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Here is the new weekly challenge. The link to the solution for last challenge is HERE. For this challenge let’s look at ranking records when multiple records can have the same rank. The objective is to determine the top 5 ranking based on the count, however since there are multiple rows with same count (similar to a round of golf) multiple people can be in the same place (Rank) if they have the same score.
We have listed this as a beginner challenge and I expect it will go very quickly for many of you. Let us know what you think, we are looking forward to hearing your feedback.
UPDATE 1/25/2016
The solution has been uploaded.
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Hi Maveryx,
A solution to last week’s challenge can be found here.
Welcome to the third and final lap of our Weekly Challenge based on the Inspire 2024 Grand Prix! As we reach the climax of this thrilling journey, we are excited to present a challenge on predictive analysis. This topic, not often featured in Weekly Challenges, promises to push the boundaries of creativity. Get ready to dive deep and showcase your predictive analytics expertise!
Your task is to build a model to predict the top three podium finishers and compare the predicted versus the actual Silverstone podium finishers, and then identify the predicted racer who was not an actual podium finisher.
Use only driver race averages for full races, not qualifiers in Japan, Qatar, and Qatar Sprint to train the model. Use the model you built to score any drivers with full race data from Silverstone and determine the three most likely podium finishers. Then, identify any of those three drivers who did not actually make the podium at Silverstone.
Minimum lap counts per race to determine full race data:
Japan: 53
Qatar: 57
Qatar Sprint: 19
Silverstone: 52
The tasks to accomplish your objective include:
Create a training dataset using the Race Data Japan_Qat_Quali_Sprint dataset for your model. Be sure to exclude qualifying races and drivers who did not complete a full race using the minimum lap counts above.
Using this training dataset, build a Logistic Regression to estimate the likelihood a driver will finish in the top three on the podium.
Use any Avg variables as possible predictors and nothing else.
Use a Stepwise tool with the default configuration to determine the best predictor variables. The Stepwise tool will automatically determine the final model variables for the model.
Score any Silverstone drivers with full race data using the Stepwise output and identify the top three most likely podium finishers.
Compare the predicted podium finishers versus the actual Silverstone podium finishers. Find the predicted driver who did not finish on the actual podium.
Feel free to use the hints provided within the workflow.
Need a refresher? Review the following lessons in Academy to gear up.
Predictive Modeling
Predictive Analytics Fundamentals
Creating a Predictive Model
Good luck!
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Hi Maveryx,
We posted the solution JSON file to Cloud Quest #8. Check it out and let us know what you think! Send suggestions to academy@alteryx.com or leave a comment below!
Let’s dive into this week's quest!
Upload the provided Cloud Quest 9 - Start File.json file into your Analytics Cloud library.
The necessary datasets are pre-populated in the Text Input tools.
For more detailed instructions on how to import and export Designer Cloud workflow files, check out the pinned article Cloud Quest Submission Process Update.
Scenario:
In this week’s quest, a general contractor needs your assistance assessing his business using date-time analysis.
Bob, who had been working as a home builder, decided to transition his business towards leasing construction equipment. Among other equipment, he has two cranes he has been leasing for a while. He wants to get a better idea how his crane leasing business has been going.
Create a workflow that will show how many days both of his cranes have been leased at the same time during the years 2016-2018, the only years where he has a full set of data for both cranes.
Hint: In Designer Desktop, the Generate Rows tool would be the most efficient way to tokenize records within a date range. Unfortunately, the Generate Rows tool is not yet available in Designer Cloud (coming soon in 2024!), but you can still solve this quest thinking outside the box with a cartesian join from the Append Columns tool.
A combination of the Summarize, Filter, Append Columns, Formula, and Sample tools should solve your problem, but not necessarily in this sequence.
If you find yourself struggling with any of the tasks, feel free to explore these interactive lessons in the Maveryx Academy for guidance:
Getting Started with Designer Cloud
Building Connections in Designer Cloud
Building Your Workflow in Designer Cloud
Once you have completed your quest, go back to your Analytics Cloud library.
Download your workflow solution file.
Include your JSON file and a screenshot of your workflow as attachments to your comment.
Here’s to a successful quest!
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Hi Maveryx,
A solution to last week’s challenge can be found here.
Welcome to the second lap of our Weekly Challenge based on the Inspire 2024 Grand Prix. Get ready to dive deeper into this challenge and showcase your spatial skills!
The Silverstone racetrack owners offered McLaren some space inside the track for their VIP area. Using the provided Silverstone racetrack spatial object and data for the point that represents the finish line, your job is to find a zone within the interior of the track that meets the following location and capacity requirements. Then, calculate how many seats will fit in that VIP zone.
Requirements for the VIP zone:
Only areas inside the track should be considered, and for safety reasons, the edge of the VIP zone cannot be within 10 meters (0.01 kilometers) of the track.
For optimal viewing, the VIP zone should be within a 100-meter (0.1-kilometer) trade area of the finish line.
VIPs should have a maximum capacity of 1 person per 10 square meters of space.
What is the total number of VIP seats (no partial people allowed) that McLaren can fit inside the designated VIP zone?
Hint: Once you calculate square kilometers available within the constraints, multiply that by 1,000,000 to get square meters, divide that by 10, and round down to the nearest whole number to determine the number of VIP seats available.
Feel free to use the hints provided within the workflow.
Need a refresher? Review the Spatial Lessons in Academy to gear up.
Good luck!
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Hi Maveryx,
We posted the solution JSON file to Cloud Quest #10. Check it out and let us know what you think! Send suggestions to academy@alteryx.com or leave a comment below!
Let’s dive into this week's quest!
Download and extract the provided ZIP file containing your starting data and workflow files.
Upload the provided Cloud Quest 11 - Start File.json file into your Analytics Cloud library.
Reconnect the provided NY Times Data.csv dataset to your starting workflow file.
For more detailed instructions on how to import and export Designer Cloud workflow files, check out the pinned article Cloud Quest Submission Process Update.
Scenario:
In today’s Cloud Quest, you will find a dataset containing the titles, key words, and other data for all New York Times articles published from January 1, 2020, to December 31, 2020.
Your first task is to identify which day of the week has the highest number of articles published in the Sports section.
Your second task is to identify how many times the word "Football" or "football" appears in the headline or keywords on the day of the week with the highest number of articles published in the Sports section.
In your result, write a statement similar to this:
The word football appears [number] times in articles published in the Sports section on [day of week]s.
Hint: Unlike Designer Desktop, the Text To Columns tool in Designer Cloud requires the backslash character (\) to be used to escape values within strings. White space characters can be escaped with a backslash as they are in RegEx syntax. You can find more information in the Delimiters field in the Text To Columns tool's Configuration window.
A combination of the Filter, Summarize, Formula, Text To Columns, and Join tools should solve your problem, but not necessarily in this sequence.
If you find yourself struggling with any of the tasks, feel free to explore these interactive lessons in the Maveryx Academy for guidance:
Getting Started with Designer Cloud
Building Connections in Designer Cloud
Building Your Workflow in Designer Cloud
Once you have completed your quest, go back to your Analytics Cloud library.
Download your workflow solution file.
Include your JSON file and a screenshot of your workflow as attachments to your comment.
Here’s to a successful quest!
... View more