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I have a table my_table below and a measure meas_a which takes on values a, b or c
How can my time series visualisation using col_b (x-axis) and col_c (y-axis) be filtered by col_a = meas_a?
For example, if meas_a = "c", then only the last three rows will be included in the visualisation.
Here's a non-picture version of the above table:
| col_a | col_b | col_c |
| a | 1/1/2024 | 1 |
| a | 1/2/2024 | 2 |
| a | 1/3/2024 | 3 |
| b | 1/1/2024 | 4 |
| b | 1/2/2024 | 5 |
| b | 1/3/2024 | 6 |
| c | 1/1/2024 | 7 |
| c | 1/2/2024 | 8 |
| c | 1/3/2024 | 9 |
Solved! Go to Solution.
HI @costing,
Measure expressions are calculated based on their row contents and group. If you want to invoke the specific calculation results in other measure formulas.
It should be better to create variable with summarize function to reproduce the current row contents structures and you can invoke the measure in this variable table.
Reference link:
Measure Totals, The Final Word
Regards,
Xiaoxin Sheng
Hi @costing
Please look into the solution in another post
Solved: measure not filtering visuals when clicked - Microsoft Fabric Community
Let me know if that works for you
If your requirement is solved, please mark THIS ANSWER as SOLUTION ✔️ and help other users find the solution quickly. Please hit the Thumbs Up 👍 button if this comment helps you.
Thanks
Pijush
Linkedin
Proud to be a Super User! | |
Hi, sorry I have no idea how the link relates to my question 😅
Hi @costing
Please share sample data in usable format (not an image)
Proud to be a Super User! | |
Here you go!
| col_a | col_b | col_c |
| a | 1/1/2024 | 1 |
| a | 1/2/2024 | 2 |
| a | 1/3/2024 | 3 |
| b | 1/1/2024 | 4 |
| b | 1/2/2024 | 5 |
| b | 1/3/2024 | 6 |
| c | 1/1/2024 | 7 |
| c | 1/2/2024 | 8 |
| c | 1/3/2024 | 9 |
my attempts have been to create new measures for col_b and col_c
For example for col_c
not_working_meas_c = calculate(my_table[col_c], my_table[col_a] = [meas_a])
However this is incorrect DAX.
The below does work, but it gives the sum, a single value, whereas I need a value for each row from the filtered table to go into the time series chart:
unhelpful_meas_c = calculate(sum(my_table[col_c]), my_table[col_a] = [meas_a])
It seems like a very simple use case. If you know R, the answer would simply be:
r_meas_c = my_table[col_a == meas_a]$col_c
HI @costing,
Measure expressions are calculated based on their row contents and group. If you want to invoke the specific calculation results in other measure formulas.
It should be better to create variable with summarize function to reproduce the current row contents structures and you can invoke the measure in this variable table.
Reference link:
Measure Totals, The Final Word
Regards,
Xiaoxin Sheng
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