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I have a bit complicated PowerQuery query which has many steps. Within these steps I have a date, team and conditions as below (not actual data)
So the challenge is that I want to count the Pass number for each team for each day and then create another count for Pass and Fail and then it will be used in so many calculations which I can handle later.
I have tried many options, like for example grouping, but it was so confusing because as I mentioned before, the query has so many columns and calculations now. I could successfully solve the issue by creating DAX measure, but the issue here that I need to calculate the average outcome which is not possible to because I couldn't also average the measure of the outcome. So I have no other option but to make the countif though PowerQuery.
Appreciate your help and ideas.
Raw data as text is here in google sheets
I am assuming that your dates showing the year 0203 is a typo and should be 2023
Not sure exactly what you want for output, but you should be able to adapt the below.
The solution seems to be a simple grouping with a count of the number of passes and/or fails.
The below code generates a separate column for passes and fails per team and date.
It is not sorted in the original order, but that could be added if necessary.
#"Grouped Rows" = Table.Group(#"Previous Step", {"Date", "Team"}, {
{"Pass", (t)=>List.Count(List.Select(t[#"PASS/FAIL"], each _ = "Pass")), Int64.Type},
{"Fail", (t)=>List.Count(List.Select(t[#"PASS/FAIL"], each _ = "Fail")), Int64.Type}
})
Using your data table from the Google sheet (after correcting the year):
let
Source = Excel.CurrentWorkbook(){[Name="Table12"]}[Content],
#"Changed Type" = Table.TransformColumnTypes(Source,{{"Date", type date}, {"Team", type text}, {"PASS/FAIL", type text}}),
#"Grouped Rows" = Table.Group(#"Changed Type", {"Date", "Team"}, {
{"Pass", (t)=>List.Count(List.Select(t[#"PASS/FAIL"], each _ = "Pass")), Int64.Type},
{"Fail", (t)=>List.Count(List.Select(t[#"PASS/FAIL"], each _ = "Fail")), Int64.Type}
})
in
#"Grouped Rows"
Note If you require that all teams show on all dates even if they didn't play, one merely creates a new table containing all dates and teams; and then Joins that to the original table, as in the code below:
let
Source = Excel.CurrentWorkbook(){[Name="Table12"]}[Content],
#"Changed Type" = Table.TransformColumnTypes(Source,{{"Date", type date}, {"Team", type text}, {"PASS/FAIL", type text}}),
//If you need to show all teams on all dates, even if they didn't play on a date
//we merely create a blank table (dates and teams), and execute an outer join.
//then remove the original date/team columns before the grouping.
#"Date List" = List.Distinct(#"Changed Type"[Date]),
#"All Teams" = List.Distinct(#"Changed Type"[Team]),
Blank = Table.FromColumns(
{List.Combine(List.Transform(#"Date List", each List.Repeat({_}, List.Count(#"All Teams")))),
List.Repeat(#"All Teams", List.Count(#"Date List"))},
type table[dates=date, teams=text]),
join = Table.Join(Blank,{"dates","teams"}, #"Changed Type",{"Date","Team"}, JoinKind.LeftOuter),
#"Removed Columns" = Table.RemoveColumns(join,{"Date", "Team"}),
#"Grouped Rows" = Table.Group(#"Removed Columns", {"dates", "teams"}, {
{"Pass", (t)=>List.Count(List.Select(t[#"PASS/FAIL"], each _ = "Pass")), Int64.Type},
{"Fail", (t)=>List.Count(List.Select(t[#"PASS/FAIL"], each _ = "Fail")), Int64.Type}
}),
#"Sorted Rows" = Table.Sort(#"Grouped Rows",{{"dates", Order.Ascending}, {"teams", Order.Ascending}})
in
#"Sorted Rows"
If you need the zeroes in your final output, you'll need to do a cross join to bring in combinations not present in the original.
let
Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45WMtQ31DcyMDJW0lFyDAISAYnFxUqxOigSrn44JFxcgYRbYmYOuoSfD7KEkb4RilEkSeA0Cr8E3LlIEmDnEpYw1jfWNzAywDSKIgmcduCUQI0PJAnU+CDGKNSwotwOiFGxAA==", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [Date = _t, Team = _t, #"PASS/FAIL" = _t]),
#"Changed Type" = Table.TransformColumnTypes(Source,{{"Date", type text}, {"Team", type text}, {"PASS/FAIL", type text}}),
#"Grouped Rows" = Table.Group(#"Changed Type", {"Date", "Team"}, {{"Count", each Table.RowCount(_), Int64.Type}}),
Custom1 = List.Distinct( #"Grouped Rows"[Date]),
#"Converted to Table" = Table.FromList(Custom1, Splitter.SplitByNothing(), {"Date"}, null, ExtraValues.Error),
#"Added Custom" = Table.AddColumn(#"Converted to Table", "Team", each List.Distinct( #"Grouped Rows"[Team])),
#"Expanded Team" = Table.ExpandListColumn(#"Added Custom", "Team"),
#"Merged Queries" = Table.NestedJoin(#"Expanded Team", {"Date", "Team"}, #"Grouped Rows", {"Date", "Team"}, "Expanded Team", JoinKind.LeftOuter),
#"Expanded Expanded Team" = Table.ExpandTableColumn(#"Merged Queries", "Expanded Team", {"Count"}, {"Count"}),
#"Replaced Value" = Table.ReplaceValue(#"Expanded Expanded Team",null,0,Replacer.ReplaceValue,{"Count"})
in
#"Replaced Value"
Stepping through the code:
Group by date and team and create a count:
Get a distinct list of dates
Convert to table
Add column for a cross join with all teams (to get zero values later)
Expand
Merge back to the grouped step to pull in the previous grouped values.
Replace nulls with 0
You can amend this for your other question by simply filtering for pass before you do the grouping.
Just add column, custom column
= 1
then click select Pass/Fail column, transform .. pivot .. and choose the new column as values column
let Source = Excel.CurrentWorkbook(){[Name="Table1"]}[Content],
#"Added Custom" = Table.AddColumn(Source, "Custom", each 1),
#"Pivoted Column" = Table.Pivot(#"Added Custom", List.Distinct(#"Added Custom"[PassFail]), "PassFail", "Custom", List.Sum)
in #"Pivoted Column"
I want to move the data from one column which has distinct values in rows but the other column has same values in rows as shown in the pitcure.
I am new to power BI, can someone please help on this?
Thank you in advance
Req
You can create the following two measures - using CONCATENATEX()
Col_1 = CONCATENATEX(Your_Table,Your_Table[Col1]&";")
Col_2 = CONCATENATEX(Your_Table,Your_Table[Col2]&";")
In Power BI, you can perform some Transformation in Power Query Editor to achieve your required output.
Let, your table structure and sample data looks as below-
Now, go to Advanced Editor for your table and replace the code with this below code-
let
Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("PcdJDoAgEETRu/TaSyCoKDjPEu5/Dbs0qcVP/ktJjBTitENy8avSTqrWLqrRbsprz6dSr9WMITuwJANoyQg6sgcrcgDrj1Z3BBtyAj05gy25gB25goHcwEjuYC85vw==", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [col1 = _t, col2 = _t, col3 = _t]),
#"Changed Type" = Table.TransformColumnTypes(Source,{{"col1", type text}, {"col2", type text}, {"col3", type text}}),
//--New Transformation starts from here
#"Grouped Rows" = Table.Group(#"Changed Type", {"col1"}, {{"grouped", each _, type table [col1=nullable text, col2=nullable text, col3=nullable text]}}),
#"Added Custom" = Table.AddColumn(#"Grouped Rows", "Custom", each [grouped][col2]),
#"Added Custom1" = Table.AddColumn(#"Added Custom", "Custom.1", each [grouped][col3]),
#"Extracted Values" = Table.TransformColumns(#"Added Custom1", {"Custom", each Text.Combine(List.Transform(_, Text.From), ";"), type text}),
#"Extracted Values1" = Table.TransformColumns(#"Extracted Values", {"Custom.1", each Text.Combine(List.Transform(_, Text.From), ";"), type text}),
#"Removed Columns" = Table.RemoveColumns(#"Extracted Values1",{"grouped"})
in
#"Removed Columns"
Here is the final output-
I have a performance monitoring table in which users are listed vertically and then months are listed across the header. These months are dynamically generated on a 12-month rolling window. At the beginning of each month, one month falls off the back of the query and another appears at the front. After beginning of month, I get the following error until I manually re-run the report:
The '<#MONTH>' column does not exist in the rowset.
