Pharo DataFrame: Past, Present, and Future

Larisa Safina (1, 2) , Oleksandr Zaitsev (3) , Cyril Ferlicot-Delbecque (1, 2) , Papa Ibrahima Sow (4)

1 CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189
2 EVREF - Reflective Evolution of Ever-running Software Systems
3 Arolla
4 ESP - École Supérieure Polytechnique de Dakar

DataFrame is a tabular data structure for data analysis. It is a two-dimensional table (similar to a spreadsheet) with an extensive API for querying and manipulating the data. Data frames are available in many programming languages (e.g., pandas in Python or data.frame in R), they are the go-to tools for data scientists and machine learning practitioners. Pharo DataFrame was first released in 2017. Since then, the library underwent many changes and improvements. In this paper, we present the Pharo DataFrame library, show examples of its usage, and compare its API to that of pandas. We overview the changes that have been made since DataFrame v1.0, discuss the limitations of the current implementation, and present the roadmap for future.

Keywords: Pharo; DataFrame; Data analysis; Data structures

Domains: Computer Science [cs]; Software Engineering [cs.SE]

Larisa Safina, Oleksandr Zaitsev, Cyril Ferlicot-Delbecque, Papa Ibrahima Sow. Pharo DataFrame: Past, Present, and Future. International Workshop on Smalltalk Technologies, Aug 2023, Lyon, France. ⟨hal-04212030⟩