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Challenge #277: 2016 Summer Olympics

dYoast
8 - Asteroid

I don't have the same results for average age, but I did include totals for all countries.

Trying a spoiler for the first time.

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dYoast_0-1626713034822.png

 

 

ggruccio
13 - Pulsar
13 - Pulsar

Used 8-5-2016 as the start date for the Rio Olympics.

 

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Fairly simple separate data calculations - brought back together at the end of the data stream.  ggruccio_0-1626714779837.png

 

achillesjing
7 - Meteor

Here is my solution

mike_w
8 - Asteroid

As a few others have mentioned - I also get results different from the solution provided. Using the CreW Expect Equal Tool reveals the issues, there's a handful or so errors: So for example it says there's a problem in row 23; checking the solution provided, row 23 is Bhutan with 2 Female Athletes, 0 (or [Null]) Male Athletes - and then [Null] Total Athletes!  That can't be right. 

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mike_w_0-1626721934626.png

 

Elias_Nordlinder
11 - Bolide

My solution, also get 5 records wrong because not correct value in output given as for other people.

 

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Elias_Nordlinder_0-1626723479681.png
Elias_Nordlinder_1-1626723497939.png

 

 

ryan-bush
Alteryx
Alteryx

Fun and timely challenge! '2016-08-05' for the age calculation is a useful tip

Michael_McKee
Alteryx
Alteryx

This was a fun one

phottovy
12 - Quasar

I don't think I'll make the podium for my time on this one.

 

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277.png
kelly_gilbert
12 - Quasar

I love these summary/fact-finding challenges! Like others, I had a couple of discrepancies in the total athlete counts likely due to null counts for one of the genders (I'm pretty sure my solution is correct).

 

Spoiler
My workflow:
kelly_gilbert_0-1626745062223.png

 


Differences from the solution:
kelly_gilbert_1-1626745150113.png

Fun fact: one of my colleagues is an athlete in this dataset!

Qiu
17 - Castor

Thanks for the tip from @Blake , be careful with the age.

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challenge_277.PNG