Where '<#MONTH>' is the month that gets dropped off, e.g. if it is Sept 2019, it would be 'August 2018'.
I tried adding a window to the query that moved the start of the query ahead a day to try to eliminate the perceived race condition. This did not work.
Here is the M query I have currently:
let
Source = US_TOTALS,
#"Appended Query" = Table.SelectRows(Table.Combine({Source, CA_TOTALS}), each [DATELASTFULFILLMENT] >= #"This Year"),
#"Reordered Columns" = Table.ReorderColumns(#"Appended Query",{"SALESMAN", "RegionName", "DATELASTFULFILLMENT", "Total Sales", "Customer", "GROUP"}),
#"Inserted Start of Month" = Table.AddColumn(#"Reordered Columns", "StartOfMonth", each Date.StartOfMonth([DATELASTFULFILLMENT]), type date),
#"Reordered Columns1" = Table.ReorderColumns(#"Inserted Start of Month",{"SALESMAN", "RegionName", "DATELASTFULFILLMENT", "Total Sales", "StartOfMonth", "GROUP", "Customer"}),
#"Removed Columns" = Table.RemoveColumns(#"Reordered Columns1",{"Customer"}),
#"Date One" = Date.AddMonths(Date.StartOfMonth(Date.AddDays(DateTime.Date(DateTime.LocalNow()),1)),1),
#"Date Two" = Date.AddYears(Date.AddMonths(Date.StartOfMonth(Date.AddDays(DateTime.Date(DateTime.LocalNow()),1)),0),-1),
#"Filtered Rows" = Table.SelectRows(#"Removed Columns", each [DATELASTFULFILLMENT] < Date.AddMonths(Date.StartOfMonth(DateTime.Date(DateTime.LocalNow())),1) and [DATELASTFULFILLMENT] >= Date.AddYears(Date.AddMonths(Date.StartOfMonth(DateTime.Date(DateTime.LocalNow())),0),-1)),
//#"Filtered Rows" = Table.SelectRows(#"Removed Columns", each Date.From([DATELASTFULFILLMENT]) < #"Date One" and Date.From([DATELASTFULFILLMENT]) >= #"Date Two"),
#"Grouped Rows" = Table.Group(#"Filtered Rows", {"SALESMAN", "RegionName", "StartOfMonth", "GROUP"}, {{"Total", each List.Sum([Total Sales]), type number}}),
#"Reordered Columns2" = Table.ReorderColumns(#"Grouped Rows",{"SALESMAN", "RegionName", "GROUP", "StartOfMonth", "Total"}),
#"Inserted Month Name" = Table.AddColumn(#"Reordered Columns2", "Month Name", each Date.MonthName([StartOfMonth]), type text),
#"Inserted Year" = Table.AddColumn(#"Inserted Month Name", "Year", each Date.Year([StartOfMonth]), type number),
#"Merged Columns" = Table.CombineColumns(Table.TransformColumnTypes(#"Inserted Year", {{"Year", type text}}, "en-US"),{"Month Name", "Year"},Combiner.CombineTextByDelimiter(" ", QuoteStyle.None),"Month"),
#"Removed Columns2" = Table.RemoveColumns(#"Merged Columns",{"StartOfMonth", "GROUP"}),
#"Grouped Rows1" = Table.Group(#"Removed Columns2", {"SALESMAN", "Month", "RegionName"}, {{"Total", each List.Sum([Total]), type number}}),
#"Sorted Rows" = Table.Sort(#"Grouped Rows1",{{"SALESMAN", Order.Ascending}}),
#"Pivoted Columns" = Table.Pivot(#"Sorted Rows", List.Distinct(#"Sorted Rows"[Month]), "Month", "Total", List.Sum),
Columns = List.RemoveFirstN(Table.ColumnNames(#"Pivoted Columns"),2),
#"Replaced Value" = Table.ReplaceValue(#"Pivoted Columns",null,0,Replacer.ReplaceValue,Columns),
#"Changed Type" = Table.TransformColumnTypes(#"Replaced Value",List.Transform(Columns, each {_, Currency.Type })),
#"Merged Queries" = Table.NestedJoin(#"Changed Type",{"SALESMAN"},USER_MAPPING_COMBINED,{"USERNAME"},"USER_MAPPING_COMBINED",JoinKind.LeftOuter),
#"Expanded USER_MAPPING" = Table.ExpandTableColumn(#"Merged Queries", "USER_MAPPING_COMBINED", {"NAME"}, {"NAME"})
in
#"Expanded USER_MAPPING"
Expected Results:
The query refreshes as normal
Actual Results:
The query errors with The '<#MONTH>' column does not exist in the rowset.
