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Here is this week’s challenge, I would like to thank everyone for playing along and for your feedback. The link to the solution for last challenge #33 is HERE. For this chalenge let’s look at creating a macro from scratch. I recommend you first solve the problem with tools on the canvas, then cake a macro from the tools.
Use Case: Our customer has a need to convert date/time strings into a date-time format.
Examples of the different input formats include: 4/8/2015 4:00, 5/10/2015 13:00. The conversion is automatic when the hours are 2 digits (10-24), but it ignores hours 1-9 (creates NULL values on conversion).
Objective: Create a macro to effectively convert and preserve the data in a date-time format.
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Here is this week’s challenge, I would like to thank everyone for playing along and for your feedback. The link to the solution for last challenge #16 is HERE. This week’s assignment is listed as an advanced exercise due to the requirement of using a batch macro for the solution.
The 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 through May 31, 2013. The numerator will be total number of accounts closed in June 2013 or between June 1, 2013 through June 30, 2013.
The objective is to create a batch macro that calculates the retention rate for May, June, July and August.
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A solution to last week's challenge can be found here!
This week's challenge was submitted by @kelly_gilbert - thank you for your contribution!
Challengers, get ready to have some fun with this one! And, with various levels of difficulty built into this challenge, there's something for everyone!
Your challenge this week is to build a Bingo Card! This challenge uses events/observations from a baseball game, but you can customize this input for anything from traditional numbers to things you might see at Thanksgiving Dinner. Enjoy!
Source: GIPHY
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A solution to last week’s challenge can be found here. "Pumpkins Halloween 2013" by Mod Mischief is licensed under CC BY-SA 2.0
Pumpkins abound, and squirrels are happy. It’s that time of the year! Halloween is in just a few days, and you need to get candy for trick-or-treaters.
This Halloween dataset contains 85 types of candy. Take a closer look at the columns: - sugar percentage - The percentile of sugar it falls under within the data set. - price percentage - The unit price percentile compared to the rest of the set. - favorite percentage - The overall win percentage according to 269,000 matchups.
Your house is going to be a hit if your candy basket includes the following: - The 5 candies with the lowest “sugar percentage”. An average trick or treater consumes 7,000 calories worth of candy, so you want to offer some healthy options. - The 5 candies with the highest “favorite percentage”. Your neighbors know you are a people pleaser! - The 5 candies with the lowest “price percentage”. The giant tarantula inflatables you bought weren’t cheap, so you need to save some money on the treats.
And no peanut or almond candies. The teal pumpkins at your front door communicate that your candy basked is allergy-friendly. (Did you know that’s a “thing”?)
Hint
Make sure to filter out all candies that are not allergy friendly first.
Among the 85 types of candy from the dataset, what are the 15 candies to have in your basket?
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This solution to last week's challenge can be found HERE.
A website log tracks every click visitors are making on a particular link on the site in order to measure interest in the link.
However, web consumers are impatient and may click a link multiple times in short succession.
The goal of this exercise is to flag "duplicate clicks" that is defined as the event fire date happening within 30 seconds of the previous event fire date for the same user (IDFA) and device (DeviceID)
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