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Hi Maveryx,
We posted the solution JSON file to Cloud Quest #5. 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 the provided JSON start file and upload it into your Analytics Cloud library. For more detailed instructions on how to import and export Designer Cloud workflow files, check out the pinned article .
Scenario:
This week’s quest revolves around data provided about standardized math exams administered in New York City Public Schools from 2013 to 2019. Download the provided district_math_results.csv dataset and reconnect it in your starting workflow file. Ensure that the Interpret Column Datatypes checkbox is not selected in the Input Data tool options. The dataset includes details on the district, grade, year, category (male/female); the number of students who took the test; and the percentage of students who achieved each level, with Level 4 being the highest.
You have two tasks:
Calculate the change, by district, in the percentage of 8th grade female students who achieved a Level 4 score in 2019 compared to 2013.
Identify the top three districts that showed the most significant improvement in the Level 4 percentage over the same period.
Hint: Configure the Cross Tab tool to create a new column based on the Year field, labeling the columns as Year 2013 and Year 2019. The Level 4 percentage should serve as the value for these columns, using the Use First Value method. Ensure the data is grouped by District.
A combination of the Sample, Filter, Cross Tab, Formula, and Select tools should solve your problem, but not necessarily in this sequence.
A combination of the Sample, Filter, Cross Tab, Formula, and Select 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 workflow screenshot as attachments to your comment.
Here’s to a successful quest!
Source: https://infohub.nyced.org/docs/default-source/default-document-library/2014-15-to-2022-23-nyc-regents-overall-and-by-category---public.xlsx
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Last week's challenge is posted HERE!
OK, I have a problem... for you to solve!
We are selling bottles of wine - each of which has a unique ID since it's a limited vintage.
Customers can request their wine bottles be delivered in various different sizes of delivery box.
Customers order wine in ranges - from ID 1 to 25 for example.
Challenge: Build a macro that takes in order ranges, allows the user to input the box size, and outputs the order broken into the requested box sizes.
There are 3 sample outputs displayed to test the different box sizes: - Box size of 6 - Box size of 12 - Box size of 96
The macro must check for, or prevent 3 specific error conditions: - a null value for either the from or to value on an order range - non-numeric values in the from & to values - situations where the from ID is greater than the to ID
BONUS - Instead of using an interface tool to allow the user to set 6/12/96 box sizes, build a batch macro that will package all three scenarios at once! DOUBLE BONUS - Complete this challenge whilst listening to some UB40
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This week we will run an anecdotal workflow to prove the Birthday Paradox! The Birthday paradox simply refers to the phenomenon that if you assembled 23 people into one room, the chances of two people having the same birthday are 50-50. We could 'math' this out, but why not just assembles 100s of thousands of people in the seconds to prove it?
In this challenge, your goal is to build a table that increment group sizes from 2 people all the way to 50 people. In each of those group sizes, run 1000 random trials and see what percent of groups had at least one set of people match. Why 1000? Theoretically, the more trials you run, the more likely you are to get a refined percent (e.g. flipping a coin four times may not a perfect 50-50 chance where it would be much closer after 1000 flips).
Due to the nature of this challenge, you will need to generate your own data! I have provided a sample output of mine, but since we are randomly assigning birthdays, you may find small differences in our answers. At what group size did it exceed 75% chance? 90% chance?
Looking to try the new interactive chart tool too?
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A solution to last week’s challenge can be found here.
To solve this week’s challenge, use Designer Cloud or Designer Desktop.
Haven’t heard about Designer Cloud yet? Watch a demo.
How often do you get to be the judge of a Pokémon video game tournament? How well do you know your Pokémons?
In this challenge, you will determine who qualifies as a Pokémon trainer for a tournament! Pokémon are virtual creatures living with human partners called “trainers.”
Let's introduce you to the concept of Pokémon types. Types are properties applied to Pokémon and their moves, which affect the power of moves in battles. There are 18 types: Normal, Fire, Fighting, Water, Flying, Grass, Poison, Electric, Ground, Psychic, Rock, Ice, Bug, Dragon, Ghost, Dark, Steel, and Fairy. A Pokémon may have either one or two types. For instance, Charmander is a Fire type, while Bulbasaur is both a Grass type and a Poison type. There are a total of 324 possible ways to assign types to a Pokémon.
To qualify as a trainer in the tournament, you must have at least eight Pokémon types total, ranging across your six-Pokémon roster. The dataset Pokemon trainers contains information on four Pokémon trainers and their six Pokémon. The dataset Pokedex contains information on all Pokémons from all generations, such as the type (or types) of the Pokémon.
Your challenge is to determine which trainers qualify for the tournament and list the trainers' names and their six Pokémons (eight Pokémon types total).
Thank you for your comment @Jean-Balteryx . The start file was updated.
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Generating sample data to represent a population is key for many types of analyses! In this workflow, we have a list of 1000 people and we want to simulate a a test score for each person. For each person, randomize a score for the exam, but we're not going to make it that easy!
You'll need to generate the simulated scores under these conditions: 1) The lowest possible test score is a 50%, while the highest is a 90% 2) The simulated score must be 'randomly' generated as a normal distribution, where the population mean is 70%. 3) After creating the simulated test results, build a chart view to prove you have achieved a 'random' normal distribution by binning each score to the nearest point.
Stuck? Hint 1
Did I say 'simulation'?
Hint 2
You might have a hard time without the free predictive tools installed.
Hint 3
Oh, cool! There's a tool that simulates sample data! *Cough* Simulation Sampling *Cough* *Cough*
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