当然可以。以下是如何在 Power Query 中执行此操作的示例 M 代码:
let
Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("ndKxCoMwEAbgd8ksohdN5y527VDoIA5BQwnYCufSx28oKZHmzqQdJEL4uPvv0vcCoDyUUEElCnExT726s3bf1aKZ3Hm8G7Sjdn/yfTMUtAHSNKQ5mQVvVrOV2oT6r5b0ajbrmlHurNF+B+tQP0bj++aJzCfdvKCdtqGi9iAB2Vz0wgJsyDFu+qz5pxEV22dsuH0myQ4lacKi2x9yBaVIBaSKt5bTYbwy9tmT6pMrGqJKQMVBP5PhBQ==", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [Date = _t, Name = _t, Code = _t, #"Connection Type" = _t, Country = _t, Calls = _t, Invalid = _t]),
#"Changed Type" = Table.TransformColumnTypes(Source,{{"Date", type date}, {"Name", type text}, {"Code", type text}, {"Connection Type", type text}, {"Country", type text}, {"Calls", Int64.Type}, {"Invalid", Int64.Type}}),
#"Removed Columns" = Table.RemoveColumns(#"Changed Type",{"Code"}),
#"Grouped Rows" = Table.Group(#"Removed Columns", {"Date", "Name", "Connection Type", "Country"}, {{"Calls", each List.Sum([Calls]), type text}, {"Invalid", each List.Sum([Invalid]), type text}})
in
#"Grouped Rows"
Table.RemoveColumns 将删除Code 列,Table.Group 将对指定列(Date、Name、Connection Type 和Country)上的数据进行分组并聚合数据,在此求和案例(Calls 和 Invalid)。
您只能使用 UI 来执行此操作。在 Power Query 编辑器中,右键单击 Code 列的标题并选择 Remove。然后从Transform标签点击最左边的按钮Group By并填写如下: