0.103 | 0 | 100 | 1 | 1 |
| 9/1/2020 12:56 | 4 | -0.103 | 0 | 100 | 1 | 1 |
| 9/1/2020 13:26 | 4 | -0.103 | 0 | 100 | 1 | 1 |
| 9/1/2020 13:26 | 4 | -0.594 | 0 | 100 | 4 | 1 |
| 9/1/2020 13:31 | 4 | -0.594 | -0.1 | 100 | 4 | 1 |
| 9/1/2020 13:36 | 4 | -0.654 | -15 | 99.9 | 4 | 1 |
| 9/1/2020 20:31 | 4 | 0.02 | -24.7 | 77.3 | 4 | 1 |
| 9/1/2020 20:33 | 4 | 16.927 | 0 | 77.8 | 3 | 1 |
| 9/1/2020 20:38 | 4 | 17.407 | 1.5 | 79.1 | 3 | 1 |
| 9/1/2020 20:58 | 4 | 17.331 | 7.3 | 84.4 | 3 | 1 |
| 9/1/2020 21:23 | 4 | 17.282 | 14.5 | 91.1 | 3 | 1 |
| 9/1/2020 21:27 | 4 | 17.284 | 15.9 | 92.4 | 3 | 1 |
| 9/1/2020 21:28 | 4 | 15.926 | 16.2 | 92.6 | 2 | 1 |
| 9/1/2020 23:23 | 4 | 2.269 | 25.6 | 101.3 | 2 | 1 |
| 9/1/2020 23:43 | 4 | 1.862 | 26.4 | 101.9 | 2 | 1 |
| 9/1/2020 23:44 | 4 | -0.1 | 0 | 100 | 1 | 2 |
| 9/2/2020 0:14 | 4 | -0.1 | 0 | 100 | 1 | 2 |
| 9/2/2020 7:19 | 4 | -0.102 | 0 | 100 | 1 | 2 |
| 9/2/2020 7:24 | 4 | -0.102 | 0 | 100 | 1 | 2 |
| 9/2/2020 7:26 | 4 | -0.175 | 0 | 100 | 4 | 2 |
| 9/2/2020 7:31 | 4 | -1.253 | -0.1 | 99.9 | 4 | 2 |
| 9/2/2020 20:01 | 4 | -0.025 | -5 | 79.7 | 4 | 2 |
| 9/2/2020 20:06 | 4 | -0.025 | -15 | 79.7 | 4 | 2 |
| 9/2/2020 20:11 | 4 | -0.025 | -22.2 | 79.7 | 4 | 2 |
| 9/2/2020 20:15 | 4 | 7.011 | 0 | 80.1 | 3 | 2 |
| 9/2/2020 20:20 | 4 | 17.448 | 1.5 | 81.5 | 3 | 2 |
| 9/2/2020 20:35 | 4 | 17.376 | 5.9 | 85.5 | 3 | 2 |
| 9/2/2020 20:55 | 4 | 17.344 | 11.6 | 90.8 | 3 | 2 |
| 9/2/2020 20:58 | 4 | 16.897 | 12.5 | 91.6 | 2 | 2 |
| 9/2/2020 21:18 | 4 | 9.272 | 15.6 | 94.4 | 2 | 2 |
| 9/2/2020 23:08 | 4 | 2.274 | 22.6 | 100.8 | 2 | 2 |
| 9/2/2020 23:11 | 4 | 1.002 | 0 | 100 | 1 | 3 |
| 9/3/2020 9:35 | 4 | -0.102 | 0 | 100 | 1 | 3 |
| 9/3/2020 9:39 | 4 | -1.319 | 0 | 100 | 4 | 3 |
| 9/3/2020 9:49 | 4 | -0.661 | -0.1 | 99.9 | 4 | 3 |
| 9/3/2020 14:09 | 4 | -3.817 | -15.4 | 85.9 | 4 | 3 |
| 9/3/2020 20:34 | 4 | -0.294 | -33.2 | 69.6 | 4 | 3 |
| 9/3/2020 20:36 | 4 | 17.005 | 0 | 70.1 | 3 | 3 |
| 9/3/2020 21:21 | 4 | 17.305 | 13.1 | 82 | 3 | 3 |
| 9/3/2020 21:56 | 4 | 17.398 | 23.2 | 91.3 | 3 | 3 |
| 9/3/2020 21:57 | 4 | 15.347 | 23.4 | 91.5 | 2 | 3 |
| 9/3/2020 22:57 | 4 | 4.322 | 30.8 | 98.3 | 2 | 3 |
| 9/4/2020 0:32 | 4 | 2.248 | 34.9 | 102.1 | 2 | 3 |
| 9/4/2020 0:34 | 4 | 0.622 | 0 | 100 | 1 | 4 |
| 9/4/2020 7:14 | 4 | -0.103 | 0 | 100 | 1 | 4 |
| 9/4/2020 7:18 | 4 | -0.716 | 0 | 100 | 4 | 4 |
| 9/4/2020 7:23 | 4 | -1.818 | -0.2 | 99.9 | 4 | 4 |
| 9/4/2020 12:23 | 4 | -7.451 | -7 | 93.6 | 4 | 4 |
| 9/4/2020 13:58 | 4 | -3.936 | -14.9 | 86.3 | 4 | 4 |
| 9/4/2020 18:48 | 4 | -0.704 | -26.9 | 75.3 | 4 | 4 |
| 9/4/2020 18:51 | 4 | 11.033 | 0 | 75.8 | 3 | 4 |
