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Anonymous's avatar
Anonymous
Not applicable
5 years ago
Solved

Comparing datetimezones to group table by condition

Hi I´m trying to compare two datetimezones from different columns on same table in order to determine how many row does that set have per ID. I have this data

 

IDDateTimeZone 1DateTimeZone 2
12021-05-28T09:00:56.6630000-05:002021-06-03T08:52:39.6570000-05:00
12021-05-28T09:00:56.6630000-05:002021-05-27T08:52:39.6570000-05:00
22021-02-01T15:53:56.0860000-05:002021-02-02T15:53:56.0860000-05:00
22021-02-01T15:53:56.0860000-05:002021-02-03T15:53:56.0860000-05:00
22021-02-01T15:53:56.0860000-05:002021-02-04T15:53:56.0860000-05:00
32021-02-01T15:53:56.0860000-05:002021-01-29T15:53:56.0860000-05:00
42020-10-15T19:07:57.8600000-05:002020-10-16T19:07:57.8600000-05:00
42020-10-15T19:07:57.8600000-05:002020-10-14T19:07:57.8600000-05:00
42020-10-15T19:07:57.8600000-05:002020-10-17T19:07:57.8600000-05:00

 

So 

Set 1 (DateTimeZone 1 < DateTimeZone 2)

IDDateTimeZone 1DateTimeZone 2
12021-05-28T09:00:56.6630000-05:002021-06-03T08:52:39.6570000-05:00
22021-02-01T15:53:56.0860000-05:002021-02-02T15:53:56.0860000-05:00
22021-02-01T15:53:56.0860000-05:002021-02-03T15:53:56.0860000-05:00
22021-02-01T15:53:56.0860000-05:002021-02-04T15:53:56.0860000-05:00
42020-10-15T19:07:57.8600000-05:002020-10-16T19:07:57.8600000-05:00
42020-10-15T19:07:57.8600000-05:002020-10-17T19:07:57.8600000-05:00

 

Set 2 (DateTimeZone 2< DateTimeZone 1 )

IDDateTimeZone 1DateTimeZone 2
12021-05-28T09:00:56.6630000-05:002021-05-27T08:52:39.6570000-05:00
32021-02-01T15:53:56.0860000-05:002021-01-29T15:53:56.0860000-05:00
42020-10-15T19:07:57.8600000-05:002020-10-14T19:07:57.8600000-05:00

 

So what I want to get is

Set 2

IDDateTimeZone 2< DateTimeZone 1DateTimeZone 2 > DateTimeZone 1
111
203
310
412

 

Thanks, 

 

Any help or suggestion would be really appreciated

 

Julio

 

 

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  • AlB's avatar
    AlB
    5 years ago

    Anonymous 

    So you want to do it in PQ? Place the following M code in a blank query to see the steps.

    let
    Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("rdFJCsMwDEDRu2QdGQ2WPJzDu5D7XyNKDaGFuqEmRtqIz9t42xZa1tcyMgEqcG5YKmJVC2aC/vzsh6sxQGmYq3KVEkzTW7OvM6I36U7kq2ZAaqRV5RQx2xfRGx4106I8LsZf4qnJXyIBlzsx9hqBfLSR/0yqmkKPP8Te2KiZFuPjYhqK+wE=", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [ID1 = _t, ID2 = _t, #"DateTimeZone 1" = _t, #"DateTimeZone 2" = _t]),
    #"Changed Type" = Table.TransformColumnTypes(Source,{{"ID1", Int64.Type}, {"ID2", Int64.Type}, {"DateTimeZone 1", type datetimezone}, {"DateTimeZone 2", type datetimezone}}),
    #"Grouped Rows" = Table.Group(#"Changed Type", {"ID1", "ID2"}, {{"DateTimeZone 2< DateTimeZone 1", each Table.RowCount(Table.SelectRows(_, each [DateTimeZone 2]<[DateTimeZone 1]))}, {"DateTimeZone 1< DateTimeZone 2", each Table.RowCount(Table.SelectRows(_, each [DateTimeZone 1]<[DateTimeZone 2]))}}),
    #"Changed Type1" = Table.TransformColumnTypes(#"Grouped Rows",{{"DateTimeZone 2< DateTimeZone 1", Int64.Type}, {"DateTimeZone 1< DateTimeZone 2", Int64.Type}})
in
    #"Changed Type1"

    		 Please accept the solution when done and consider giving a thumbs up if posts are helpful. 

    Contact me privately for support with any larger-scale BI needs, tutoring, etc.

