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The link to last week’s challenge is HERE.
This week’s exercise is another example of how Alteryx can take poorly formatted data such as transactional log files and turn it into usable data.
Use Case: A customer has some data that comes with key product information stored at the top of the file. Each data column contains three lines of header information per product (product, market and type). The customer wants this information to be shown in rows for each product.
Objective: Reformat the input data to match the output example.
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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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A solution to last week’s challenge can be found here.
Are you wondering which artists produced the top songs? Do you want some insights? This challenge is for you.
The following dataset contains information about the top 500 songs. Using the dataset, find the top 50 artists with the most albums and the highest average rating. Include the following columns in your list :
- Artist(s) - Number of albums (Descending) - Average rating based on all albums (Descending) - Album title(s) - Average number of reviews based on all albums (Descending) - Genre(s) - Year the first album was released - Year the last album was released
Note: If in your solution you have null records for the Release Year, do not include them.
This challenge was updated to propose 2 start files and 2 solutions.
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A solution to last week's Challenge has been posted HERE!
This year's (2017-2018) flu season has been reported to be the most severe in the past decade. In particular, influenza-related hospitalizations are on the rise across a wider range of age groups than normal. For this week's Challenge, we'll use data from the Center for Disease Control (CDC) concerning California's data on influenza-related hospitalizations. Create a table that shows the cumulative number of hospitalizations per age group for each flu season.
Looking for additional analyses to do? How about a week-by-week comparison of hospitalizations? Or perhaps a forecast of the number of expected hospitalizations for a particular age group? Or maybe a visual representation of the data is up your alley!
Stay healthy out there!
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A solution to last week’s challenge can be found here.
Do you have to work with messy data?
The provided dataset is Messy with a capital M. For this challenge, calculate the average cost of an app (Application Fee and Cost) based on the 10 most expensive apps.
Guidelines: - You must use the values of the creator whose last name starts with S. - Calculate the cost of each app (application fee + cost). - Round up the cost of each app; for example, if an app costs $67.03, round up to $68. - Determine the cost at X.99; for example, if an app costs $68, the final cost will be $67.99. - Then you will calculate the average cost based on the 10 most expensive apps.
Start by cleaning the messy dataset.
Thank you for your comments. This Weekly Challenge was updated.
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