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Consider this data sample :
| User | Lines | Hours | UpH |
| Jan | 147 | 2.1 | 70 |
| Jan | 147 | 2.1 | 70 |
| Jan | 147 | 2.1 | 70 |
| Jan | 147 | 2.1 | 70 |
| Jan | 147 | 2.1 | 70 |
| Jan | 147 | 2.1 | 70 |
| Jan | 147 | 2.1 | 70 |
| Jan | 147 | 2.1 | 70 |
| Piet | 200 | 2.6 | 77 |
| Piet | 200 | 2.6 | 77 |
| Piet | 200 | 2.6 | 77 |
| Piet | 200 | 2.6 | 77 |
| Piet | 200 | 2.6 | 77 |
| Piet | 200 | 2.6 | 77 |
| Piet | 200 | 2.6 | 77 |
| Piet | 200 | 2.6 | 77 |
| Piet | 200 | 2.6 | 77 |
| Total | 347 | 4.7 | 74 |
UpH is Lines / Hours
On a line level this is straight forward.
But on a total level it should only sum the unique values.
Summing unique values would also work on a line level because there is only 1 value.
But can it be done sum unique?
Solved! Go to Solution.
Hi @rpinxt - create a new measures for unique Lines and Hours as below:
For New measure Hours:
Now let's calculate another measure for the totalUpH based on the unique sums.
TotalUpH = DIVIDE([UniqueLines], [UniqueHours])
Hope it works
Proud to be a Super User! | |
Note that this assumes only one unique set of values for each user.
If this is not the case, try summarizing over the appropriate level of granularity. For example, this groups over users and lines:
UniqueLines =
SUMX (
SUMMARIZE (
'lhp',
'lhp'[User],
'lhp'[Lines]
),
'lhp'[Lines]
)
Thanks for this @rajendraongole1 and @AlexisOlson I appreciate it.
However with the first method I did not get unique values per user :
So guessing it was because of what Alexis said, howver that method also did not give me unique lines per user.
181460 is the total number of rows in the dataset.
Used this code :
But this did not change anything.
Thanks again @AlexisOlson and @rajendraongole1
Your solutions work but not entirely how we had our data modeled.
We made changes now and found a solutions.
Thanks for your help.
Thanks for this @rajendraongole1 and @AlexisOlson I appreciate it.
However with the first method I did not get unique values per user :
So guessing it was because of what Alexis said, howver that method also did not give me unique lines per user.
181460 is the total number of rows in the dataset.
Used this code :
But this did not change anything.
Those results look odd for sure. Is the [User name] column in your table visual coming from a different data table?
Hi @rpinxt - create a new measures for unique Lines and Hours as below:
For New measure Hours:
Now let's calculate another measure for the totalUpH based on the unique sums.
TotalUpH = DIVIDE([UniqueLines], [UniqueHours])
Hope it works
Proud to be a Super User! | |
Note that this assumes only one unique set of values for each user.
If this is not the case, try summarizing over the appropriate level of granularity. For example, this groups over users and lines:
UniqueLines =
SUMX (
SUMMARIZE (
'lhp',
'lhp'[User],
'lhp'[Lines]
),
'lhp'[Lines]
)
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| User | Count |
|---|---|
| 25 | |
| 22 | |
| 21 | |
| 19 | |
| 18 |
| User | Count |
|---|---|
| 42 | |
| 41 | |
| 40 | |
| 21 | |
| 20 |