Dive deeper into solving problems with Alteryx, explore new frontiers in your analytics journey, and push yourself to prove and improve your skills with our Certification Program.
Dive into new analytics techniques with lessons that incorporate videos, hands-on activities and quizzes to assess your knowledge.
Also available in...
The solution to last week's challenge is HERE.
This week we will be offering our third ever challenge on converting strings to dates. Sometimes these may be simple, but every once in awhile, we come across those source systems that drop things in a format that are better understood by machine than by a human. In this week's challenge, convert the string to a date using the following rules:
1) The Input contains dates formatted as year, month, day where the first character details if the year begins with 19 or 20.
2) It is 19 when the first character is 0 and 20 when the character is 1.
3) The remainder of the date following the 0 or 1 is the remaining year digits followed by month followed by day.
Example: 1040202 should become 2004-02-02.
... View more
Hello Community Members,
A solution to last week’s challenge can be found here.
We are excited to kick off our series of Weekly Challenges submitted by User Group members! Over the next 4 weeks, we will be featuring challenges submitted as part of our Weekly Challenge User Group October Takeover event. Thank you to everyone who submitted their challenges!
The first challenge in this series comes from Jessica Emerson (@jessemers), a member of the Houston User Group. Thanks, Jessica, for this fantastic contribution!
The World Happiness Report polls over 100,000 people in over 130 countries annually to determine happiness rankings. The main life evaluation question asks respondents to think of a ladder, with the best possible life for them being a 10 and the worst possible life being a 0. They are then asked to rate their own current lives on that 0 to 10 scale (Ladder Score). The columns following the happiness score are variables based on observed data for six factors: economic production, social support, life expectancy, freedom, absence of corruption, and generosity. The report uses these variables to help explain the happiness ranking variation across countries.
The provided datasets include the World Happiness Report data for 2023 and 2024.
Your task is to use the provided datasets to answer the following questions:
Which year had the highest average happiness score?
For each year, which is the highest-scoring country with a gross domestic product (GDP) under 1?
Which five countries had the highest average generosity factor over the 2-year period?
Bonus task: How high is your country’s happiness score?
Happy solving!
Data Source: World Happiness Report Data Dashboard
The Academy Team
... View more
A link to the last challenge is HERE.
The knapsack problem:
There are 5 boxes of varying weights and dollar amounts - which boxes should be chosen to maximize the amount of money while still keeping the overall weight under or equal to 15 kg?
From a challenge standpoint, which combination of box/boxes is most optimal if you were only allowed 1 box in the backpack? 2 boxes in the backpack? 3 boxes in the backpack? or 4 boxes in the backpack?
Output 1: details the number of boxes and total $ without going over 15kg.
Output 2: details the specific blocks per batch.
I have included spatial objects as part of the input should you want to use a location optimizer macro as part of the solution. The new prescriptive simulation tools may also be a good choice for a solution. We are looking forward to seeing the solutions you come up with. Please don't feel constrained by the example output, your solution may be better! I am looking forward to seeing your solutions in this new more interactive forum.
... View more
Hello Community members,
A solution to last week’s challenge can be found here.
Thank you Ippei Nakagawa @gawa, for this week’s highly appropriate challenge!
Weekly Challenges have a long history with the number of Weekly Challenges published now totaling more than 450! Whether you have been solving challenges for a long time or are just starting out, it can be fun to analyze past Weekly Challenge statistics!
The provided dataset contains records of users who interacted with each Weekly Challenge through number 437 from November 2015 to August 2024. It includes posting dates and times, and the challenge number. Use this data to complete the following tasks:
Calculate how many days passed between the oldest and the most recent interaction date for all Weekly Challenge posts combined.
Determine the top 15 unique users who posted responses to the most Weekly Challenges from November 2015 to August 2024.
Feel free to mention the Top 15 users and express your congratulations when you post your solution!
Need a refresher? Review the following lessons in Academy to gear up:
Sampling Data
Summarizing Data
Good luck!
The Academy Team
Download Start File
Data Source: Datasets prepared using Community API.
... View more
Hi Maveryx,
A solution to last week’s challenge can be found here.
In April, we celebrate Earth Month, a time dedicated to raising awareness and taking action for environmental conservation and sustainability.
This weekly challenge delves into temperatures, highlighting their crucial role in our planet's health. The dataset presents comprehensive information on global temperature records, covering various countries worldwide. It includes average temperature records in Celsius for major cities from 1743 to 2013.
To solve this challenge, we will be concentrating on the data from 1950 onwards.
Your tasks are as follows:
Determine which cities have average temperatures greater than or equal to 25 degrees.
Among the cities identified in the previous task, identify the country with the highest number of such cities.
Examining all countries within the dataset, pinpoint the year with the highest average temperature and the year with the lowest average temperature across the globe.
Need a refresher? Review these lessons in Academy to gear up:
Sorting Data
Separating Data into Columns and Rows
Summarizing Data
Source: https://www.kaggle.com/datasets/maso0dahmed/global-temperature-records-1850-2022
Good luck!
... View more