Where '<#MONTH>' is the month that gets dropped off, e.g. if it is Sept 2019, it would be 'August 2018'.
screenshot for reference:
Ok, I'm going to take a second swing at this. If I'm way off base, I apologize. But let me bring out an example to simulate your error.
let
Seed = Number.Mod(Number.Round(Time.Second(DateTime.LocalNow())), 7) + 1,
Source = List.Generate(()=> Seed, each _ < Seed + 6, each _ + 1),
#"Converted to Table" = Table.FromList(Source, Splitter.SplitByNothing(), {"MonthNumbers"}, null, ExtraValues.Error),
#"Added Custom" = Table.AddColumn(#"Converted to Table", "MonthNames", each Date.MonthName(#date(2019, [MonthNumbers], 1))),
#"Pivoted Column" = Table.Pivot(#"Added Custom", List.Distinct(#"Added Custom"[MonthNames]), "MonthNames", "MonthNumbers", List.Sum)
in
#"Pivoted Column"
So, this creates a table that looks like so:
But every single second, the frame shifts by a month. So if you refresh the preview every second, you'll see the frame slide Jan-Jun, Feb-Jul, Mar-Aug... when December is the last month in the window, it skips back to the Jan-Jun. The point is, the columns are changing.
Now you try to load this model. It does not work!
From the time you create the model with one column set, to the time it takes to load the column set, those columns have been changed and so one of the columns isn't there any more. This is like when your month changes. When you go in and load manually, you'll update your model and things will work fine until the next change in columns. But when you're doing it with the scheduled load, that doesn't update the model, it just tries to load the data and runs into this column mismatch.
So, how do we fix it without losing this dynamic naming? Let's look at that pivot... what if we don't do it and leave our power query looking like this?
Now the column names won't change when we load it into the model. We create a matrix visualization like so, and do some refreshes:
No errors, nice dynamic headers.
So, that's the approach that I think you need. I hope it helps.
Edit: Per comment, this answer shows how to deal with a source that comes with changing column names over time, which is not the problem the asker has.
#RyanB is correct. The right approach here is to do your crosstab layout in reports rather than in data model. The right way, in general, to deal with things that change is to reify these as data, rather than as schema.
Original post below
You're looking for the 'Unpivot other columns' transform:
Select the columns whose names do not change.
Use 'Unpivot other columns' transform
Rename columns
Deal with months as a single month column
Make sure this comes before any steps that depend on the changing column names.
Here are two sample queries that are identical in code except for the source, which has differently named columns:
// query1
let
Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("RU85FsQgCL2LdQoWUTiLL8VkJve/QliSTKF8/oK4VsO2tY8fpLyEe1aWKm3fVgvpiF7SBNLZZulQQLrD9LK339I6mAOYpoJBo5tmUOgUYNr7YwfTiUwShA/VyL/wnufhyMRqv1oHRswTJANNBshGAWN63edNkf41j4GJvzseMn67Xw==", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type text) meta [Serialized.Text = true]) in type table [ID = _t, Somethingstatic = _t, #"May-2019" = _t, #"Jun-2019" = _t, #"Jul-2019" = _t, #"Aug-2019" = _t]),
#"Unpivoted Other Columns" = Table.UnpivotOtherColumns(Source, {"ID", "Somethingstatic"}, "Attribute", "Value"),
#"Renamed Columns" = Table.RenameColumns(#"Unpivoted Other Columns",{{"Attribute", "Month"}}),
#"Changed Type" = Table.TransformColumnTypes(#"Renamed Columns",{{"Value", Int64.Type}, {"ID", Int64.Type}})
in
#"Changed Type"
// query 2
let
Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("RU85FsQgCL2LdQoWUTiLL8VkJve/QliSTKF8/oK4VsO2tY8fpLyEe1aWKm3fVgvpiF7SBNLZZulQQLrD9LK339I6mAOYpoJBo5tmUOgUYNr7YwfTiUwShA/VyL/wnufhyMRqv1oHRswTJANNBshGAWN63edNkf41j4GJvzseMn67Xw==", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type text) meta [Serialized.Text = true]) in type table [ID = _t, Somethingstatic = _t, #"Jun-2019" = _t, #"Jul-2019" = _t, #"Aug-2019" = _t, #"Sep-2019" = _t]),
#"Unpivoted Other Columns" = Table.UnpivotOtherColumns(Source, {"ID", "Somethingstatic"}, "Attribute", "Value"),
#"Renamed Columns" = Table.RenameColumns(#"Unpivoted Other Columns",{{"Attribute", "Month"}}),
#"Changed Type" = Table.TransformColumnTypes(#"Renamed Columns",{{"Value", Int64.Type}, {"ID", Int64.Type}})
in
#"Changed Type"
I have a spreadsheet that contains column Names as the product name, quantity, cost.
