Filter out rows with max values in certain column

[anonymous]

I’m feeling a bit stupid now as I should be able to figure this out on my own.

I’ve got a table that goes something like this:

User	Exercise	Date	Score	Level 1	Level 2	Level 3
User X	Exercise 1	Date 1	365	91%	81%	73%
User X	Exercise 2	Date 2	180	90%	78%	69%
User X	Exercise 1	Date 3	380	95%	84%	76%
User X	Exercise 2	Date 4	200	100%	87%	77%
User X	Exercise 3	Date 4	150	33%	30%	27%
User X	Exercise 1	Date 5	350	88%	78%	70%

Where Level 1, 2 and 3 indicates your progress towards that level for each exercise (each exercise has unique goal levels defined)

I want to create a slice where I list all the unique rows based on exercises for a user where level 2 is at it’s maximum. Which for User X should result in the following:

User	Exercise	Date	Score	Level 1	Level 2	Level 3
User X	Exercise 2	Date 2	180	90%	78%	69%
User X	Exercise 2	Date 4	200	100%	87%	77%
User X	Exercise 3	Date 4	150	33%	30%	27%

Thankful for any hints and help!

[WillowMobileSys]

Is your resultant table correct? you are showing Exercise 2 twice. If it is correct, please explain why Exercise 2 should be shown twice

[gregdiana1]

I think the first row is incorrect and should read

User	Exercise	Date	Score	Level 1	Level 2	Level 3
User X	Exercise 1	Date 3	380	95%	84%	76%
User X	Exercise 2	Date 4	200	100%	87%	77%
User X	Exercise 3	Date 4	150	33%	30%	27%

[gregdiana1]

Ok, you do not even need a slice you can do this with a table view and aggregation as shown below.

This will yield

And then you can click on anyone and drill down.

If you have more than one user then simply group as follows

Which yields

and then drilling down on X gives

This no-code should do unless you want to develop a custom T/F select statement for any slice.which is possible and easily done.

Cheers

Greg Diana

Here is the table I used

ID	User	Exercise	Date	Score	Level 1	Level 2	Level 3
1.00	User X	Exercise 1	Date 1	365.00	91%	81%	73%
2.00	User X	Exercise 2	Date 2	180.00	90%	78%	69%
3.00	User X	Exercise 1	Date 3	380.00	95%	84%	76%
4.00	User X	Exercise 2	Date 4	200.00	100%	87%	77%
5.00	User X	Exercise 3	Date 4	150	33%	30%	27%
6.00	User X	Exercise 1	Date 5	350	88%	78%	70%
7.00	User Y	Exercise 1	Date 1	365.00	91%	83%	73%
8.00	User Y	Exercise 2	Date 2	180.00	90%	76%	69%
9.00	User Y	Exercise 1	Date 3	380.00	95%	80%	76%
10.00	User Y	Exercise 2	Date 4	200.00	100%	85%	77%
11.00	User Y	Exercise 3	Date 4	150	33%	55%	27%
12.00	User Y	Exercise 1	Date 5	350	88%	75%	70%

[anonymous]

Thanks!!!

[anonymous]

Typo