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smallsets  

Visual Documentation for Data Preprocessing
View on CRAN: Click here


Download and install smallsets package within the R console
Install from CRAN:
install.packages("smallsets")

Install from Github:
library("remotes")
install_github("cran/smallsets")

Install by package version:
library("remotes")
install_version("smallsets", "2.0.0")



Attach the package and use:
library("smallsets")
Maintained by
Lydia R. Lucchesi
[Scholar Profile | Author Map]
First Published: 2023-02-03
Latest Update: 2023-12-05
Description:
Data practitioners regularly use the 'R' and 'Python' programming languages to prepare data for analyses. Thus, they encode important data preprocessing decisions in 'R' and 'Python' code. The 'smallsets' package subsequently decodes these decisions into a Smallset Timeline, a static, compact visualisation of data preprocessing decisions (Lucchesi et al. (2022) <doi:10.1145/3531146.3533175>). The visualisation consists of small data snapshots of different preprocessing steps. The 'smallsets' package builds this visualisation from a user's dataset and preprocessing code located in an 'R', 'R Markdown', 'Python', or 'Jupyter Notebook' file. Users simply add structured comments with snapshot instructions to the preprocessing code. One optional feature in 'smallsets' requires installation of the 'Gurobi' optimisation software and 'gurobi' 'R' package, available from <https://www.gurobi.com>. More information regarding the optional feature and 'gurobi' installation can be found in the 'smallsets' vignette.
How to cite:
Lydia R. Lucchesi (2023). smallsets: Visual Documentation for Data Preprocessing. R package version 2.0.0, https://cran.r-project.org/web/packages/smallsets. Accessed 22 Apr. 2025.
Previous versions and publish date:
1.0.0 (2023-02-03 11:10)
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