Power BI 中的按类别索引相当于分区上的 SQL row_number

Question

如何在Power BI的M中按类别添加索引并按列排序。我寻找相当于 SQL:

ROW_NUMBER() over(partition by [Category] order by [Date] desc

假设我们有一个 table:

+----------+-------+------------+
| Category | Value |    Date    |
+----------+-------+------------+
| apples   |     3 | 2018-07-01 |
| apples   |     2 | 2018-07-02 |
| apples   |     1 | 2018-07-03 |
| bananas  |     9 | 2018-07-01 |
| bananas  |     8 | 2018-07-02 |
| bananas  |     7 | 2018-07-03 |
+----------+-------+------------+

期望的结果是：

+----------+-------+------------+-------------------+
| Category | Value |    Date    | Index by category |
+----------+-------+------------+-------------------+
| apples   |     3 | 2018-07-01 |                 3 |
| apples   |     2 | 2018-07-02 |                 2 |
| apples   |     1 | 2018-07-03 |                 1 |
| bananas  |     9 | 2018-07-01 |                 3 |
| bananas  |     8 | 2018-07-02 |                 2 |
| bananas  |     7 | 2018-07-03 |                 1 |
+----------+-------+------------+-------------------+

table 的 PBI 代码：

let
    Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45WSiwoyEktVtJRMgRiIwNDC10Dc10DQ6VYHSQ5I2Q5I1Q5Y2Q5Y7BcUmIeEIIkzZElTdAkLZAlTdEkLZElzZRiYwE=", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type text) meta [Serialized.Text = true]) in type table [Category = _t, Value = _t, Date = _t])
in
    Source

Answer 1

@FoxanNg 提供的 link 为此工作。这是您需要的 M 代码：

let
    Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45WSiwoyEktVtJRMgRiIwNDC10Dc10DQ6VYHSQ5I2Q5I1Q5Y2Q5Y7BcUmIeEIIkzZElTdAkLZAlTdEkLZElzZRiYwE=", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type text) meta [Serialized.Text = true]) in type table [Category = _t, Value = _t, Date = _t]),
    AddRanking = (table, column, newColumn) =>
        Table.AddIndexColumn(Table.Sort(table, {{column, Order.Descending}}), newColumn, 1, 1),
    #"Grouped Rows" = Table.Group(Source, {"Category"}, {{"Data", each _, type table}}),
    Transformed = Table.TransformColumns(#"Grouped Rows", {{"Data", each AddRanking(_, "Date", "Rank")}}),
    #"Expand Data" = Table.ExpandTableColumn(Transformed, "Data", {"Value", "Date", "Rank"}, {"Value", "Date", "Rank"})
in
    #"Expand Data"

Answer 2

感谢 Foxan Ng 和 Alexis Olson，感谢您提供有趣的 PBI 函数方法。我想在集合中添加其他方法。

PBI 方法，无功能：

let
    Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45WSiwoyEktVtJRMgRiIwNDC10Dc10DQ6VYHSQ5I2Q5I1Q5Y2Q5Y7BcUmIeEIIkzZElTdAkLZAlTdEkLZElzZRiYwE=", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type text) meta [Serialized.Text = true]) in type table [Category = _t, Value = _t, Date = _t]),
    #"Grouped rows" = Table.Group(Source, {"Category"}, {{"NiceTable", each Table.AddIndexColumn(Table.Sort(_,{{"Date", Order.Descending}} ), "Index",1,1), type table}} ),
    #"Expanded NiceTable" = Table.ExpandTableColumn(#"Grouped rows", "NiceTable", {"Value", "Date", "Index"}, {"Value", "Date", "Index"})
in
    #"Expanded NiceTable"

此解决方案的灵感来自此处的 ImkeF 解释：https://community.powerbi.com/t5/Desktop/Custom-column-Index-or-Ranking-by-other-column/td-p/33864/page/3

这是我最喜欢的 R 方法。需要 dplyr 包。我喜欢它的简单性。

let
    Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45WSiwoyEktVtJRMgRiIwNDC10Dc10DQ6VYHSQ5I2Q5I1Q5Y2Q5Y7BcUmIeEIIkzZElTdAkLZAlTdEkLZElzZRiYwE=", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type text) meta [Serialized.Text = true]) in type table [Category = _t, Value = _t, Date = _t]),
    #"Run R Script" = R.Execute("library(dplyr)#(lf)output <- dataset %>% group_by(Category) %>% mutate(row_no_by_category = row_number(desc(Date)))",[dataset=Source]),
    output = #"Run R Script"{[Name="output"]}[Value]
in
    output

Power BI 中的按类别索引相当于分区上的 SQL row_number

Index by category in Power BI equivalent to SQL row_number over partition

m

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