I want to convert this to rows of data that contain Product Name, Quantity, Cost.
See image below as to what I want.
What is the best way to handle this in Power Query M Language?
Not sure if I want to pivot just the columns that have prod name, quantity and cost?
Thanks
Here's A way...
Starting with this table as Table1:
You can select the Customer column and Unpivot Other Columns to get this:
Then you can add an index column (keep it named Index) and then also a custom column (keep it named Custom) with if Text.EndsWith([Attribute],"Cost") then 1 else 0 as its formula to get this:
Then add another custom column... Name it Total Cost and enter #"Unpivoted Other Columns"[Value]{[Index]+(List.Count(#"Added Custom"[Custom])/List.Sum(#"Added Custom"[Custom]))} as its formula to get:
The two steps above were, first, to set up to locate the corresponding Cost of the Tshirts based on the Cost's position in the Value column and, then, to actually locate the cost and record it on the same line as the respective Tshirts. The Index column provides row positioning information while the Custom column provides count information--both the overall list count and the count of rows with Cost. I use the count information to determine how many index positions to move down the Value column to get associated cost values dynamically.
Then filter on the Attribute column, using Text Filters > Does Not End With... and type the word Cost. All the rows with an Attribute entry ending with the word Cost should disappear:
Remove the Index and Custom columns and Rename the Attribute and Value columns to Product Name and Quantity, respectively to get your final result:
Here's my M code:
let
Source = Excel.CurrentWorkbook(){[Name="Table1"]}[Content],
#"Unpivoted Other Columns" = Table.UnpivotOtherColumns(Source, {"Customer"}, "Attribute", "Value"),
#"Added Index" = Table.AddIndexColumn(#"Unpivoted Other Columns", "Index", 0, 1),
#"Added Custom" = Table.AddColumn(#"Added Index", "Custom", each if Text.EndsWith([Attribute],"Cost") then 1 else 0),
#"Added Custom2" = Table.AddColumn(#"Added Custom", "Total Cost", each #"Unpivoted Other Columns"[Value]{[Index]+(List.Count(#"Added Custom"[Custom])/List.Sum(#"Added Custom"[Custom]))}),
#"Filtered Rows" = Table.SelectRows(#"Added Custom2", each not Text.EndsWith([Attribute], "Cost")),
#"Removed Columns" = Table.RemoveColumns(#"Filtered Rows",{"Index", "Custom"}),
#"Renamed Columns" = Table.RenameColumns(#"Removed Columns",{{"Attribute", "Product Name"}, {"Value", "Quantity"}})
in
#"Renamed Columns"
They key here is pivoting and unpivoting.
Starting with a table like this,
Select the right four columns and click Transform > Unpivot Columns to get this table:
Now create a custom column that classifies the value using this formula.
if Text.EndsWith([Attribute], "Cost") then "Cost" else "Quantity"
I also chopped off the " Cost" piece at the end of the Attribute column. You can either Transform > Replace Values and replace " Cost" with nothing or Transform > Extract > Text Before Delimiter " Cost".
