Visualise number of stations by category

[Anonymous]

Hello,

So i have a data set composed of

Table transactions: 

id transaction /

station /

amount /

date

Table Station: 

Station /

Location /

Country

And Table Date

I can visualise in a Matrix how many transactions per station per time(month, year, day ,week... ). 

Using the function number of transactions (NbreTransactions N = COUNTX(Tbl_Transactions,Tbl_Transactions[ID Transaction]))

The visualition looks like this:

Station	month 1	month 2	month 3
A	50	55	100
B	0	2	6
C	1	100	0

Morover i have edited the visual So that the number appear in colors based on the category ( green >5 yellow >0 and red=0). You get the idea.

My problem is I want a visual where i can track the number of stations by Number of transaction per period by category.

I want the final result in a stacked histogram.

For the table above Example :

month 1 the stacked histogram divided into 3 part where it shows 1/3 red 1/3 yellow 1/3 green.

month 2 the stacked histogram divided into 2 part where it shows 1/3 yellow 2/3 green.

month 3 the stacked histogram divided into 2 part where it shows 1/3 red 2/3 green.

I'm really lost any help is appreciated.

Thank you.

[v-chenwuz-msft · Accepted solution]

Hi  , 

Is this you want?

If yes, please follow these steps to do.

1 Create a color table via 

Table = {("RED",1),("GREEN",3),("YELLOW",2)}

2 Create a measure:

measure =
VAR _S =
    SUMMARIZE ( 'FACT TABLE', [Station], "COUNT", [NbreTransactions N] )
VAR _R =
    COUNTROWS ( FILTER ( _S, [COUNT] = 0 ) ) + 0
VAR _Y =
    COUNTROWS ( FILTER ( _S, [COUNT] > 0 && [COUNT] < 5 ) ) + 0
VAR _G =
    COUNTROWS ( FILTER ( _S, [COUNT] > 5 ) ) + 0
RETURN
    SWITCH ( SELECTEDVALUE ( 'Table'[Color] ), "RED", _R, "YELLOW", _Y, _G )

3 Create a visual and put this measure in y-axis, month in x-axis and color in legend. 

Pbix in the end you can refer.

Best Regards

Community Support Team _ chenwu zhu

If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

[Anonymous]

Thank you and have a nice day.