Alteryx Academy

  Hello Community Members, A solution to last week’s challenge can be found here.    This challenge was submitted by Yash Thakkar. We appreciate your contribution @yash_thakkar!    Some months mark pivotal moments for students and job seekers worldwide, especially when exploring the H-1B job market. The H-1B visa program allows US employers to temporarily hire foreign workers in specialty occupations requiring a combination of highly specialized knowledge and a bachelor's degree or higher in a relevant field, or its equivalent.   The dataset provided includes fiscal year 2024 data on employers who have submitted petitions to employ H-1B workers.   Your tasks are: Identify the top 10 companies that submitted the most H-1B petitions in 2024. Determine the top 10 industries with the highest demand (number of total petitions submitted) for H-1B workers in 2024. Hints: Exclude companies with missing industry data (Industry (NAICS) Code). Focus only on approved petitions as follows: Initial Approval (first-time H-1B employment) Continuing Approval (extensions or changes for existing H-1B employees) Happy solving!   Sources: https://www.uscis.gov/tools/reports-and-studies/h-1b-employer-data-hub https://www.uscis.gov/tools/reports-and-studies/h-1b-employer-data-hub/understanding-our-h-1b-employer-data-hub   The Academy Team ... View more

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.      ... View more

The solution to last week's challenge can be found HERE.    Determine the items of clothing that have the highest average rating. In your analysis, include 1) only items of clothing that have at least 10 positive feedback reviews and 2) the five highest rated clothing items from each class.   The original data and its metadata can be found here.        ... View more

For the fourth challenge let’s look at parsing Dates from text strings. To view the previous challenge, click HERE.   A dataset contains a text field that has a date embedded within the text. The problem is that the date is represented a few different ways. For example:   16-APR-2005 Nov•16,•1900 4-SEP-00 Jan•5•2000   The goal is to create a new Date/Time field populated with the dates contained within the text field. You will also need to standardize the dates so that they are all formatted the same. We have listed this as an advanced exercise since parsing out the dates can be challenging depending on the technique you employ to do it. As always, we love to hear your comments. Have fun!   UPDATE 12/7/2015: The solution has been uploaded ... View more

Here is a new challenge for this week. The link to the solution for last week’s challenge is HERE. The use case: We received some text data and that includes an embedded line-feed character. The objective is to remove the new line character, convert the date-time string to a date-time formatted field and then do some renaming per the sample output. Good luck, I look forward to your feedback. ... View more