SiPy - Bringing Python and R to the End-User in a Plugin-Extensible System

Nicholas TF Tan¹, Mathialagan Mugundhan¹, Tiantong Liu², Rick YH Tan¹, Alexander Y Tang¹, Bryan JH Sim¹, Jensen ZH Tan¹ and Maurice HT Ling^1,3*
¹School of Applied Science, Temasek Polytechnic, Singapore
²Independent Researcher
³HOHY PTE LTD, Singapore
*Corresponding Author: Maurice HT Ling, School of Applied Science, Temasek Polytechnic, Singapore; HOHY PTE LTD, Singapore.

Published: May 31, 2025

DOI: 10.55162/MCMS.08.295

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Abstract  

Data/statistical literacy is required for informed participation and better decision making in a literate society, and learning a data analysis tool may enhance the learning of statistical concepts. R and Python are well-known platforms for data analysis but are also difficult to learn even though they may be synergistic. Here, we present SiPy (Statistics in Python) as a data analysis tool built using Python and integrates analysis from R, and extensible using plug-ins. We will describe the architecture of the current version of SiPy, SiPy 0.6.0 codenamed “Otoro-Chutoro Continuum”, with a listing of the 60 available analytical functions across 8 function classes. This is followed by an elaboration of SiPy plugin system where end-users can add functions as plugins, before ending with a description of SiPy’s scripting system catering to modular scripting.

Keywords: Data analysis software; Statistical analysis software; Python; R; Plugin; Scripting

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