Hi NMC20 ,

This is a difficult problem. What i suggest is creating in PowerQuery a new conditional column with the following statements: 

Next up creating a new summarized table of the current table you have:

_NewTable = SUMMARIZE('Table','Table'[Item],
"08:00 - 09:00", DIVIDE(MAX('Table'[08:00 - 09:00]),MAX('Table'[Denominator])),
"09:00 - 10:00", DIVIDE(MAX('Table'[09:00 - 10:00]),MAX('Table'[Denominator])),
"10:00 - 11:00", DIVIDE(MAX('Table'[10:00 - 11:00]),MAX('Table'[Denominator])),
"11:00 - 12:00", DIVIDE(MAX('Table'[11:00 - 12:00]),MAX('Table'[Denominator])),
"12:00 - 13:00", DIVIDE(MAX('Table'[12:00 - 13:00]),MAX('Table'[Denominator]))
)

which has the following output

Here is another way you could do this in M.
Adding a column with the row sum

and then select the Item and RowSum column and "unpivoting other columns"

you can then divide the count by the row sum.

You can use the resulting table to create a matrix visual similar to your desired output.

Here is the example M code.

let
    Source = 
    Table.FromRows(
        Json.Document(
            Binary.Decompress(
                Binary.FromText(
                    "i45WMjRQcMnPL1LSUTIEYiMobQzEJkqxOtFKJsjSIGwAVWYMljaDSRsgSZkCsblSbCwA", 
                    BinaryEncoding.Base64
                ), 
                Compression.Deflate
            )
        ), 
        let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [Item = _t, #"08:00 - 09:00" = _t, #"09:00 - 10:00" = _t, #"10:00 - 11:00" = _t, #"11:00 - 12:00" = _t, #"12:00 - 13:00" = _t]
    ),
    #"Added Custom" = 
    Table.AddColumn(
        Source, 
        "RowSum", 
        each 
        List.Sum(
            List.Transform(
                Record.ToList(
                    Record.RemoveFields(_, {"Item"})
                ), 
                each Number.FromText(_)
            )
        ), 
        Int64.Type
    ),
    #"Unpivoted Other Columns" = 
    Table.UnpivotOtherColumns(
        #"Added Custom", 
        {"Item", "RowSum"}, 
        "Time", 
        "Value"
    ),
    #"Add Percentage" = 
    Table.AddColumn(
        #"Unpivoted Other Columns", 
        "Percentage", 
        each Number.FromText([Value]) / [RowSum], 
        type number
    ),
    #"Remove RowSum" = 
    Table.RemoveColumns(
        #"Add Percentage",
        {"RowSum"}
    )
in
    #"Remove RowSum"

Hi NMC20, here's another solution for your query using M. Thanks

Here's the code:
let
Source = #table(
{"Item", "08:00 - 09:00", "09:00 - 10:00", "10:00 - 11:00", "11:00 - 12:00", "12:00 - 13:00"},
{{"10 Door", 1, 2, 1, 3, 4}, {"4 Door", 1, 0, 2, 3, 4}, {"6 Door", 0, 1, 2, 5, 7}}
),
Cols = List.RemoveLastN(List.Skip(Table.ColumnNames(Source), 1), 1),
Table = Source,
Unpivot = Table.UnpivotOtherColumns(Table, {"Item"}, "Attribute", "Value"),
#"Grouped Rows" = Table.Group(
Unpivot,
{"Item"},
{{"Data", each _, type table [Item = text, Attribute = text, Value = number]}}
),
TTF = Table.TransformColumns(
#"Grouped Rows",
{
"Data",
each Table.TransformColumns(
Table.DuplicateColumn(_, "Item", "Denom"),
{"Denom", each Total[Total]{List.PositionOf(Total[Item], _)}}
)
}
),
TTS = Table.TransformColumns(
TTF,
{
"Data",
each Table.SelectColumns(
Table.Pivot(
Table.SelectColumns(
Table.AddColumn(_, "Val", each [Value] / [Denom]),
{"Item", "Attribute", "Val"}
),
[Attribute],
"Attribute",
"Val",
List.Sum
),
Cols
)
}
),
Expand = Table.ExpandTableColumn(TTS, "Data", Cols, Cols)
in
Expand

Hi NMC20,

Thank you for reaching out to the Microsoft Fabric Forum Community. And also thanks to Demert , SundarRaj  and jgeddes for prompt and helpful responses.

Just following up to see if the solution provided was helpful in resolving your issue. Please feel free to let us know if you need any further assistance.

Best regards,

Prasanna Kumar

Hi NMC20,

No, you cannot have two let and in blocks in the same query each query can only have one let and one in. Once you open the Advanced Editor, you can clear the existing code and paste the code provided in the relevant response. Then, update the connection string in the Source step to match your setup, and click OK to apply the changes.

if the issue still persists Please reach out to us, to assist further.

Thanks & regards,

Prasanna Kumar

Hi NMC20,

Just following up to see if the solution provided was helpful in resolving your issue. Please feel free to let us know if you need any further assistance.

Best regards,

Prasanna Kumar

Hi NMC20 

o calculate the % uptake by item over time in Power BI—where each item has a different number of available units—you need to dynamically adjust the denominator for each item based on its availability. The goal is to convert raw counts (e.g., doors used per hour) into a percentage of total available units for that item, broken down by hourly time slots. You've already achieved the time-based breakdown, which is great, but converting to percentages requires bringing in the availability data and using it in a DAX measure. The best approach is to create a separate table with two columns: one for Item and one for Available Units. Then, create a relationship between this table and your main usage data via the Item column. Once the relationship is in place, create a measure using DAX like this:

% Uptake = 
DIVIDE(
    SUM('UsageData'[Used]),
    RELATED('Availability'[Available Units])
)

This measure calculates the usage for each item and hour and divides it by that item's total available units. Power BI will then respect the item-level granularity during visualization, showing the correct percentage per hour per item. You can format this measure as a percentage, and use it in your matrix visual with Item on rows and time slots as columns. This setup ensures that each item uses its own denominator, and the result reflects true percentage uptake as you'd expect.

Hi NMC20,

Thank you for reaching out to the Microsoft Fabric Forum Community, and special thanks to MarkLaf, Poojara_D12 , slorin  and Demert  for their prompt and helpful responses.

Just following up to see if the solutions provided by community members were helpful in addressing the issue.

If one of the responses helped resolve your query, please consider marking it as the Accepted Solution. Feel free to reach out if you need any further clarification or assistance.

Best regards,
Prasanna Kumar