![]() Data collected in 20 using the same protocol correlated r=.94, p=.002. One might think that a sample on a single day might not be very stable, but they are. To measure percent change, I compare that to data collected on May 27, 2019. I collected the job counts discussed in this section on October 5, 2022. All of the results in this section use those procedures to make the required queries. The details of this protocol are described in a separate article, How to Search for Data Science Jobs. To level the playing field, I developed a protocol to focus the search for each software within only jobs for data scientists. General-purpose languages (e.g., Python, C, Java) are heavily used in data science jobs, but the vast majority of jobs that require them have nothing to do with data science. Some software is used only for data science (e.g., scikit-learn, Apache Spark), while others are used in data science jobs and, more broadly, in report-writing jobs (e.g., SAS, Tableau). Searching for jobs using is easy, but searching for software in a way that ensures fair comparisons across packages is challenging. As their co-founder and former CEO Paul Forster stated, includes βall the jobs from over 1,000 unique sources, comprising the major job boards β Monster, CareerBuilder, HotJobs, Craigslist β as well as hundreds of newspapers, associations, and company websites.β also has superb search capabilities. is the biggest job site in the U.S., making its collection of job ads the best around. Plots of change in job demand give us a good idea of what will become more popular in the future. Job ads are rich in information and are backed by money, so they are perhaps the best measure of how popular each software is now. One of the best ways to measure the popularity or market share of software for data science is to count the number of job advertisements that highlight knowledge of each as a requirement. In rough order of the quality of the data, these include: There are many ways to measure popularity or market share, and each has its advantages and disadvantages. Do your colleagues use it so you can easily share data and programs?. ![]()
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