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A solution to last week’s challenge can be found here.
Are you wondering which artists produced the top songs? Do you want some insights? This challenge is for you.
The following dataset contains information about the top 500 songs. Using the dataset, find the top 50 artists with the most albums and the highest average rating. Include the following columns in your list :
- Artist(s) - Number of albums (Descending) - Average rating based on all albums (Descending) - Album title(s) - Average number of reviews based on all albums (Descending) - Genre(s) - Year the first album was released - Year the last album was released
Note: If in your solution you have null records for the Release Year, do not include them.
This challenge was updated to propose 2 start files and 2 solutions.
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A solution to last week’s challenge can be found here.
Welcome to Hollywood!
Your production company just signed a contract to work with a very successful director on her next film. You met her for lunch to talk about the movie and took notes.
Use the dataset and your notes to figure out who the best choices are for the top three actors to cast in the movie, the ideal film location, and the expected revenue of the movie.
Notes - Who is the most popular actor in the comedy that generated the most revenue? - Who is the most popular actor in the action movie that generated the most revenue? - Which actor appeared in the comedy or action movie that generated the most revenue? This will also give you the ideal film location. - What is the expected revenue of this movie based on the average revenue of the last movie each of the three actors worked on?
Hints - To be in this movie, the actor must have a diva score. - The lower the diva score, the easier the actor is to work with. - The higher the diva score, the more difficult the actor is to work with.
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A solution to last week’s challenge can be found here.
This challenge comes to us from @AkimasaKajitani . Thank you for your contribution, Aki!
Meteorite showers are a captivating natural phenomenon, though it can be challenging to see them depending on your location. Fortunately, residents and visitors in the Las Vegas area enjoy an advantageous position, being in proximity to expansive desert skies that offer excellent conditions for meteorite watching.
For this challenge, your mission is to plan a budget-friendly meteorite impact site tour near Las Vegas, ensuring enthusiasts visit locations where they have the best opportunity to witness this celestial spectacle.
Here are the tasks you must complete. Calculate all distances in kilometers.
Find a meteorite impact site that is closest to a hotel that costs less than $200 per night. Designate this location as the "First Stop."
Identify the nearest meteorite impact site in relation to the First Stop. Label this site as the "Second Stop" and determine the distance between the first and second stops.
Locate the nearest meteorite impact site in relation to the Second Stop. Name this site “Third Stop” and determine the distance between the second and third stops.
Calculate the total distance traveled from the hotel to the third stop.
Data Summary:
You have two datasets. The text dataset contains the latitude and longitude of some hotels in Las Vegas with their cost per night. The second dataset, meteorite-landings.csv, contains the latitude and longitude of over 45,000 meteorites that have struck our planet.
Source: https://www.kaggle.com/datasets/nasa/meteorite-landings
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Here is this week’s challenge, I would like to thank everyone for playing along and for your feedback. The link to the solution for last challenge #16 is HERE. This week’s assignment is listed as an advanced exercise due to the requirement of using a batch macro for the solution.
The use case: A bank is looking to calculate customer retention rate month over month. The denominator in the calculation are all of the accounts open 24 months prior to the start of the month. For example, for June 2013, the denominator would be the total number of accounts open between June 1, 2011 through May 31, 2013. The numerator will be total number of accounts closed in June 2013 or between June 1, 2013 through June 30, 2013.
The objective is to create a batch macro that calculates the retention rate for May, June, July and August.
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I'm excited to present to you Lap 1 of the 2018 US Grand Prix! If you were at Inspire in Anaheim with us in June, you saw our 3 finalists (@BenMoss, @mattagee, @NicoleJohnson) solve this workflow in front of roughly 3000 Alteryx users and fans.
Tackling this workflow won't compare to the experience our finalists had, but it will give you a glimpse into what it takes to compete in the Grand Prix. To make it more life-like, I suggest doing the following.
1) Open up the workflow and give yourself 2 minutes to read the prompt - don't touch the mouse!
2) Time yourself - the drivers had a maximum of 12 minutes to finish.*
3) To take it to the next level, invite your friends and neighbors over, provide them food and drinks, and put on some headphones as you solve.
*At Inspire, the journey did begin by the drivers having to find the data in Alteryx Connect - I've provided the data for you in the workflow.
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