Now pivot the custom column (choose the Value column as your Values Column choice) and, finally, rename the Attribute column to Product Name.
Here's my M code for all the steps:
let
Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45WcknNK0stUnAuLS7Jz00tUtJRMjIGEoYmIJapqZ6pAYhnZKpnYKAUqxOt5JyRmZyYno+swdAQSJiagtUZgNQBeeYQDbEA", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type text) meta [Serialized.Text = true]) in type table [Customer = _t, #"Product Orange T-shirt" = _t, #"Product Blue T-shirt" = _t, #"Product Orange T-shirt Cost" = _t, #"Product Blue T-shirt Cost" = _t]),
#"Changed Type" = Table.TransformColumnTypes(Source,{{"Customer", type text}, {"Product Orange T-shirt", Int64.Type}, {"Product Blue T-shirt", Int64.Type}, {"Product Orange T-shirt Cost", type number}, {"Product Blue T-shirt Cost", type number}}),
#"Unpivoted Columns" = Table.UnpivotOtherColumns(#"Changed Type", {"Customer"}, "Attribute", "Value"),
#"Added Custom" = Table.AddColumn(#"Unpivoted Columns", "Custom", each if Text.EndsWith([Attribute], "Cost") then "Cost" else "Quantity"),
#"Replaced Value" = Table.ReplaceValue(#"Added Custom"," Cost","",Replacer.ReplaceText,{"Attribute"}),
#"Pivoted Column" = Table.Pivot(#"Replaced Value", List.Distinct(#"Replaced Value"[Custom]), "Custom", "Value", List.Sum),
#"Renamed Columns" = Table.RenameColumns(#"Pivoted Column",{{"Attribute", "Product Name"}})
in
#"Renamed Columns"
This is for a Power Query:
I am working on a report that compiles information from different dates and I need a column that generates the most recent date in the list and the previous date to the most current one in separate columns:
Most Current Date must be the same for the whole column (same for Previous Date Column)
Table Name : Skipped_Issue
Worker |Case |Report_Date |MOST_CURRENT_DATE |PREVIOUS_DATE
Tran |3000 |1/2018
Dhni |52451 |4/2018
Dhtuni |39656 |2/2018
For the most recent date, you can create a custom column with this formula:
= Date.From(List.Max(NameOfPreviousStep[Report_Date]))
Where NameOfPreviousStep references the prior step in your query (e.g. #"Changed Type" or Source).
To get the second to last date, you can create a custom column that evaluates the max after removing the MOST_CURRENT_DATE
= Date.From(
List.Max(
List.RemoveItems(#"Added Custom"[Report_Date],
#"Added Custom"[MOST_CURRENT_DATE])))
Here's the whole query for the sample data:
let
Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45WCilKzFPSUTI2MDAAUob6hvpGBoYWSrE60UouGXmZQDFTIxNTQyBtgipXUgqWNbY0MzUD0kZw2VgA", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type text) meta [Serialized.Text = true]) in type table [Worker = _t, Case = _t, Report_Date = _t]),
#"Changed Type" = Table.TransformColumnTypes(Source,{{"Worker", type text}, {"Case", Int64.Type}, {"Report_Date", type date}}),
#"Added Custom" = Table.AddColumn(#"Changed Type", "MOST_CURRENT_DATE", each Date.From(List.Max(Source[Report_Date])), type date),
#"Added Custom1" = Table.AddColumn(#"Added Custom", "PREVIOUS_DATE", each Date.From(List.Max(List.RemoveItems(#"Added Custom"[Report_Date], #"Added Custom"[MOST_CURRENT_DATE]))), type date)
in
#"Added Custom1"
#Alexis-Olson That's useful, my respect for lists goes up! I needed to get the max row for each item(worker) date, I wrote code like this:
#"Grouped Rows" = Table.Group(#"Removed Columns", {"Worker"}, {{"AllDates", each _, type table}}),
#"Added ReportDate List" = Table.AddColumn(#"Grouped Rows", "ReportDates", each [AllDates][Report_Date]),
#"Added MaxReportDate" = Table.AddColumn(#"Added ReportDate List", "Report_Date", each List.Max([ReportDates])),
and then merged back to get the single item for the max date for each worker. I'm finding the Grouped Rows with all rows handy when I need a list of a column