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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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Hi Maveryx,
A solution to last week’s challenge can be found here.
This challenge comes to us from @AkimasaKajitani . Thank you for your contribution, Aki!
Meteorite showers are a captivating natural phenomenon, though it can be challenging to see them depending on your location. Fortunately, residents and visitors in the Las Vegas area enjoy an advantageous position, being in proximity to expansive desert skies that offer excellent conditions for meteorite watching.
For this challenge, your mission is to plan a budget-friendly meteorite impact site tour near Las Vegas, ensuring enthusiasts visit locations where they have the best opportunity to witness this celestial spectacle.
Here are the tasks you must complete. Calculate all distances in kilometers.
Find a meteorite impact site that is closest to a hotel that costs less than $200 per night. Designate this location as the "First Stop."
Identify the nearest meteorite impact site in relation to the First Stop. Label this site as the "Second Stop" and determine the distance between the first and second stops.
Locate the nearest meteorite impact site in relation to the Second Stop. Name this site “Third Stop” and determine the distance between the second and third stops.
Calculate the total distance traveled from the hotel to the third stop.
Data Summary:
You have two datasets. The text dataset contains the latitude and longitude of some hotels in Las Vegas with their cost per night. The second dataset, meteorite-landings.csv, contains the latitude and longitude of over 45,000 meteorites that have struck our planet.
Source: https://www.kaggle.com/datasets/nasa/meteorite-landings
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The solution to last week's challenge can be found here!
This week's challenge was submitted by the illustrious @MarqueeCrew who came across this challenge at a Tableau User Group! Yes - the problem really was around beer and Pop-Tart pairings.
At a recent Tableau User Group, a poll was conducted using SurveyMonkey and the data was exported to an Excel workbook. Unfortunately, the data wasn't in a format that made it easy to work with in Tableau. Fortunately, an Alteryx user was there to prep the data on their behalf.
Within the survey data, there are repeating groups of Pop-Tart, Beer and Score values. Yes, the TUG had samples of Pop-Tarts paired with the beers from Bell's Brewery. The task was to create a single column for each of these values, allowing for repeating the balance of the survey results.
Can you Normalize the output data? For bonus play, can you analyze the data and provide insights from the sample data?
The output should include: 1. Name of the fiber 2. The original spatial line object 3. The new spatial line object 4. New length of line
This is my vote for best pairing.
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A solution to last week’s challenge can be found here.
The Big Five personality traits, also known as the five-factor model (FFM), is a taxonomy, or grouping, for personality traits.
The dataset contains responses from users who rated themselves on a scale of 1 to 5 for 50 questions in the 5 personality factors. Some questions are weighted positively in the final score, some are weighted negatively.
Your job is to give each user a score in each of the 5 factors (Sum of all points per factor). Additionally, each users' final score should be adjusted as follows per the scoring instructions on https://openpsychometrics.org/
Extraversion: 20 + Score Agreeableness: 14 + Score Conscientiousness: 14 + Score Neuroticism: 38 - Score Openness: 8 + Score
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A solution to last week’s challenge can be found here. Source: https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/how-to-make-cloth-face-covering.html
With the sudden need for masks around the globe, sewing has seen an increase in popularity. Many local communities have asked their citizens to pitch in and provide masks to create a sufficient supply. These masks are usually created by sewing a pattern with at least 2 layers of fabric.
In the attached datasets, we have the number of masks created by a local community known as Bastille St. Below that, we also have the number of masks created by local companies and independent contractors for the same community. Use this data to find the total number of masks produced by each group for each mask size and the total number of masks produced by each group.
As a bonus challenge, use the additional table of fabric requirements to determine the total number of cotton bundles that were used by each individual/group. Each bundle of cotton is 122cm x 100 cm and color coded so you can only use each bundle for one size of mask. Remember that they are 2 layers thick!
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