Hi There,
Aim: Create a Calculated Column that returns the value closest to the test date.
I have a 'Growth' table (Table 1) and a 'Sprint' table (Table 2). The growth table contains the a Bio Age value. I would like to append Bio Age into the Sprint table in order to figure out what a player's Bio Age was at the time they took a sprint test. A player could have undertake a sprint test at a different time to getting their measurements taken (which are stored in the Growth table). Therefore, I need to find the Bio Age of a player that has been recorded closest to the session date that the sprint test was undertaken.
Relationship: There is no relationship between the two tables as there are duplicate values within the two - which is why I thought LOOKUPVALUE may be the best method of finding the value. PlayerID is present in both tables.
Table 1 - Growth:
Player ID | Session Date | Height (cm) | Bio Age |
001 | 01/04/2019 | 130.7 | 8.8 |
001 | 18/06/2020 | 133.7 | 9.3 |
001 | 09/03/2021 | 134.9 | 9.7 |
Table 2 - Sprint:
Player ID | Session Date | Sprint Time - 5m | Bio Age |
001 | 01/05/2019 | 3.21 | ? |
001 | 10/05/2020 | 3.18 | ? |
001 | 24/05/2021 | 3.17 | ? |
Any help would be greatly appreciate. Many thanks in advance.
Solved! Go to Solution.
@heastham
Add the following column to the Growth Table:
Closest Bio Age=
var __player = Sprint[Player ID]
var __sprdate = Sprint[Session Date]
var __growth =
ADDCOLUMNS(
FILTER(
Growth,
Growth[Player ID] = __player
),
"diff", ABS(DATEDIFF(__sprdate , Growth[Session Date] , DAY ))
)
var __mindiff = MINX( __growth,[diff])
var __age =
MAXX(
FILTER( __growth, [diff] = __mindiff ),
Growth[Bio Age]
)
return
__age
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@heastham
Add the following column to the Growth Table:
Closest Bio Age=
var __player = Sprint[Player ID]
var __sprdate = Sprint[Session Date]
var __growth =
ADDCOLUMNS(
FILTER(
Growth,
Growth[Player ID] = __player
),
"diff", ABS(DATEDIFF(__sprdate , Growth[Session Date] , DAY ))
)
var __mindiff = MINX( __growth,[diff])
var __age =
MAXX(
FILTER( __growth, [diff] = __mindiff ),
Growth[Bio Age]
)
return
__age
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⚪ Website ⚪ LinkedIn ⚪ PBI User Group
How would you change the code if Player ID didnt exist?? and session date was just a numerical field and you had to look up and return the Bio Age based on the closest value to the numerical field?
So far so good! You my friend are a dream!
Thank you so much for your input 😀
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