RKaggle

An R package for downloading datasets from Kaggle into the R Console.

Installation

To install the latest version on CRAN, run:

install.packages("RKaggle")

To install the development version, run:

# install.packages('devtools')

# devtools::install_github("benyamindsmith/RKaggle")
install.packages("RKaggle", repos = c('https://benyamindsmith.r-universe.dev', 'https://cloud.r-project.org'))

Sample Usage

>library(RKaggle)
># Download and read the "canadian-prime-ministers" dataset from Kaggle
>canadian_prime_ministers <- RKaggle::get_dataset("benjaminsmith/canadian-prime-ministers")
>canadian_prime_ministers
# A tibble: 29 × 5
   No.        Name                `Political Party`     `Term Start`     `Term End`      
   <chr>      <chr>               <chr>                 <chr>            <chr>           
 1 1 (1 of 2) John A. Macdonald   Liberal-Conservative  1 July 1867      5 November 1873 
 2 2          Alexander Mackenzie Liberal               7 November 1873  8 October 1878  
 3 1 (2 of 2) John A. Macdonald   Liberal-Conservative  17 October 1878  6 June 1891     
 4 3          John Abbott         Liberal-Conservative  16 June 1891     24 November 1891
 5 4          John Thompson       Liberal-Conservative  5 December 1892  12 December 1894
 6 5          Mackenzie Bowell    Conservative          21 December 1894 27 April 1896   
 7 6          Charles Tupper      Conservative          1 May 1896       8 July 1896     
 8 7          Wilfrid Laurier     Liberal               11 July 1896     10/6/1911       
 9 8          Robert Borden       Government (Unionist) 10/10/1911       7/10/1920       
10 9 (1 of 2) Arthur Meighen      Conservative          7/10/1920        12/29/1921      
# ℹ 19 more rows
# ℹ Use `print(n = ...)` to see more rows

Present Scope

RKaggle presently only supports the download and loading of the following file formats:

• .csv
• .tsv
• .xlsx
• .json
• .rds
• .parquet
• .ods
• .shp
• .geojson
• .feather

Blogs

1. RObservations #51: Download Kaggle Datasets into the R Console with {RKaggle}

References

1. Akhtar et al. (2024). Croissant: A Metadata Format for ML-Ready Datasets. Proceedings of the Eighth Workshop on Data Management for End-To-End Machine Learning, 4, 1–6. https://doi.org/10.1145/3650203.3663326

Similar Works

• kaggler

Acknowledgements

The TidyTuesday project from where I based the code for this package on initially.