![]() ![]() But given their infrastructure and the use of open libraries for working, both of these programming languages can be a hit when it comes to data science. The main purpose or use of the R is for the statistical analysis as the programs it has for this approach are more sophisticated and advanced just as needed to perform the statistical analysis.Īs for Python, it uses a more direct approach with data science and its varied prospects. Both excel in their own way where continuous addition of libraries and tools is done on a constant basis to increase the user experience for both these programming languages. Since their debut tooth of these languages has been continuously used in the data science statistics related projects. R and Python are both open source programming languages with a relatively large community. Vulnerability Analyst / Penetration Tester.User Interface / User Experience (UI / UX) Developer.User Interface / User Experience (UI / UX) Designer.Systems Integration Engineer / Specialist.Software Development / Engineering Manager.Software as a Service (SaaS) Sales Engineer.Business Intelligence Developer/Architect.
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