Forum Discussion
Pivot unpivot Timestamp Values
- 1 year ago
Hi Anonymous ,
Try the following code:
let Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45WMtY3NNY3MjAyVTA0sjIwACKFAF8lHSXn/NyCxLxKQyDTQM9IKVaHVkqNkJWamGJXakq0UkyFpsSbianUCEkpkqdw+olUlUbIKnE4FCOcCKhEtt2IaB/hURkLAA==", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [Date = _t, Company = _t, Value = _t]), #"Changed Type with Locale" = Table.TransformColumnTypes(Source, {{"Date", type datetime}, {"Value", type number}}, "en-us"), #"Grouped Rows" = Table.Group(#"Changed Type with Locale", {"Date"}, {{"Count", each _, type table [Date=nullable datetime, Company=nullable text, Value=nullable number]}}), #"Added Custom" = Table.AddColumn(#"Grouped Rows", "Custom", each Table.AddIndexColumn ( [Count], "Index",1)), #"Expanded Custom" = Table.ExpandTableColumn(#"Added Custom", "Custom", {"Company", "Value", "Index"}, {"Custom.Company", "Custom.Value", "Custom.Index"}), #"Removed Columns" = Table.RemoveColumns(#"Expanded Custom",{"Count"}), #"Grouped Rows1" = Table.Group(#"Removed Columns", {"Date", "Custom.Index"}, {{"Count", each _, type table [Date=nullable datetime, Custom.Company=text, Custom.Value=number, Custom.Index=number]}}), #"Pivoted Column" = Table.Pivot(Table.TransformColumnTypes(#"Grouped Rows1", {{"Date", type text}}, "pt-PT"), List.Distinct(Table.TransformColumnTypes(#"Grouped Rows1", {{"Date", type text}}, "pt-PT")[Date]), "Date", "Count"), #"Added Custom1" = Table.AddColumn(#"Pivoted Column", "Custom", each Table.FromColumns( (try Table.ToColumns([#"13/03/2025 12:00:00"]) otherwise Table.ToColumns( #table({"Date"}, {{null}}))) & (try Table.ToColumns([#"13/02/2025 12:45:00"]) otherwise Table.ToColumns( #table({"Date"}, {{null}}))) & (try Table.ToColumns([#"13/02/2025 12:55:00"]) otherwise Table.ToColumns( #table({"Date"}, {{null}}))) & (try Table.ToColumns([#"13/03/2025 13:00:00"]) otherwise Table.ToColumns( #table({"Date"}, {{null}}))) & (try Table.ToColumns([#"13/03/2025 13:25:00"]) otherwise Table.ToColumns( #table({"Date"}, {{null}}))) & (try Table.ToColumns([#"13/02/2025 13:05:00"]) otherwise Table.ToColumns( #table({"Date"}, {{null}}))) )), #"Removed Columns1" = Table.RemoveColumns(#"Added Custom1",{"13/03/2025 12:00:00", "13/02/2025 12:45:00", "13/02/2025 12:55:00", "13/03/2025 13:00:00", "13/02/2025 13:05:00", "13/03/2025 13:25:00"}), #"Expanded Custom1" = Table.ExpandTableColumn(#"Removed Columns1", "Custom", {"Column1", "Column2", "Column3", "Column4", "Column5", "Column6", "Column7", "Column8", "Column9", "Column10", "Column11", "Column12", "Column13", "Column14", "Column15", "Column16", "Column17", "Column18", "Column19", "Column20", "Column21", "Column22", "Column23", "Column24"}, {"Column1", "Column2", "Column3", "Column4", "Column5", "Column6", "Column7", "Column8", "Column9", "Column10", "Column11", "Column12", "Column13", "Column14", "Column15", "Column16", "Column17", "Column18", "Column19", "Column20", "Column21", "Column22", "Column23", "Column24"}), #"Removed Columns2" = Table.RemoveColumns(#"Expanded Custom1",{"Column4", "Column8", "Column12", "Column16", "Column20", "Column24"}) in #"Removed Columns2"What I'm doing is the following:
- Grouping by the date columns you need
- Adding and index for each of the date/times
- Expanding the index for that group
- Regrouping based on the date and the index
- Making a pivot based on the date
- Adding a custom step to join all the columns of the dates
- Removing the index columns
Once again be carefull because with different dates this will mean that the combination of the steps are not automatic and you need to redo them.
See file attach.
Hi Anonymous ,
For this I suggest to have a calculation and not a pivot of the columns.
Can you please let me know what is that OK/NOK will be based on? I can try and tell you how to use that calculation. It can be done either in DAX or Power Query.
MFelix thank you for helping, So here, the condition I want in PBI Desktop is if Value for 12 pm =1 pm = 2pm then ok else not ok and for this condition the table has to be in converted in this format in PQ
| Date | Company | Value | Date | Company | Value |
| 3/13/2025 12:00:00 PM | Company1 | 0.2 | 3/13/2025 1:00:00 PM | Company1 | 0.5 |
| 3/13/2025 12:00:00 PM | Company1 | 0.2 | 3/13/2025 1:00:00 PM | Company2 | 1.5 |
- MFelix1 year agoSuper User
Hi Anonymous ,
Just a quick follow up you have in the data 12PM but also 12:45 PM or 12:55 when this happens are you comparing 13:45 to 12:45 or everything is consider 12?
How do you handle that part of the data
- Anonymous1 year agoNot applicable
MFelix Raw data will have that data but we need to just filter only 12:00, 1:00, 2:00