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
Weekly Challenge #292
This challenge is about pivoting, preparing, and reporting data.
This dataset lists information about local soccer team players, including an ID number, the group, the team they belong to, and the region from which they come.
Use the following dataset to:
• Pivot the data to show the count of the IDs for each group based on the region and respective team.
• Arrange and prepare the data so that the number of players in each group is listed under each region and team
• Create a report that illustrates the data you arranged in the previous step
C:\Users\Philip\AppData\Local\Temp\Engine_20692_aa5f122f311f466fa960d99bf4283728_\Engine_2680_bfd9aced2e2a40e784ffc495174a1b44_.yxdb
Single
Report
Challenge 292 - Data.yxdb
Challenge 292 - Data.yxdb
C:\Users\Philip\AppData\Local\Temp\Engine_20692_aa5f122f311f466fa960d99bf4283728_\Engine_2680_fb740ddc4b464a62b3078b818671d34e_.yxdb
Single
Report
Challenge 292 - Output.yxdb
Challenge 292 - Output.yxdb
Simple
Contains
REGION
True
fixed
2021-11-01 14:41:39
0
region
2021-11-01 14:41:39
2021-11-01 14:41:39
Contains([REGION],"region")
Warning
All
ByName
REGION - Ascending
TEAM - Ascending
Basic
100%
Formula
Data
TEAM
==
1
CONTAINS(Team, 'Region')
Subtotals
Formula
Data
==
1
contains([Team], 'Total')
Totals
Basic Table
Horizontal
Challenge 292 - Pivoting, Prepping and Reporting