Community Spring Cleaning week is here! Join your fellow Maveryx in digging through your old posts and marking comments on them as solved. Learn more here!

Weekly Challenges

Solve the challenge, share your solution and summit the ranks of our Community!

Also available in | Français | Português | Español | 日本語
IDEAS WANTED

Want to get involved? We're always looking for ideas and content for Weekly Challenges.

SUBMIT YOUR IDEA

Challenge #109: Women in Government Around the World

Jonathan-Sherman
15 - Aurora
15 - Aurora

Challenge 109 is done!

 

Spoiler
challenge 109 JMS solution.PNG
mbogusz
9 - Comet

There would be different results if countries w/ nulls in 1997 have a history we're looking for and have been filtered out.

 

Spoiler
2019-09-27 12_19_09-Greenshot.png 

 

T_Willins
14 - Magnetar
14 - Magnetar

My solution

 

Spoiler
Workflow 109.JPG

 

KMiller
8 - Asteroid

Solution attached.

Spoiler
10-10-2019 09-28-09.png
dhtay
8 - Asteroid

A nice data prep challenge! I ran into some pitfalls with the multi-row formula tool. Would have gotten it within 15 minutes otherwise.challenge109.PNG

justindavis
10 - Fireball
Spoiler
challenge_109_solution_justindavis.PNG
dsmdavid
11 - Bolide

Can finally attach files, although cannot edit my previous reply

RoDO
8 - Asteroid

My solution

 

Spoiler
challenge_109_RODO_Solution.png
SueDonim
8 - Asteroid

Good one and quite relevant to some stuff I need to do for work.  I beat my head against the wall for about 20 minutes trying to see why my answer didn't match yours, when I found I had filtered on "<2" instead of "<=2"....

 

Spoiler
The directions pretty well defined the process I followed:
- Transpose data to put the years into columns
- Filter out data not between 1997 and 2017
- Count instances where data is null
- Filter out those that provided no data (I think the directions were a bit unclear as to whether any missing data should be filtered out vs those that never provided data - I assume it meant include them if they ever provided data and exclude them if they never did (that is, 21 nulls)
- Set missing records equal to prior record (with grouping by country)
- Join with other input data to get region and income group
- Determine if percentage declined year over year and filter out countries those that declined more than twice
- Cross-tab to put data back into columns
- Calculate difference between 2017 and 1997 (or use 2017 for difference if 1997 is null)
- Sort descrneding
- Determine top 3 for each income group

MySolution.PNG
sachinw
8 - Asteroid

My Solution: