A solution to last week’s challenge can be found here.
To solve this week’s challenge, use Designer Cloud or Designer Desktop.
Do you have to reformat lists because the last name and first name are listed in a different order?
In this weekly challenge, you need to rearrange an improperly formatted list of subscribers. Some of the subscribers’ names are listed with the last name(s) followed by a comma, and then the first name(s).
Your goal is to reorder the list with the first name(s) followed by the last name(s), and put the list in alphabetical order. For example, the subscriber “BORROEL GOMEZ, JUANA” should be listed as “JUANA BORROEL GOMEZ” with no punctuation.
Note that some subscribers can have more than one first name or last name.
Haven’t heard about Designer Cloud yet? Watch a demo.
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Hi Maveryx,
We posted the solution JSON file to Cloud Quest #7. 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 8 - Start File.json file into your Analytics Cloud library.
The input and output datasets are included in the start 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:
A group of friends are playing their favorite game. Not understanding the importance of inputting data in an easy-to-work-with format, they devised an incredibly inefficient way to keep score of their game!
In the game, there are five rounds of play and five players (a, b, c, d, and e—the first letter of their names). Each time the player’s initial appears in lowercase, the player is awarded 1 point. Each time their initial appears in uppercase, 1 point is subtracted from their overall score. Now it is your job to figure out each player’s score for each round and their respective totals after all five rounds of play. Who won?
Hints:
Tokenize the input data into rows.
There are many ways to calculate scores for each letter, but an If/Then statement can accomplish this in one expression.
When pivoting, you can perform multiple calculations at once including Sum and Total Column.
A combination of the Cross Tab, RegEx, Formula, and Dynamic Replace 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.
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!
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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.
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A solution to last week's Challenge can be found here!
A big thanks to those of you that joined us last week at Inspire for the Weekly Challenge session! It was so much fun solving with you all!
This week, we're identifying the most popular baby names that were registered between the years of 1880 and 2017. Given the provided dataset, determine the most popular names for Males and Females for each available year. The column "Field_1" contains three concatenated values: the name, the associated gender (Male or Female) and the number of occurrences that the name appeared in birth records. The column "FileName" contains the name of the file in which the record is found; the data was read in from a zip file that contained text files for each year (1880-2017) of records.
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