Experimental and Exploratory Analysis of Programming Languages Popularity According to the PYPL Index

Abstract

This article dwells upon procedure for primary and exploratory analysis of data concerning programming languages popularity according to the PYPL index. Classical, but flexible methods of cluster and correlation analysis, and mathematical statistics have been used in data analysis. Examples of various researches in the field of popularity and development of programming languages have been provided, and based on open questions in this area, set of graphic results has been constructed by data analysis, which logically has resulted in conclusions regarding the selection of models and methods for further data forecasting. Integral part of the report information content consists of executable code examples in the R programming language, which can be used to conduct similar studies. © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).