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Description:
A solution to last week’s challenge can be found here.
Are you ready to further explore the cheesy dataset from Weekly Challenge #339?
This dataset provides information about the 2021 World Cheese Awards.
Your challenge is to: - Find the top 5 countries based on the number of categories entered and the average rating. - Determine which country had the highest average rating based on the previous question. - Find the country that has exactly 29 BRONZE ratings.
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A solution to last week’s challenge can be found here.
To solve this week’s challenge, use Designer Desktop, Designer Cloud, Designer Experience, or Designer Cloud, Trifacta Classic.
Over the years, Barbie, the doll made by Mattel, has had a lot of different jobs! She has been super busy. Did you know she ran for President of the United States 10 times? Quite impressive!
This dataset complies a list of Barbies that were released from 1959 through 2020. It includes the career name and type of career for that Barbie.
For this challenge, first determine which career Barbie had more than twice between the years 2017 and 2019.
Next, calculate by job type how many different types of jobs Barbie held over the years from 1959 through 2020, including the percentage of each.
Data Source: https://data.world/judkacag/barbies-careers-1959-2020
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A solution to last week’s challenge can be found here.
Are you ready to explore a cheesy dataset?
This dataset provides information about the 2021 World Cheese Awards.
Your challenge is to: - Find the category of cheese that has the highest average rating per category. Your answer must include the category number, the average rating, and the category name. - Find all the companies that have a perfect rating of 4 in the category they entered. Your answer must include the company name, the average rating , and the count.
Hints: You need to create a new rating system column based on the following: SUPER GOLD = 4 GOLD = 3 SLIVER = 2 BRONZE = 1
In addition, create 2 new columns, category number and category name, using information from the category column.
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A solution to last week’s challenge can be found here.
Congratulations, class of 2026!
For many new college students, now is the time to pay tuition for college, and sometimes their college decision is based on financial data.
This dataset contains information about private and public colleges in the US, where these institutions often offer different tuition for
in-state and out-of-state students.
Using the provided data: - Create a list of 4-year colleges by state that includes the total payment (tuition plus room and board) in 2020 for private colleges and public colleges for in-state and out-of-state students. - Find the top 10 schools that give the most significant discounts for in-state students.
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The solution to last week's challenge can be found HERE!
Just a note: Santalytics will take over Weekly Challenge the 3 weeks following this challenge. Let me say, it's gonna be exciting (an we secretly have been priming you with some of the more recent challenges)! Stay tuned next week to participate!
This week's challenge is taking advantage of the waning days of November and will bring out one last fall-themed challenge. This particular challenge was conceived, constructed and submitted by the distinguished @NicoleJohnson! Thanks Nicole!
Challenge:
You are promoting a new phone app called PIXL near the T-Mobile campus that tracks the Latitude/Longitude of the photos you take so that you can combine the pictures you've taken with a map of your route. You've given the app to some people in the area so they can test it out, and are tracking various phone data for analysis. Things were going well until about 12:50, when you ordered your favorite drink - a Pumpkin Spice Latte, extra pumpkin, of course - and were just about to sit down at your desk to enjoy your beverage, when you were suddenly pulled away to deal with an emergency logo situation... By the time you made it back 20 minutes later to where you'd left your latte on your desk, your treasured PSL was gone!!! Now you knew people were running all over the area testing out your new app, so you thought perhaps you might be able to use the data you were collecting from the testers to see if anyone in the area had seen your PSL thief...
Using the PIXL Data & image links below, see if you can identify the Pumpkin Spice Latte stealing culprit!!
HINTS: - Data file is structured with some concatenated information: DateTime (in 24-hour format), Phone Number, Latitude & Longitude where picture was taken, and some other qualifiers & delimiters.
- Data will need to be parsed first to find the relevant fields for analysis. - Assume that the thief probably couldn't have been farther than .25 miles from the location of the robbery during the time frame in question. - There will likely be more than one potential thief in the area once you've filtered your results for time & location proximity, so you'll also want to see the images from their PIXL app data in order to narrow down your search!
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