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A solution to last week’s challenge can be found here.
Welcome to the Good Ladies weekly challenge!
Five women heist a jewelry store and steal a precious gem in the shape of a ball of yarn.
In the dataset, the 5 women responsible for the heist have been negligent and left clues behind. You are the detective on the case who is looking for these clues in a dataset.
1. Fingerprints on the glass surrounding the gem show fingerprints belonging to someone with the letters "Fled" in their first name or last name.
2. IT Department at the police is able to find that the back door lock password was changed to "ugfsjsh".
3. The vault holding the gem was blown open with "dynamic" dynamite. Found in the ruble is a business card piece. You can make out the first few letters of the word "Bogi"
4. The security guard's witness statement states that he has been vigilant about watching the store. There was only one instance last week when he was distracted by a woman with brunette hair who worked at a wireless store. He remembered later that she'd dropped a handkerchief that had the initials B.K. on it.
5. A slogan was left behind that said, "Those that synergize together can accomplish much and receive the TORPHY."
First, you will have to parse the data.
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A solution to last week’s challenge can be found here.
The Eurovision Song contest or Eurovision is an annual song competition in Europe.
During a live show, contestants representing European countries, sing a song and receive points. The contestant with the most points wins. In 1974, the Swedish group ABBA became a household name in Europe by winning this contest with the song "Waterloo".
The dataset for this challenge provides information about the Eurovision from 1975 to 2019. The column “Edition” contains a date followed by one or two initials “f” or “fs”. For this challenge, use the values followed by “f”.
Use the dataset to: - Find out which country has won the contest from 1975 to 2019 - List by descending order the countries who have won the most time between these dates
Hint A country cannot give points to its representative. Make sure to take this rule into consideration. Mistakes happen in datasets.
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A solution to last week’s challenge can be found here. Source: https://www.dailymail.co.uk/news/article-4965690/Humpback-whale-breaches-Sydney-Harbour-sunset.html
Every year whales around the world migrate from their feeding grounds to their breeding grounds. Some species travel an outstanding 12,000 miles round trip!
Use the data sets below to analyze migration movements for different whale species.
The file Whale_Migration_Data contains a list of whales whose migration patterns have been tracked from 2001-2003, and the total kilometers each whale swam on each day of their migration.
The file Whale_Pods contains a list of whale ids and pod ids, which indicates the pod each whale belongs to.
The file Whale_Species contains information about the whale species of each pod.
Find the total number of kilometers each pod swam for migration for each year, then find the average number of kilometers each whale in that pod swam (total kilometers / number of whales in the pod). Then, find the pod with the highest average kilometers swam per whale for each species for each year.
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With another Alteryx Inspire behind us, we wanted to share a workflow from a session in the Community Track: 'Born to Solve - Think Like an Alteryx Champion'
In this session, @patrick_digan presented a analytical challenge to @estherb47 sight-unseen! The intent of the session was to show more than solving a problem, but show attendees how some of the top challenge leaders approach and think about problems. Would you like to try it yourself? See below!
THE CREW
Challenge
Suppose you have 3 ordinary dice (6 sides with the numbers 1-6). You roll all 3 dice and compute the score like so: Multiply the largest number by the second largest number. Then add the remaining number. Given this unique method of scoring, which is the most likely score?
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The solution to last week's challenge can be found HERE.
Determine the items of clothing that have the highest average rating. In your analysis, include 1) only items of clothing that have at least 10 positive feedback reviews and 2) the five highest rated clothing items from each class.
The original data and its metadata can be found here.
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