Fabric is Generally Available. Browse Fabric Presentations. Work towards your Fabric certification with the Cloud Skills Challenge.
Hello,
For some time now I am strugling with measure that will count orders based on their last status.
I tackled this from multiple angles and even ask ChatGPT for help, but couldn't find a solution.
My goal is table visualization with columns for:
names of statuses in first column (STATUS_DICTIONARY[NAME]),
number of orders which have given status as their latest,
% of GT
My model looks like this:
ORDERS[ID] - 1 to * - ORDERS_STATUS[ID_ORDER]
STATUS_DICTIONARY[ID] - 1 to * - ORDERS_STATUS[ID_STATUS]
And below is some sample data:
ORDERS
ID | NUMBER |
1 | 23/01/1 |
2 | 23/01/2 |
3 | 23/01/3 |
4 | 23/01/4 |
5 | 23/01/5 |
ORDERS_STATUS
ID | ID_ORDER | ID_STATUS | DATE_CHANGE |
1 | 1 | 1 | 26.09.2023 |
2 | 1 | 2 | 26.09.2023 |
3 | 2 | 1 | 26.09.2023 |
4 | 3 | 1 | 27.09.2023 |
5 | 4 | 1 | 27.09.2023 |
6 | 1 | 3 | 27.09.2023 |
7 | 2 | 5 | 28.09.2023 |
8 | 3 | 2 | 28.09.2023 |
9 | 3 | 3 | 29.09.2023 |
10 | 5 | 1 | 30.09.2023 |
11 | 4 | 2 | 30.09.2023 |
STATUS_DICTIONARY
ID | NAME |
1 | aaa |
2 | bbb |
3 | ccc |
4 | ddd |
5 | eee |
Based on all above I expect result to look like this:
STATUS NAME | NUMBER OF ORDERS | % OF GT |
aaa | 1 | 20% |
bbb | 1 | 20% |
ccc | 2 | 40% |
ddd | 0 | 0% |
eee | 1 | 20% |
I will be very gratefull for any help.
Thank you!
Solved! Go to Solution.
@Maciej1992 , here are the measures:
orders_amt =
VAR t =
FILTER (
ORDERS_STATUS,
VAR order_id = CALCULATE ( SELECTEDVALUE ( ORDERS[ID] ) )
VAR maxDt =
CALCULATE (
MAX ( ORDERS_STATUS[DATE_CHANGE] ),
ORDERS_STATUS[ID_ORDER] = order_id,
ALL ( ORDERS_STATUS )
)
VAR maxStatus =
CALCULATE (
MAX ( ORDERS_STATUS[ID_STATUS] ),
ORDERS_STATUS[DATE_CHANGE] = maxDt,
ORDERS_STATUS[ID_ORDER] = order_id
)
RETURN
ORDERS_STATUS[ID_ORDER] = order_id && ORDERS_STATUS[ID_STATUS] = maxStatus
)
RETURN
COUNTROWS ( t )
% OF GT =
VAR latestRows = [orders_amt]
VAR allrows =
CALCULATE (
SUMX ( VALUES ( STATUS_DICTIONARY[NAME] ), [orders_amt] ),
ALL ( STATUS_DICTIONARY[NAME] )
)
RETURN
latestRows / allrows
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly. Appreciate your Kudos.
Check out my latest demo report in the data story gallery.
Stand with Ukraine!
Here are official ways you can support Ukraine financially (accounts with multiple currencies):
1) Support the Armed Forces of Ukraine: https://bank.gov.ua/ua/about/support-the-armed-forces
2) Come Back Alive foundation: https://www.comebackalive.in.ua/
Thank you!
@Maciej1992 , here are the measures:
orders_amt =
VAR t =
FILTER (
ORDERS_STATUS,
VAR order_id = CALCULATE ( SELECTEDVALUE ( ORDERS[ID] ) )
VAR maxDt =
CALCULATE (
MAX ( ORDERS_STATUS[DATE_CHANGE] ),
ORDERS_STATUS[ID_ORDER] = order_id,
ALL ( ORDERS_STATUS )
)
VAR maxStatus =
CALCULATE (
MAX ( ORDERS_STATUS[ID_STATUS] ),
ORDERS_STATUS[DATE_CHANGE] = maxDt,
ORDERS_STATUS[ID_ORDER] = order_id
)
RETURN
ORDERS_STATUS[ID_ORDER] = order_id && ORDERS_STATUS[ID_STATUS] = maxStatus
)
RETURN
COUNTROWS ( t )
% OF GT =
VAR latestRows = [orders_amt]
VAR allrows =
CALCULATE (
SUMX ( VALUES ( STATUS_DICTIONARY[NAME] ), [orders_amt] ),
ALL ( STATUS_DICTIONARY[NAME] )
)
RETURN
latestRows / allrows
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly. Appreciate your Kudos.
Check out my latest demo report in the data story gallery.
Stand with Ukraine!
Here are official ways you can support Ukraine financially (accounts with multiple currencies):
1) Support the Armed Forces of Ukraine: https://bank.gov.ua/ua/about/support-the-armed-forces
2) Come Back Alive foundation: https://www.comebackalive.in.ua/
Thank you!
Worked like a charm! Thank you very much. You truly are a Rockstar 🙂
Check out the November 2023 Power BI update to learn about new features.
Read the latest Fabric Community announcements, including updates on Power BI, Synapse, Data Factory and Data Activator.