| 9/4/2020 19:16 | 4 | 17.268 | 7.3 | 82.5 | 3 | 4 |
| 9/4/2020 19:46 | 4 | 17.223 | 15.9 | 90.4 | 3 | 4 |
| 9/4/2020 19:51 | 4 | 16.994 | 17.2 | 91.6 | 2 | 4 |
| 9/4/2020 22:11 | 4 | 2.249 | 27.9 | 101.4 | 2 | 4 |
| 9/4/2020 22:12 | 4 | -0.102 | 0 | 100 | 1 | 5 |
| 9/4/2020 23:52 | 4 | -0.104 | 0 | 100 | 1 | 5 |
| 9/1/2020 0:01 | 7 | -0.103 | 0 | 100 | 1 | 1 |
| 9/1/2020 12:56 | 7 | -0.103 | 0 | 100 | 1 | 1 |
| 9/1/2020 13:26 | 7 | -0.103 | 0 | 100 | 1 | 1 |
| 9/1/2020 13:26 | 7 | -0.594 | 0 | 100 | 4 | 1 |
| 9/1/2020 13:31 | 7 | -0.594 | -0.1 | 100 | 4 | 1 |
| 9/1/2020 13:36 | 7 | -0.654 | -15 | 99.9 | 4 | 1 |
| 9/1/2020 20:31 | 7 | 0.02 | -24.7 | 77.3 | 4 | 1 |
| 9/1/2020 20:33 | 7 | 16.927 | 0 | 77.8 | 3 | 1 |
| 9/1/2020 20:38 | 7 | 17.407 | 1.5 | 79.1 | 3 | 1 |
| 9/1/2020 20:58 | 7 | 17.331 | 7.3 | 84.4 | 3 | 1 |
| 9/1/2020 21:23 | 7 | 17.282 | 14.5 | 91.1 | 3 | 1 |
| 9/1/2020 21:27 | 7 | 17.284 | 15.9 | 92.4 | 3 | 1 |
| 9/1/2020 21:28 | 7 | 15.926 | 16.2 | 92.6 | 2 | 1 |
| 9/1/2020 23:23 | 7 | 2.269 | 25.6 | 101.3 | 2 | 1 |
| 9/1/2020 23:43 | 7 | 1.862 | 26.4 | 101.9 | 2 | 1 |
| 9/1/2020 23:44 | 7 | -0.1 | 0 | 100 | 1 | 2 |
@JoeJoe666 - Ah, quieres Cthulhu - https://community.powerbi.com/t5/Quick-Measures-Gallery/Cthulhu/m-p/509739#M211
En realidad, no, no Cthulhu pero se puede hacer con 2 columnas, todavía estoy trabajando en la versión de una sola columna. PBIX se adjunta debajo de sig, es tabla (13).
Cycle Change = VAR __Table = FILTER('Table (13)',[device]=EARLIER([device]) && [time]<=EARLIER([Time])) VAR __Previous = MAXX(FILTER(__Table,[time]<EARLIER([Time])),[Time]) VAR __PreviousState = MAXX(FILTER(__Table,[Time]=__Previous),[State]) RETURN IF(([State]=1 && __PreviousState<>1),1,0) Cycles = SUMX(FILTER('Table (13)',[device]=EARLIER([device]) && [Time]<=EARLIER([Time])),[Cycle Change])OK, metí esto en una sola columna:
Single Column non working = VAR __BaseTable = 'Table (13)' VAR __Table = ADDCOLUMNS( ADDCOLUMNS( ADDCOLUMNS( FILTER(__BaseTable,[device]=EARLIER([device]) && [time]<=EARLIER([Time])), "__Previous",MAXX(FILTER(__BaseTable,[time]<EARLIER([Time])),[Time]) ), "__PreviousState",MAXX(FILTER(__BaseTable,[Time]=[__Previous]),[State]) ), "__CycleChange",IF(([State]=1 && [__PreviousState]<>1),1,0) ) RETURN SUMX(__Table,[__CycleChange])Se ha actualizado el PBIX.
11 Replies
- Greg_Deckler
Community Champion
@JoeJoe666 - Ah, quieres Cthulhu - https://community.powerbi.com/t5/Quick-Measures-Gallery/Cthulhu/m-p/509739#M211
En realidad, no, no Cthulhu pero se puede hacer con 2 columnas, todavía estoy trabajando en la versión de una sola columna. PBIX se adjunta debajo de sig, es tabla (13).
