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dax_bi
Helper I
Helper I

How to find percentage of values in a same column

Hello all,

I have a problem that I can not solve 

 

i want to find the % of purchase and no purchase on a matrix table 

 

like for example 

i would like to get a table like this 

dax_bi_0-1658494358693.png

 

 

6 REPLIES 6
dax_bi
Helper I
Helper I

i want to have a % for each Purchase and no purchase for each month next the the "Nb" coulumn

 

dax_bi_0-1658498323927.png

Below is a sample image from Excel, i just wanted to get something similar

dax_bi_1-1658498396214.png

 

 

dax_bi
Helper I
Helper I

Sorry for my previous data info i guess this pbix would make more sense, please download from below link

 

https://we.tl/t-wlZBfZbxwa

dax_bi
Helper I
Helper I

Hi Kudo, 

 

Thanks for your reply , below is my table and i need to get similar table like in the screenshot i provided earlier, is there any way you can help please 

 

idsubmissionNumberuserId📠Country📠City📠Retailer📠Store📆Date📝Was a service performed?📝Was the AOP kit used?📝Type of Service.1📝Type of Service.2📝Which Collection was used for the Service?📝Was the client's Complexion touched up?📝Was a Purchase made?🏷Number of References📦Total Quantity of Products🪙Total Basket Value🚻Was the client a new La Prairie user?🚻Client Gender🌎Nationality🚻Client Age RangeUpdateUser.Id📆Date - BasketCorrectDate
019c789c-9308-4125-9600-41ddb94820bf27955660106012HONG KONGHONG KONGDFSHONG KONG, DOWNTOWN DUTY FREE, GALLERIA SUN PLAZA7/21/2022 7:04:42 AM +00:00NoNo   NoPurchase11281Existing🚺FemaleEurope41-50769127/21/2022 9:04:42 AM +02:007/21/2022 3:04:42 PM +00:00
03a1334a-9177-4e67-95cd-cb2b6453db8327956667106012HONG KONGHONG KONGDFSHONG KONG, DOWNTOWN DUTY FREE, GALLERIA SUN PLAZA7/21/2022 7:46:47 AM +00:00YesNoFaceFullPlatinum RareNoPurchase11281Existing🚺FemaleChina31-40 7/21/2022 9:46:47 AM +02:007/21/2022 3:46:47 PM +00:00
1f160837-65fc-4d58-987a-1e0ba5d3b8f327941425105812UNITED ARAB EMIRATESDUBAIDUBAI DUTY FREEDUBAI, DXB, DF, CONCOURSE A, ZONE 18/12/2022 6:44:12 AM +00:00YesYesHandHandPlatinum RareYesNo Purchase000New🚺FemaleIndia20-30769128/12/2022 8:44:12 AM +02:008/12/2022 10:44:12 AM +00:00
203c9a5d-7022-4045-9047-05b20616fd8c27946335106012HONG KONGHONG KONGDFSHONG KONG, DOWNTOWN DUTY FREE, GALLERIA SUN PLAZA8/19/2022 8:00:00 AM +00:00NoNo   NoPurchase11252New👥OtherEurope31-40769128/19/2022 10:00:00 AM +02:008/19/2022 4:00:00 PM +00:00
25cbe64b-99fc-4f43-bdf6-65b4c83c04e427964488106047UNITED KINGDOMLONDONDUFRYLONDON, LHR, TERMINAL 57/20/2022 10:25:00 AM +00:00YesNoHandHandSkin CaviarNoNo PurchasenullnullnullNew🚹MaleOther Asia41-50 7/20/2022 12:25:00 PM +02:007/20/2022 11:25:00 AM +00:00
26a381f5-2c60-48d5-a210-0cd5f0ca1c7a27941441105812HONG KONGHONG KONGDFSHONG KONG, DOWNTOWN DUTY FREE, GALLERIA SUN PLAZA8/21/2022 6:15:39 AM +00:00NoNo   YesNo Purchase000Existing🚺FemaleAfrica50+769128/21/2022 8:15:39 AM +02:008/21/2022 2:15:39 PM +00:00
4f653761-e97a-4d26-8cf4-ea8b733c822127941418105812UNITED KINGDOMLONDONDUFRYLONDON, LHR, TERMINAL 38/11/2022 6:43:36 AM +00:00YesYesEyesProduct ApplicationWhite CaviarNoNo Purchase000New🚺FemaleNorth America41-50769128/11/2022 8:43:36 AM +02:008/11/2022 7:43:36 AM +00:00
