Calculate new clients over time

[mccollough]

Let's say you want to trend the number of distinct client ID's over time from a table of invoices.

I have an invoice table that looks like this

Date	Client ID	Sale Amount
1/1/2021	100	$100
1/1/2021	223	$100
1/2/2021	100	$50
1/3/2021	270	$100
1/3/2021	100	$100
1/4/2021	223	$50
1/5/2021	270	$100
1/6/2021	400	$100
1/6/2021	550	$50
1/6/2021	660	$100
1/6/2021	700	$100
1/7/2021	100	$50

And I want to produce something that looks like this 

Date	Client Count
1/1/2021	2
1/2/2021	2
1/3/2021	3
1/4/2021	3
1/5/2021	3
1/6/2021	7
1/7/2021	7

I've already successfully created a table of distinct dates and I've tried to aggregate Client IDs with SUMMARIZECOLUMNS but I've only been able to show the number of distinct IDs that occur on each date. 

[AlexisOlson · Accepted solution]

This looks like a standard cumulative total pattern.

Client Count = 
VAR CurrDate = MAX ( dimDate[Date] )
RETURN
    CALCULATE ( DISTINCTCOUNT ( Table1[Client ID] ), dimDate[Date] <= CurrDate )

[mccollough]

You're a wizard Harry

Thank you so much for the help!!!

[smpa01]

@mccollough   you can use a measure like this

Measure = 
VAR _date =
    MAX ( 'Table'[Date] )
RETURN
    COUNTROWS (
        EXCEPT (
            VALUES ( 'Table'[Client ID] ),
            SUMMARIZE (
                FILTER ( ALL ( 'Table' ), 'Table'[Date] < _date ),
                'Table'[Client ID]
            )
        )
    )