Cycle Change = VAR __Table = FILTER('Table (13)',[device]=EARLIER([device]) && [time]<=EARLIER([Time])) VAR __Previous = MAXX(FILTER(__Table,[time]<EARLIER([Time])),[Time]) VAR __PreviousState = MAXX(FILTER(__Table,[Time]=__Previous),[State]) RETURN IF(([State]=1 && __PreviousState<>1),1,0) Cycles = SUMX(FILTER('Table (13)',[device]=EARLIER([device]) && [Time]<=EARLIER([Time])),[Cycle Change])OK, metí esto en una sola columna:
Single Column non working = VAR __BaseTable = 'Table (13)' VAR __Table = ADDCOLUMNS( ADDCOLUMNS( ADDCOLUMNS( FILTER(__BaseTable,[device]=EARLIER([device]) && [time]<=EARLIER([Time])), "__Previous",MAXX(FILTER(__BaseTable,[time]<EARLIER([Time])),[Time]) ), "__PreviousState",MAXX(FILTER(__BaseTable,[Time]=[__Previous]),[State]) ), "__CycleChange",IF(([State]=1 && [__PreviousState]<>1),1,0) ) RETURN SUMX(__Table,[__CycleChange])Se ha actualizado el PBIX.
- JoeJoe666Frequent Visitor
Muchas gracias. No habría hecho nada de esto.
Mis datos tienen más de 400.000 filas. Intenté esto y Power BI sigue diciendo "trabajar en él" y luego 10-15 minutos más tarde dice "No hay suficiente memoria para completar esta operación. Por favor, intente esto más tarde..." Tengo 32 gb de memoria.
- daxer-almighty
Solution Sage
Aquí está el código M para hacerlo:
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 [Time = _t, device = _t, m1 = _t, m2 = _t, m3 = _t, State = _t, Cycles = _t]), #"Changed Type" = Table.TransformColumnTypes(Source,{{"Time", type datetime}, {"device", Int64.Type}, {"m1", type number}, {"m2", type number}, {"m3", type number}, {"State", Int64.Type}, {"Cycles", Int64.Type}}), #"Removed Columns" = Table.RemoveColumns(#"Changed Type",{"Cycles"}), #"Sorted Rows" = Table.Sort(#"Removed Columns",{{"device", Order.Ascending}, {"Time", Order.Ascending}}), #"Added Index" = Table.AddIndexColumn(#"Sorted Rows", "Index", 0, 1, Int64.Type), #"Reordered Columns" = Table.ReorderColumns(#"Added Index",{"Index", "Time", "device", "m1", "m2", "m3", "State"}), #"Added Custom" = Table.AddColumn(#"Reordered Columns", "PrevState", each let PrevRowState = List.SingleOrDefault( Table.SelectRows(#"Reordered Columns", (r) => r[Index] = [Index] - 1 and r[device] = [device])[State], null ) in PrevRowState ), #"Added Custom1" = Table.AddColumn(#"Added Custom", "ShouldAddOne", each if [PrevState] is null or ([PrevState] <> 1 and [State] = 1) then 1 else 0 ), #"Added Custom2" = Table.AddColumn(#"Added Custom1", "Cycle", each // this is just a cumulative sum of ShouldAddOne List.Sum( Table.SelectRows(#"Added Custom1", (r) => r[Index] <= [Index] and r[device] = [device] )[ShouldAddOne] ) ), #"Removed Columns1" = Table.RemoveColumns(#"Added Custom2",{"PrevState", "ShouldAddOne"}) in #"Removed Columns1"- JoeJoe666Frequent Visitor
@daxer todopoderoso Gracias. Sin embargo, no estoy seguro de cómo copiar pegar esto en M. Trataré de aprender y probarlo. La solución DAX funciona pero no funcionó para mí debido a más de 400.000 partidas individuales. ¿Esto me daría el mismo error de memoria?
- Greg_Deckler
Community Champion
@JoeJoe666 - Aquí hay una mejora en el modelo que con suerte ayudará, me perdí un filtro. Déjame ver qué otros trucos puedo hacer para obtener un cálculo más optimizado pero prueba esto mientras tanto. Hay mucho que hacer con esta cosa, no es bonito lo que estás tratando de lograr. Para la solución Power Query, abra Advanced Editor y pegue el código, pero puede ser un poco peludo si nunca lo ha hecho antes. Además, el enfoque de 2 columnas debe ser mucho menos procesamiento.
Cycles Count Column = VAR __BaseTable = 'Table' VAR __Time = [Time] VAR __device = [device] VAR __Table = ADDCOLUMNS( ADDCOLUMNS( ADDCOLUMNS( FILTER(__BaseTable,[device]=__device && [time]<=__Time), "__Previous",MAXX(FILTER(__BaseTable,[device]=__device && [time]<EARLIER([Time])),[Time]) ), "__PreviousState",MAXX(FILTER(__BaseTable,[device]=__device && [Time]=[__Previous]),[State]) ), "__CycleChange",IF(([State]=1 && [__PreviousState]<>1),1,0) ) RETURN SUMX(__Table,[__CycleChange])
- Greg_Deckler
Community Champion
@JoeJoe666 - En caso de que te lo perdiste, actualicé mi respuesta original con una solución DAX. Soluciones de dos columnas y de una sola columna.