     

4 Replies

  • AlB's avatar
    AlB
    Community Champion
    5 years ago

    Anonymous 

    So you want to do it in PQ? Place the following M code in a blank query to see the steps.

    let
    Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("rdFJCsMwDEDRu2QdGQ2WPJzDu5D7XyNKDaGFuqEmRtqIz9t42xZa1tcyMgEqcG5YKmJVC2aC/vzsh6sxQGmYq3KVEkzTW7OvM6I36U7kq2ZAaqRV5RQx2xfRGx4106I8LsZf4qnJXyIBlzsx9hqBfLSR/0yqmkKPP8Te2KiZFuPjYhqK+wE=", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [ID1 = _t, ID2 = _t, #"DateTimeZone 1" = _t, #"DateTimeZone 2" = _t]),
    #"Changed Type" = Table.TransformColumnTypes(Source,{{"ID1", Int64.Type}, {"ID2", Int64.Type}, {"DateTimeZone 1", type datetimezone}, {"DateTimeZone 2", type datetimezone}}),
    #"Grouped Rows" = Table.Group(#"Changed Type", {"ID1", "ID2"}, {{"DateTimeZone 2< DateTimeZone 1", each Table.RowCount(Table.SelectRows(_, each [DateTimeZone 2]<[DateTimeZone 1]))}, {"DateTimeZone 1< DateTimeZone 2", each Table.RowCount(Table.SelectRows(_, each [DateTimeZone 1]<[DateTimeZone 2]))}}),
    #"Changed Type1" = Table.TransformColumnTypes(#"Grouped Rows",{{"DateTimeZone 2< DateTimeZone 1", Int64.Type}, {"DateTimeZone 1< DateTimeZone 2", Int64.Type}})
in
    #"Changed Type1"

    		 Please accept the solution when done and consider giving a thumbs up if posts are helpful. 

    Contact me privately for support with any larger-scale BI needs, tutoring, etc.

     

    • Anonymous's avatar
      Anonymous
      Not applicable
      5 years ago

      Thank you so much!

  • AlB's avatar
    AlB
    Community Champion
    5 years ago

    Hi Anonymous 

    1. Place Table1[Id] in a table visual. Make sure it is set to "Don't summarize"

    2. Add these measures to the visual

    DTZ1<DTZ2 = 
COUNTROWS(FILTER(Table1, Table1[DateTimeZone 2] < Table1[DateTimeZone 1])) + 0
    DTZ2<DTZ1 = 
COUNTROWS ( FILTER ( Table1, Table1[DateTimeZone 1] < Table1[DateTimeZone 2] ) ) + 0

     

    		 Please accept the solution when done and consider giving a thumbs up if posts are helpful. 

    Contact me privately for support with any larger-scale BI needs, tutoring, etc.

     

  • Anonymous's avatar
    Anonymous
    Not applicable
    5 years ago

    Thanks for the response AlB . And sorry for the misleading first example of data I tried your solution and create a visual table but is not grouping the results. Its making the count but is assigned to every row of the visual table. And I want to the count its made grouping by ID. Perhaps another option could be making it on code with the Table. Group command but I don´t know how to do it exactly. 

     

    I get to something like this.

     

    ID1ID2DateTimeZone 1DateTimeZone 2
    112021-05-28T09:00:56.6630000-05:002021-06-03T08:52:39.6570000-05:00
    112021-05-28T09:00:56.6630000-05:002021-05-27T08:52:39.6570000-05:00
    122021-02-01T15:53:56.0860000-05:002021-02-02T15:53:56.0860000-05:00
    122021-02-01T15:53:56.0860000-05:002021-02-03T15:53:56.0860000-05:00
    122021-02-01T15:53:56.0860000-05:002021-02-04T15:53:56.0860000-05:00
    232021-02-01T15:53:56.0860000-05:002021-01-29T15:53:56.0860000-05:00
    242020-10-15T19:07:57.8600000-05:002020-10-16T19:07:57.8600000-05:00
    242020-10-15T19:07:57.8600000-05:002020-10-14T19:07:57.8600000-05:00
    242020-10-15T19:07:57.8600000-05:002020-10-17T19:07:57.8600000-05:00

     

    So what I want to achieve is this

     

    ID1ID2DateTimeZone 2< DateTimeZone 1DateTimeZone 2 > DateTimeZone 1
    1111
    1203
    2310
    2412

     

     

    But I dont know hot make the grouping by two columns and accesing correctly to datimezone data

     

     

     

    Table.Group(Table1, {"ID1","ID2"}, {"DT2>DT1", each Table.RowCount(Table.SelectRows(Table1,[DateTimeZone2]>[DateTimeZone1]))})

     

     

     

     

    Thanks for your help. Maybe I need another approach

    Julio