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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.
Congratulations, class of 2026!
For many new college students, now is the time to pay tuition for college, and sometimes their college decision is based on financial data.
This dataset contains information about private and public colleges in the US, where these institutions often offer different tuition for
in-state and out-of-state students.
Using the provided data: - Create a list of 4-year colleges by state that includes the total payment (tuition plus room and board) in 2020 for private colleges and public colleges for in-state and out-of-state students. - Find the top 10 schools that give the most significant discounts for in-state students.
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The link to the solution for last challenge #38 is HERE.
This week is a little different, as we work with Alteryx workflows and macros that were created by other people it may be necessary to ‘de bug’ someone else work or make modifications to get components to function in your workflow. In this case you will start with a macro that had errors and work through the process of fixing it.
Use Case: A bank is looking to calculate customer retention rate month over month. The denominator in the calculation are all of the accounts open 24 months prior to the start of the month. For example, for June 2013, the denominator would be the total number of accounts open between June 1, 2011 and May 31, 2013. The numerator will be total number of accounts closed in June 2013 or between June 1, 2013 and June 30, 2013.
Objective: The included macro should calculate the retention rate for May through Dec 2013 but there are errors in the macro. Your job is to fix the broken Macro.
Have fun…
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A solution to last week’s challenge can be found here.
Do you check the weather before planning a trip to a foreign country?
The following dataset contains information about the temperature of various locations in Ireland. Your job is to find the following the average (rounded up), the minimum, and the maximum temperature by "Station" in the Spring, Summer, and Fall. Use only the temperature recorded at 12:00.
Note: Use the following dates to determine the seasons: - Spring March 19 - Summer June 20 - Fall September 22
Thank you for your comments, this challenge has been updated.
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Last week's solution can be found HERE!
Create a macro that generates a table with the date and the day of the week for all dates from a given starting date to today. The user should be able to select the start date.
Bonus 1: Add a selection that will allow the macro user to select whether or not to include weekends. Bonus 2: Create a duplicate macro that's encrypted so that no changes can be made. Leave the first macro on your canvas unencrypted so other challenge-takers can observe how your macro was built.
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