How to find percentage of values in a same column

[dax_bi]

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]

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

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

[dax_bi]

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]

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 

id

submissionNumber

userId

📠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 Range

UpdateUser.Id

📆Date - Basket

CorrectDate

019c789c-9308-4125-9600-41ddb94820bf

27955660

106012

HONG KONG

HONG KONG

DFS

HONG KONG, DOWNTOWN DUTY FREE, GALLERIA SUN PLAZA

7/21/2022 7:04:42 AM +00:00

❌No

❌No

❌No

Purchase

1

1

281

Existing

🚺Female

Europe

41-50

76912

7/21/2022 9:04:42 AM +02:00

7/21/2022 3:04:42 PM +00:00

03a1334a-9177-4e67-95cd-cb2b6453db83

27956667

106012

HONG KONG

HONG KONG

DFS

HONG KONG, DOWNTOWN DUTY FREE, GALLERIA SUN PLAZA

7/21/2022 7:46:47 AM +00:00

✅Yes

❌No

Face

Full

Platinum Rare

❌No

Purchase

1

1

281

Existing

🚺Female

China

31-40

7/21/2022 9:46:47 AM +02:00

7/21/2022 3:46:47 PM +00:00

1f160837-65fc-4d58-987a-1e0ba5d3b8f3

27941425

105812

UNITED ARAB EMIRATES

DUBAI

DUBAI DUTY FREE

DUBAI, DXB, DF, CONCOURSE A, ZONE 1

8/12/2022 6:44:12 AM +00:00

✅Yes

✅Yes

Hand

Hand

Platinum Rare

✅Yes

No Purchase

0

0

0

New

🚺Female

India

20-30

76912

8/12/2022 8:44:12 AM +02:00

8/12/2022 10:44:12 AM +00:00

203c9a5d-7022-4045-9047-05b20616fd8c

27946335

106012

HONG KONG

HONG KONG

DFS

HONG KONG, DOWNTOWN DUTY FREE, GALLERIA SUN PLAZA

8/19/2022 8:00:00 AM +00:00

❌No

❌No

❌No

Purchase

1

1

252

New

👥Other

Europe

31-40

76912

8/19/2022 10:00:00 AM +02:00

8/19/2022 4:00:00 PM +00:00

25cbe64b-99fc-4f43-bdf6-65b4c83c04e4

27964488

106047

UNITED KINGDOM

LONDON

DUFRY

LONDON, LHR, TERMINAL 5

7/20/2022 10:25:00 AM +00:00

✅Yes

❌No

Hand

Hand

Skin Caviar

❌No

No Purchase

null

null

null

New

🚹Male

Other Asia

41-50

7/20/2022 12:25:00 PM +02:00

7/20/2022 11:25:00 AM +00:00

26a381f5-2c60-48d5-a210-0cd5f0ca1c7a

27941441

105812

HONG KONG

HONG KONG

DFS

HONG KONG, DOWNTOWN DUTY FREE, GALLERIA SUN PLAZA

8/21/2022 6:15:39 AM +00:00

❌No

❌No

✅Yes

No Purchase

0

0

0

Existing

🚺Female

Africa

50+

76912

8/21/2022 8:15:39 AM +02:00

8/21/2022 2:15:39 PM +00:00

4f653761-e97a-4d26-8cf4-ea8b733c8221

27941418

105812

UNITED KINGDOM

LONDON

DUFRY

LONDON, LHR, TERMINAL 3

8/11/2022 6:43:36 AM +00:00

✅Yes

✅Yes

Eyes

Product Application

White Caviar

❌No

No Purchase

0

0

0

New

🚺Female

North America

41-50

76912

8/11/2022 8:43:36 AM +02:00

8/11/2022 7:43:36 AM +00:00

6c693221-5163-4d83-b197-6b0ed0cd67a2

27941454

105812

MACAO

MACAO

DFS

MACAO, DOWNTOWN DUTY FREE, FOUR SEASONS

8/15/2022 6:45:06 AM +00:00

❌No

❌No

✅Yes

Purchase

