Last reading

[JuliaYebra]

Hello, I have this dataset with different temperature readings for same items.

Is it any way to only keep the last reading for each item?

This would be the yellow records.

Thanks

[v-huizhn-msft]

Hi @JuliaYebra,

Have you resolved your issue? If you have, welcome to share your solution or mark the right reply as answer. More people will find solution easily here.

Best Regards,

Angelia

[nickchobotar]

Hi @JuliaYebra

Here is another light weight version as a calc column

MaxTemp =
VAR MaxDate =
    CALCULATE ( 
		MAX ( Table2[Date] ), 
		ALLEXCEPT ( Table2, Table2[Item] ) 
	)
RETURN
    CALCULATE ( 
    	VALUES ( Table2[Temperature] ), 
    	Table2[Date] = MaxDate 
	)

[parry2k]

Hi @nickchobotar

I guess it is a calculated measure not column?

[nickchobotar]

@parry2k

It is actually a calc column.  Below is the measure. Same idea expect that  ALLEXCEPT() will not work here, so I am using  ALL() + VALUES()

MaxTempMeasure = 
CALCULATE(
    VALUES(Table2[Temperature]),
        FILTER(
            Table2,
            Table2[Date] = CALCULATE(
                            MAX(Table2[Date]),
                                ALL(Table2),
                                VALUES(Table2[Item])
                        )
        )
)


Here is the solution with calculated column again 
MaxTempCalcColumn = 
VAR MaxDate =
    CALCULATE ( 
		MAX ( Table2[Date] ), 
		ALLEXCEPT ( Table2, Table2[Item] ) 
	)
RETURN
    CALCULATE ( 
    	VALUES ( Table2[Temperature] ), 
    	Table2[Date] = MaxDate 
	)

[KHorseman]

Essentially that same column is in my solution. I just nested it inside a calculated table, then used it to filter the table so only the max date rows are kept, then removed the calculated column because you don't actually need to see it after that.

[Zubair_Muhammad]

That was ingenious @KHorseman

[fhill]

There are probably several ways to do this, but here's one option:  

DAX Column 1:  This calculates the MAX DateTime for each Item && Machine grouping.

LastReading_DateTime = CALCULATE(MAX(Table2[DateTime]), FILTER(ALL(Table2), Table2[Machine] = EARLIER(Table2[Machine]) && Table2[Item] = EARLIER(Table2[Item])))

DAX Column 2:  This only returns a TEMP if the LastReading_DateTime matches the original table's DateTime

LastReading_Temp = IF (Table2[DateTime] = Table2[LastReading_DateTime],Table2[Temp],BLANK())

(Sorry my DateTime is descending, but you get the idea.)

[erik_tarnvik]

Indeed there is. Go to Power Query to edit your data import. Select both your Machine and your Item column. Click Transform - Group By. In the dialog, change New Column Date to Date, Operation to Max and Column to Date. That should give you this:

But, we lost the temperature. We need to bring it back in. Load your data again using Recent Sources. I called your table Reading, so this gives me a Reading (2) query in the Query pane. Select your original query (Reading in my example) in the query pane and click Merge Queries. In the top portion, select the Machine, Item and Date columns (ctrl-click on each column). Then select your Reading 2 query in the drop down further down and select all three same columns. Press OK. You should now have this:

Click the small icon in the upper right corner of the Reading (2) column header to expand the tables. Select only the Temp item in the resulting pop-up. Rename the resulting Column to Temp. 

The only remaining thing now is to right click the Reading (2) query and unselect the Enable Load menu item. This prevents this temporary query to from being loaded to your data model. Click close and apply and your should have the result you want.

[parry2k]

here simple formula to add new column to identify last reading (most recent)

Last Reading = 
var r = 
RANKX(
FILTER(Table1, Table1[Machine] = EARLIER(Table1[Machine]) && 
Table1[Item] = EARLIER(Table1[Item])), Table1[Date], , DESC, DENSE
)
return if(r = 1, "Yes", "")

[erik_tarnvik]

While I was writing my Power Query based response, @KHorseman provided a DAX based method that also works.

One possible benefit of the Power Query method is that it doesn't clutter your data model with unecessary data. On the other hand, perhaps you need that data for some purpose and in that case, I would go with the DAX method.

[KHorseman · Accepted solution]

Go to Modeling and hit New Table.

NewTable = SUMMARIZE(
	FILTER(
		ADDCOLUMNS(
			TableName,
			"Last Reading", VAR lastreadingdate = CALCULATE(
				MAX(TableName[Date]),
				ALLEXCEPT(TableName, TableName[Item])
			)
			RETURN IF(TableName[Date] = lastreadingdate, TRUE, FALSE) 
		),
		[Last Reading] = TRUE
	),
	TableName[Machine], TableName[Item], TableName[Date], TableName[Temperature]
)