The ultimate Fabric, Power BI, SQL, and AI community-led learning event. Save €200 with code FABCOMM.
Get registeredCompete to become Power BI Data Viz World Champion! First round ends August 18th. Get started.
Table for Copy Below:
id_transaction | date_hour | channel | campaign |
41564584 | 202201051122 | camp1 | |
41564584 | 202201051123 | camp2 | |
41564584 | 202201071122 | tiktok | camp3 |
41564584 | 202201061122 | affiliate | camp4 |
41564584 | 202201051129 | camp5 | |
44544545 | 202201051122 | camp6 | |
54546546 | 202201051122 | tiktok | camp7 |
45424545 | 202201051122 | affiliate | camp8 |
45457877 | 202201051122 | camp9 | |
45457877 | 202201051221 | tiktok | camp9 |
Solved! Go to Solution.
Hi,
you can try to apply these transformations:
let
Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("hc/BCoMwDIDhd+nZg4lJW59FPFSxUnR0h74/y2YdrK4b5NDAR/g7DIqANbEl1ShsEVtoGQBR1jXGdV/kMbvbHdTY1HAnq3fzMsW4ZY4VbvLtFLb0xl0F64yd92EPLp0t9KOlL8P5wMTP4esvi3D94iJJy1z5R7g5bjPh99tluD09G2vM35a+yhGhbBE8PgA=", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [id_transaction = _t, date_hour = _t, channel = _t, campaign = _t]),
#"Added Index" = Table.AddIndexColumn(Source, "Index", 1, 1, Int64.Type),
#"Grouped Rows" = Table.Group(#"Added Index", {"id_transaction"}, {{"MinIndex", each List.Min([Index]), type number}, {"AllRows", each _, type table [id_transaction=nullable text, date_hour=nullable text, channel=nullable text, campaign=nullable text, Index=number]}}),
#"Expanded AllRows" = Table.ExpandTableColumn(#"Grouped Rows", "AllRows", {"date_hour", "channel", "campaign", "Index"}, {"AllRows.date_hour", "AllRows.channel", "AllRows.campaign", "AllRows.Index"}),
#"Added Conditional Column" = Table.AddColumn(#"Expanded AllRows", "Custom", each if [MinIndex] = [AllRows.Index] then 1 else 0),
#"Filtered Rows" = Table.SelectRows(#"Added Conditional Column", each ([Custom] = 1)),
#"Removed Columns" = Table.RemoveColumns(#"Filtered Rows",{"MinIndex", "AllRows.Index", "Custom"})
in
#"Removed Columns"
It function but i think there is a problem in your exemple:
the third row on 07 january 2022 is "most recent" respect the first row on 05 jan 2022.
In that case you need some more transformations
If this post is useful to help you to solve your issue consider giving the post a thumbs up
and accepting it as a solution !
Hi,
you can try to apply these transformations:
let
Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("hc/BCoMwDIDhd+nZg4lJW59FPFSxUnR0h74/y2YdrK4b5NDAR/g7DIqANbEl1ShsEVtoGQBR1jXGdV/kMbvbHdTY1HAnq3fzMsW4ZY4VbvLtFLb0xl0F64yd92EPLp0t9KOlL8P5wMTP4esvi3D94iJJy1z5R7g5bjPh99tluD09G2vM35a+yhGhbBE8PgA=", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [id_transaction = _t, date_hour = _t, channel = _t, campaign = _t]),
#"Added Index" = Table.AddIndexColumn(Source, "Index", 1, 1, Int64.Type),
#"Grouped Rows" = Table.Group(#"Added Index", {"id_transaction"}, {{"MinIndex", each List.Min([Index]), type number}, {"AllRows", each _, type table [id_transaction=nullable text, date_hour=nullable text, channel=nullable text, campaign=nullable text, Index=number]}}),
#"Expanded AllRows" = Table.ExpandTableColumn(#"Grouped Rows", "AllRows", {"date_hour", "channel", "campaign", "Index"}, {"AllRows.date_hour", "AllRows.channel", "AllRows.campaign", "AllRows.Index"}),
#"Added Conditional Column" = Table.AddColumn(#"Expanded AllRows", "Custom", each if [MinIndex] = [AllRows.Index] then 1 else 0),
#"Filtered Rows" = Table.SelectRows(#"Added Conditional Column", each ([Custom] = 1)),
#"Removed Columns" = Table.RemoveColumns(#"Filtered Rows",{"MinIndex", "AllRows.Index", "Custom"})
in
#"Removed Columns"
It function but i think there is a problem in your exemple:
the third row on 07 january 2022 is "most recent" respect the first row on 05 jan 2022.
In that case you need some more transformations
If this post is useful to help you to solve your issue consider giving the post a thumbs up
and accepting it as a solution !