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Here is a new challenge for this week, it is a two part challenge so next week’s challenge will be a continuation. The link to the solution for last week’s challenge is HERE.
This week we are looking at a retail distribution analysis. We need to allocate products from the warehouse to stores based on priority. I have seen this challenge solved both with and without the use of an iterative macro.
The use case:
A retail chain has 25 stores carrying variety of items. Not every store carries the same items and each has its own level of prioritization within the chain and different required stock levels. There is a central warehouse that contains all of the available items.
The objective is to distribute items from the warehouse to each store, filling the available stock at each store in order of the store's priority.
Good luck, I look forward to hearing your feedback. Thank you for playing along.
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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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Hi Maveryx,
A solution to last week’s challenge can be found here.
Are you enjoying the new Weekly Challenge page? We hope you've had a chance to read our blog post explaining the exciting new features we've introduced in this latest version. We'd love to hear your thoughts, so please leave us a comment with your feedback!
This week's challenge, created by Motoi Tokimatsu, will test your RegEx skills! Thank you, @Tokimatsu , for presenting this intriguing task.
Have you heard about the 850 words of Charles Kay Ogden's Basic English? (In this context, the acronym BASIC stands for British American Scientific International Commercial.) In his book published in 1930, Basic English: A General Introduction with Rules and Grammar, he created a list of about 850 words to form the core vocabulary of Basic English. Basic English aims to create an easier and more efficient form of English for international communication, particularly for those learning English as a second language. The reduced vocabulary is designed to cover most everyday situations and needs without the complexity of the full English language.
Your tasks for this challenge include:
Download the data from the URL provided.
List the words (around 850)
Create an index with the first letter of each word.
Calculate the number of words that start with each letter of the alphabet.
In this challenge, the Replace and Tokenize functions in RegEx will be your best friends.
Need a refresher? Review the following lessons in Academy to gear up:
Replacing Data with RegEx
Splitting Data with RegEx
Good luck!
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A solution to last week's challenge can be found here.
Using the provided dataset, calculate the average hotel stay and count the number of hotel reservation IDs for all hotel reservations that were not canceled and at least one day in length.
Source: GIPHY
The solution file for this challenge was updated on June 24. 2022.
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Hi Maveryx,
A solution to last week’s challenge can be found here.
This challenge was submitted by Jifeng Qiu (@Qiu) and Motoi Tokimatsu (@Tokimatsu) , very engaged members of our Community.
Qiu and Tokimatsu, we appreciate your contributions to the Community!
In the Engineering, Procurement, and Construction (EPC) department of a chemical plant, equipment tags play a crucial role in managing equipment, including labeling pumps as distinct entities, such as P-101A and P-101B. The upstream Design department still prefers the old-fashioned way of creating tags and they usually concatenate tags into forms like P-101A/B or P-101A-B. This approach creates a headache for the downstream department's data processing.
Your task this week is to parse these concatenated equipment tags, making life smoother for everyone involved. Ensure the new tags start from the first letter and end with the last letter sequentially.
Create an Alteryx workflow to sequentially generate new equipment tags based on the provided dataset. For instance, if you have P-101A/E, the output should be P-101A, P-101B, P-101C, P-101D, and P-101E.
Embark on this adventure and untangle those equipment tags with precision and efficiency!
Good luck!
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