measure to get symmetrical matrix

[krishna_sipl]

Hello,
I need help to create a symmetrical matrix, day-wise.
Eg: 1st-day count the Test2 column ID's who has a Test1 column name: "Create Account"
then from 2nd day count the same ID's who has any name from Test1 column till every
7 days in percentage.

dataset attached: Dataset.csv 
it should look like this :

Just curious is it possible to create a measure to display like this?

[v-deddai1-msft]

Hi @krishna_sipl ,

>>Just curious is it possible to create a measure to display like this?

Yes it is really possible to display like this by measure. Would you please show us more details about your calculation of every column.

And please refer to youtube video: https://www.youtube.com/watch?v=WSnB5y2JXv8. I hope it may give you some thought of your issue.

Best Regards,

Dedmon Dai

[MFelix]

Hi  @krishna_sipl ,

Can you share some more context on the calculation?

I have made the download of your data and looking for example for april 16th I get 10 records what is the calculation you need for each day?

Is the calculation following:

Number of cases Create account divided by number of cases with Created in the previous day (1 till 7)

This is possible to achieve but need more insights, I was abble to get the visualization type you need but the date is on the incorrect order so I assume my previous asusmption is incorrect but overall look is possible just need to adjust the measure:

[krishna_sipl]

Thank you for reply @MFelix 
Please take look this below file, this contains complete data : File_For_Download.Pbix 

and let me explain the data which I share :

Test 1 column contains all events(names), Test 2 column contains all ids,

so supposed I choose one date like
15 April 2020 then It should show me data in the symmetrical matrix(pic reference which I shared).

Like: (horizontally) 

1. 15 April: 
   1. 1st block: count of distinct ID's who has the name "Create Account" on 15th April
   2. 2nd block: show in percentage same Ids who match with other names(except Create Account) for 15 April
   3. 3rd block:  show in percentage same Ids who match with other names(except Create Account) for 16 April
   4. 4th block:  show in percentage same Ids who match with other names(except Create Account) for 17 April
   5. 5th block:  show in percentage same Ids who match with other names(except Create Account) for 18 April
   6. 6th block:  show in percentage same Ids who match with other names(except Create Account) for 19 April
   7. 7th block:  show in percentage same Ids who match with other names(except Create Account) for 20 April
   8. 8th block:  show in percentage same Ids who match with other names(except Create Account) for 21 April
   9. 9th block:  show in percentage same Ids who match with other names(except Create Account) for 22 April
2. 16 April(next line):
   
   1. 1st block: count of distinct ID's who has the name "Create Account" on 16th April
   2. 2nd block: show in percentage same Ids who match with other names(except Create Account) for 16 April
   3. 3rd block: show in percentage same Ids who match with other names(except Create Account) for 17 April
   4. 4th block: show in percentage same Ids who match with other names(except Create Account) for 18 April
   5. 5th block: show in percentage same Ids who match with other names(except Create Account) for 19 April
   6. 6th block: show in percentage same Ids who match with other names(except Create Account) for 20 April
   7. 7th block: show in percentage same Ids who match with other names(except Create Account) for 21 April
   8. 8th block: show in percentage same Ids who match with other names(except Create Account) for 22 April
3. 17 April (next line):
   1. 1st block: count of distinct ID's who has the name "Create Account" on 17th April
   2. 2nd block: show in percentage same Ids who match with other names(except Create Account) for 17 April
   3. 3rd block: show in percentage same Ids who match with other names(except Create Account) for 18 April
   4. 4th block: show in percentage same Ids who match with other names(except Create Account) for 19 April
   5. 5th block: show in percentage same Ids who match with other names(except Create Account) for 20 April
   6. 6th block: show in percentage same Ids who match with other names(except Create Account) for 21 April
   7. 7th block: show in percentage same Ids who match with other names(except Create Account) for 22 April

So on till 22 April

Hope I explain well, please tell me if you have any doubts.

[MFelix]

Hi @krishna_sipl ,

The google drive is asking for password. can you make it shareable witouth password.

When you are referring the same ID's you mean for example:

ID 1 has 6 records in the table in 15 april

1 record is for created and the other 5 are for other names so you want to calculate 5 divided by what value?

On the 16th what is the calculation  all the values that are not created divided by the 5?

[krishna_sipl]

Hello @MFelix 

please check now: FileDownloadpdix 

same Ids, Means which you are uniquely counting on 1st block for each date.

and each ID's varies this is not necessary that you will get 6 same Ids for a name every time.

I only need to know that is it the same ID which we are counted in the first block is also present for other names.

It doesn't matter how many times, minimum it should be only a one-time match with any name for a particular date.

and this will be changing, date wise for every block.