Alteryx Academy

Hello Community Members,   A solution to last week’s challenge can be found here.    The third challenge of our Weekly Challenge User Group October Takeover was submitted by Talia Sanders (@tsand22)  from the Indianapolis User Group. Thank you, Talia, for contributing this fantastic challenge!   Did you know that every October the American Society for the Prevention of Cruelty to Animals (ASPCA) sponsors and promotes Adopt a Shelter Dog Month? This challenge helps raise awareness for the countless dogs in overcrowded shelters waiting for a loving home. Let’s highlight these wonderful pets and promote adoption!   Your task this week is to use the provided dataset with information on animals brought into the Dallas, Texas Animal Shelter for fiscal year 2022–2023 to:   1. Determine the number of dogs surrendered by their owners each month for the first nine months of 2023. Hint: Consider the Intake Date column.   2. Identify the top three dog breeds surrendered to the shelter.   3. Calculate how many dogs have been adopted from the shelter. Hint: Consider the Outcome Type column.   Happy solving!   Data Source: https://www.dallasopendata.com/Services/Dallas-Animal-Shelter-Data-Fiscal-Year-2022-2023/f77p-sgrc/data_preview ... View more

  Hello Community Members,   A solution to last week’s challenge can be found here.    We are wrapping up the October Takeover event with this fourth challenge submitted by Akimasa Kajitani (@AkimasaKajitani)  from the Tokyo User Group. Huge thanks to Aki for this fantastic challenge and his contributions to the Tokyo User Group.   For this week’s challenge, your task is to highlight the impressions people have of Jupyter Notebook, one of the most widely used Python development environments in data science. Many of you may already be familiar with it, especially since it is integrated into the Python tool in Alteryx Designer.   Your challenge is to analyze survey results on Jupyter Notebook usage. The data provided includes responses, but there is a twist—some survey entries are incomplete, and you need to remove them, also all the questions and answers are merged into a single cell in Excel.   To solve this challenge, your first step is to organize the responses to Questions 1 through 10 into a table. Then, complete the following tasks: Calculate the median, maximum, and minimum time (in minutes) that respondents took to complete the survey. Determine the count and percentage of respondents who use Jupyter Notebook regularly. Hint: Use the frequency labels from the question How often do you use Jupyter Notebook? Analyze responses to Question 7 to identify the top five words used by respondents to best describe Jupyter Notebook.   Happy solving!   Data Source: https://data.world/technology/jupyter-notebook-ux-survey Note: The format of this data has been modified to meet the objectives of this challenge.   The Academy Team ... View more

  Hi, Team Maveryx!   A solution to last week’s challenge can be found here.    It is that time again—the Superbowl is just around the corner! To get ready, grab your favorite snacks, call over some friends, and dive into some football stats. A big shoutout to Kenda Sanderson (@kenda) for bringing us this fantastic challenge!   The Superbowl is about the best of the best! You will use the provided Fantasy Football dataset to determine which positions typically have the best rank and how that has changed over time.    Complete the following tasks to solve this challenge:   Determine the five positions (POS) with the lowest overall rank (RK) for all years. Create a line graph and a table that clearly show the fluctuation in rank over time, specifically for those five positions.   Let's discover what fascinating insights you can extract from this challenge!   If you need a little help, you can review these lessons in Academy:   Connecting to Multiple Sheets at Once Changing Data Layouts Multi-Row Formula Reporting in Designer (all lessons)   Source: https://fantasydata.com/nfl/fantasy-football-leaders?season=2018&seasontype=1&scope=1&subscope=1&startweek=1&endweek=1&aggregatescope=1&range=1   ... View more

  Hello, Community Members!   A solution to last week’s challenge can be found here.   Financial analysts often need to consolidate data from various sources. This week's challenge focuses on using Alteryx functions in financial planning and analysis (FP&A) projects.   The first dataset includes sales information for various countries and business segments for the years 2022 and 2023, with the sales figures recorded in each country’s local currency. The second dataset provides the conversion rates from the countries’ currencies to euros.   Your first task is to create a final table that includes the segment, region, and total sales in euros for both 2022 and 2023. (Tip: Remove any columns where the sale price is null.) For the second part of the challenge, calculate the year-over-year variation per segment (2022–2023) and identify the segments that experienced negative variations across all three regions: Europe, Asia Pacific (APAC), and the USA.   Need a refresher? Review the following lessons in Academy to gear up: Summarizing Data Changing Data Layouts Happy solving!   The Academy Team ... View more

Aggregate Consumer Purchases: For this week’s exercise we will look at customer purchase behavior to decide if we should offer a “Meal Deal” that would add a side and drink to a purchase of pizza or a burger. The incoming data is larger than usual for these exercises so I have packaged the workflow as an Alteryx Package. The link to the solution for last challenge #7 is HERE.   This week’s Objective: In order to decide if we should start including a new "Meal Deal" on our menu we want to study the potential impact on recent transactions. Please identify the number and percentage of orders since July 1, 2013 which include the following categories of food: Pizza OR Burger along with a Side and Drink.   Summary of Data: Point of Sale data includes the ticket level information, and the lookup table categorizes items into higher level food categories.   Hint: Don't forget to join to the lookup table and filter by date.   As always we look forward to your feedback and suggestions!   UPDATE 01/18/2016: The solution has been uploaded.   UPDATE 12/28/2016: The challenge, text and solution have been updated. ... View more