6c693221-5163-4d83-b197-6b0ed0cd67a227941454105812MACAOMACAODFSMACAO, DOWNTOWN DUTY FREE, FOUR SEASONS8/15/2022 6:45:06 AM +00:00NoNo   YesPurchase341008New🚹MaleSouth America20-30769128/15/2022 8:45:06 AM +02:008/15/2022 2:45:06 PM +00:00
718722ec-5b1a-45d9-afca-199f600affa927941468105812MACAOMACAODFSMACAO, DOWNTOWN DUTY FREE, FOUR SEASONS8/20/2022 6:46:13 AM +00:00YesYesFaceFullPlatinum RareYesPurchase591860New👥OtherChina41-50769128/20/2022 8:46:13 AM +02:008/20/2022 2:46:13 PM +00:00
74a2e57a-3323-4480-a8b5-4de5e849a95027946326106012HONG KONGHONG KONGDFSHONG KONG, DOWNTOWN DUTY FREE, GALLERIA SUN PLAZA8/9/2022 12:09:00 PM +00:00YesYesFaceFullPlatinum RareYesPurchase222868New🚹MaleMiddle East41-50769128/9/2022 2:09:00 PM +02:008/9/2022 8:09:00 PM +00:00
85af6625-9d59-455e-b86b-96800d19126527926058106021UNITED KINGDOMLONDONDUFRYLONDON, LHR, TERMINAL 28/4/2022 9:07:00 AM +00:00YesYesFaceFullWhite CaviarNoPurchase281828New🚺FemaleSouth America20-30769128/4/2022 11:07:00 AM +02:008/4/2022 10:07:00 AM +00:00
9e656bd8-4852-4b2a-a714-724e9bfc287b27956721106012HONG KONGHONG KONGDFSHONG KONG, DOWNTOWN DUTY FREE, GALLERIA SUN PLAZA7/21/2022 7:48:54 AM +00:00NoNo   YesPurchase11252Existing🚺FemaleSouth America31-40 7/21/2022 9:48:54 AM +02:007/21/2022 3:48:54 PM +00:00
a357e1b1-c42d-409d-9698-1bd0f42c39e127941411105812UNITED STATESLOS ANGELESDFSLOS ANGELES, LAX, TOM BRADLY TERMINAL INTERNATIONAL8/9/2022 6:42:48 AM +00:00YesYesFaceFullPure GoldYesPurchase361599New👥OtherOther Asia31-40769128/9/2022 8:42:48 AM +02:008/9/2022 1:42:48 PM +00:00
b8211cfe-44ef-4dd7-bf67-202388af9f8227964472106047UNITED KINGDOMLONDONDUFRYLONDON, LHR, TERMINAL 27/21/2022 10:23:50 AM +00:00YesYesFacePreludePure GoldYesPurchase22nullNew🚺FemaleEurope31-40 7/21/2022 12:23:50 PM +02:007/21/2022 11:23:50 AM +00:00
d16cb1cd-9225-478d-8a2d-f956e1e35e0027932435106012HONG KONGHONG KONGDFSHONG KONG, DOWNTOWN DUTY FREE, GALLERIA SUN PLAZA8/3/2022 2:49:00 PM +00:00NoNoFacePreludeSkin CaviarNoPurchase11790New🚹MaleMiddle East41-50769128/3/2022 4:49:00 PM +02:008/3/2022 10:49:00 PM +00:00
e070b7c5-ac97-4a1f-a962-87b5878fede027942061106012HONG KONGHONG KONGDFSHONG KONG, DOWNTOWN DUTY FREE, GALLERIA SUN PLAZA8/10/2022 10:20:00 AM +00:00YesYesFacePreludeSkin CaviarNoPurchase232019Existing🚺FemaleRussia31-40769128/10/2022 12:20:00 PM +02:008/10/2022 6:20:00 PM +00:00

Try this code

Purchase = CALCULATE( DISTINCTCOUNT('Sales'[id]) , 'Sales'[Was a Purchase made?] = "Purchase") 

No purchase = CALCULATE( DISTINCTCOUNT('Sales'[id]) , 'Sales'[Was a Purchase made?] <> "Purchase") 

 

Purchase % = DIVIDE( [Purchase] , [Purchase] + [No purchase] )

technolog
Super User
Super User
technolog
Super User
Super User

I suppose that It's not a one matrix table on screenshots. It's two matrix.

If you want just calculate measures you can use something like this:

Purchase = CALCULATE( COUNT('Sales'[purchase id]) , 'Sales'[Status] = "Purchase") 

No purchase = CALCULATE( COUNT('Sales'[purchase id]) , 'Sales'[Status] <> "Purchase") 

 

Purchase % = DIVIDE( [Purchase] , [Purchase] + [No purchase] )

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