3

4

1008

New

🚹Male

South America

20-30

76912

8/15/2022 8:45:06 AM +02:00

8/15/2022 2:45:06 PM +00:00

718722ec-5b1a-45d9-afca-199f600affa9

27941468

105812

MACAO

MACAO

DFS

MACAO, DOWNTOWN DUTY FREE, FOUR SEASONS

8/20/2022 6:46:13 AM +00:00

✅Yes

✅Yes

Face

Full

Platinum Rare

✅Yes

Purchase

5

9

1860

New

👥Other

China

41-50

76912

8/20/2022 8:46:13 AM +02:00

8/20/2022 2:46:13 PM +00:00

74a2e57a-3323-4480-a8b5-4de5e849a950

27946326

106012

HONG KONG

HONG KONG

DFS

HONG KONG, DOWNTOWN DUTY FREE, GALLERIA SUN PLAZA

8/9/2022 12:09:00 PM +00:00

✅Yes

✅Yes

Face

Full

Platinum Rare

✅Yes

Purchase

2

2

2868

New

🚹Male

Middle East

41-50

76912

8/9/2022 2:09:00 PM +02:00

8/9/2022 8:09:00 PM +00:00

85af6625-9d59-455e-b86b-96800d191265

27926058

106021

UNITED KINGDOM

LONDON

DUFRY

LONDON, LHR, TERMINAL 2

8/4/2022 9:07:00 AM +00:00

✅Yes

✅Yes

Face

Full

White Caviar

❌No

Purchase

2

8

1828

New

🚺Female

South America

20-30

76912

8/4/2022 11:07:00 AM +02:00

8/4/2022 10:07:00 AM +00:00

9e656bd8-4852-4b2a-a714-724e9bfc287b

27956721

106012

HONG KONG

HONG KONG

DFS

HONG KONG, DOWNTOWN DUTY FREE, GALLERIA SUN PLAZA

7/21/2022 7:48:54 AM +00:00

❌No

❌No

✅Yes

Purchase

1

1

252

Existing

🚺Female

South America

31-40

7/21/2022 9:48:54 AM +02:00

7/21/2022 3:48:54 PM +00:00

a357e1b1-c42d-409d-9698-1bd0f42c39e1

27941411

105812

UNITED STATES

LOS ANGELES

DFS

LOS ANGELES, LAX, TOM BRADLY TERMINAL INTERNATIONAL

8/9/2022 6:42:48 AM +00:00

✅Yes

✅Yes

Face

Full

Pure Gold

✅Yes

Purchase

3

6

1599

New

👥Other

Other Asia

31-40

76912

8/9/2022 8:42:48 AM +02:00

8/9/2022 1:42:48 PM +00:00

b8211cfe-44ef-4dd7-bf67-202388af9f82

27964472

106047

UNITED KINGDOM

LONDON

DUFRY

LONDON, LHR, TERMINAL 2

7/21/2022 10:23:50 AM +00:00

✅Yes

✅Yes

Face

Prelude

Pure Gold

✅Yes

Purchase

2

2

null

New

🚺Female

Europe

31-40

7/21/2022 12:23:50 PM +02:00

7/21/2022 11:23:50 AM +00:00

d16cb1cd-9225-478d-8a2d-f956e1e35e00

27932435

106012

HONG KONG

HONG KONG

DFS

HONG KONG, DOWNTOWN DUTY FREE, GALLERIA SUN PLAZA

8/3/2022 2:49:00 PM +00:00

❌No

❌No

Face

Prelude

Skin Caviar

❌No

Purchase

1

1

790

New

🚹Male

Middle East

41-50

76912

8/3/2022 4:49:00 PM +02:00

8/3/2022 10:49:00 PM +00:00

e070b7c5-ac97-4a1f-a962-87b5878fede0

27942061

106012

HONG KONG

HONG KONG

DFS

HONG KONG, DOWNTOWN DUTY FREE, GALLERIA SUN PLAZA

8/10/2022 10:20:00 AM +00:00

✅Yes

✅Yes

Face

Prelude

Skin Caviar

❌No

Purchase

2

3

2019

Existing

🚺Female

Russia

31-40

76912

8/10/2022 12:20:00 PM +02:00

8/10/2022 6:20:00 PM +00:00

[technolog]

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]

You need provide more information if it won't help.

[technolog]

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] )