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Here is a new challenge for this week. The link to the solution for last week’s challenge is HERE.
The use case:
We received some text data and that includes an embedded line-feed character.
The objective is to remove the new line character, convert the date-time string to a date-time formatted field and then do some renaming per the sample output.
Good luck, I look forward to your feedback.
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Hi Maveryx,
A solution to last week’s challenge can be found here.
Ellen Wiegand, a Senior Sales Engineer at Alteryx, brought us this brilliant challenge idea. We are truly grateful for your contribution, Ellen!
Considering the importance of renewable energy and to celebrate Earth Day, let's work on a challenge regarding sustainable energy! We have a dataset that provides detailed information about wind towers in the United States and its territories. The text input file contains the latitude and longitude coordinates for Alteryx headquarters in Irvine, California.
Looking only at wind towers with an Attribute Confidence of 3 and Projects with more than one wind tower, complete the following tasks. (Note: The Column Descriptors tool container in the workflow file contains the definitions of the values in the input dataset.)
What is the name of the project closest to the Irvine office (CA)?
How far away from the office is it?
Hint: The provided dataset is a flat file. To facilitate the data extraction, use the JSON Parse tool in the Developer tab of Designer.
Need a refresher? Review these lessons in Academy to gear up:
Parsing JSON
Creating Spatial Objects
Changing Data Layouts
Sources:
https://evwhs.digitalglobe.com
http://www.google.com/earth/download/ge/
http://datagateway.nrcs.usda.gov/
Good luck!
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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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For the fourth challenge let’s look at parsing Dates from text strings. To view the previous challenge, click HERE.
A dataset contains a text field that has a date embedded within the text. The problem is that the date is represented a few different ways. For example:
16-APR-2005
Nov•16,•1900
4-SEP-00
Jan•5•2000
The goal is to create a new Date/Time field populated with the dates contained within the text field. You will also need to standardize the dates so that they are all formatted the same.
We have listed this as an advanced exercise since parsing out the dates can be challenging depending on the technique you employ to do it. As always, we love to hear your comments. Have fun!
UPDATE 12/7/2015:
The solution has been uploaded
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At Inspire Europe this week? Join the session "Amplify your Learning with Weekly Challenges" in Little Gallery at 11:15 to solve this challenge in a group learning session!
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