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Hello,
I have a table, "prem_incs", of the following form:
premise_number | incident_year | job_id |
100 | 2020 | 1 |
102 | 2020 | 2 |
104 | 2020 | 3 |
102 | 2020 | 4 |
106 | 2020 | 5 |
108 | 2020 | 6 |
106 | 2020 | 7 |
103 | 2020 | 8 |
105 | 2020 | 9 |
108 | 2020 | 10 |
102 | 2020 | 11 |
101 | 2020 | 12 |
105 | 2020 | 13 |
105 | 2020 | 14 |
109 | 2020 | 15 |
105 | 2020 | 16 |
103 | 2020 | 17 |
108 | 2020 | 18 |
107 | 2020 | 19 |
106 | 2020 | 20 |
I have created the following table variable, "first_grouping", which hopefully counts premise_number occurences by whatever year filter context is applied to it:
first_grouping = addcolumns(
groupby(
prem_incs,
prem_incs[incident_year],
prem_incs[premise_number]
),
"prem_counts", calculate(count(prem_incs[job_id]))
)
It produces a table like the following, which appears correct:
prem_counts | premise_number |
1 | 100 |
3 | 102 |
1 | 104 |
3 | 106 |
3 | 108 |
2 | 103 |
4 | 105 |
1 | 101 |
1 | 109 |
1 | 107 |
However, when I try to then group this table a second time by prem_counts, I don't seem to be able to achieve the result I'm seeking.
Here's the dax code that I've attempted:
overall_grouping =
var first_grouping = addcolumns(
groupby(
prem_incs,
prem_incs[incident_year],
prem_incs[premise_number]
),
"prem_counts", calculate(count(prem_incs[job_id]))
)
return addcolumns(
groupby(
first_grouping,
[prem_counts]
),
"bins", calculate(countx(first_grouping, [premise_number]))
)
Here's the result the dax returns:
prem_counts | bins |
1 | 10 |
2 | 10 |
3 | 10 |
4 | 10 |
And here's the result I desire:
prem_counts | bins |
1 | 5 |
2 | 3 |
3 | 1 |
4 | 1 |
What should I do differently to be able to perform this grouping? My goal is to ultimately to be able to use filters remove job_id values from consideration and then to dynamically recalculate the bin numbers per year for visuals.
Any and all help is appreciated; thanks!
(My goal for the output visual is someting like the following):
Solved! Go to Solution.
Hi,
I am not sure if I understood your question correctly, but please check the below picture and the attached pbix file.
It is for creating a new table.
New Table =
VAR _firstgroup =
ADDCOLUMNS (
SUMMARIZE ( prem_incs, prem_incs[incident_year], prem_incs[premise_number] ),
"@premise_count", CALCULATE ( DISTINCTCOUNT ( prem_incs[job_id] ) )
)
VAR _secondgroup =
GROUPBY (
_firstgroup,
prem_incs[incident_year],
[@premise_count],
"@countbins", SUMX ( CURRENTGROUP (), 1 )
)
RETURN
_secondgroup
If this post helps, then please consider accepting it as the solution to help other members find it faster, and give a big thumbs up.
Schedule a short Teams meeting to discuss your question
Hi,
I am not sure if I understood your question correctly, but please check the below picture and the attached pbix file.
It is for creating a new table.
New Table =
VAR _firstgroup =
ADDCOLUMNS (
SUMMARIZE ( prem_incs, prem_incs[incident_year], prem_incs[premise_number] ),
"@premise_count", CALCULATE ( DISTINCTCOUNT ( prem_incs[job_id] ) )
)
VAR _secondgroup =
GROUPBY (
_firstgroup,
prem_incs[incident_year],
[@premise_count],
"@countbins", SUMX ( CURRENTGROUP (), 1 )
)
RETURN
_secondgroup
If this post helps, then please consider accepting it as the solution to help other members find it faster, and give a big thumbs up.
Schedule a short Teams meeting to discuss your question
This solution worked perfectly for me - thank you for your help!
@Power_BI_User_ , You should use current group by
example
return
groupby(
first_grouping,
[prem_counts],
"bins", calculate(countx(CURRENTGROUP(), [premise_number]))
)
refer for options
https://medium.com/@amitchandak/power-bi-power-query-vs-dax-append-and-summarize-data-233f173d0839
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