This repository contains the data and code for the CESAB Datatoolbox exercises.
blabla
This research compendium has been developed using the statistical programming language R. To work with the compendium, you will need installed on your computer the R software itself and optionally RStudio Desktop.
The simplest way to explore the text, code and data is to click on binder to open an instance of RStudio in your browser, which will have the compendium files ready to work with. Binder uses rocker-project.org Docker images to ensure a consistent and reproducible computational environment. These Docker images can also be used locally.
You can download the compendium as a zip from from this URL:
master.zip. After unzipping: - open the .Rproj
file in RStudio - run devtools::install() to ensure you have the
packages this analysis depends on (also listed in the
DESCRIPTION file). - finally, open
analysis/paper/paper.Rmd and knit to produce the paper.docx, or run
rmarkdown::render("analysis/paper/paper.Rmd") in the R console
utils::sessionInfo()
#> R version 3.6.3 (2020-02-29)
#> Platform: x86_64-pc-linux-gnu (64-bit)
#> Running under: Ubuntu 16.04.6 LTS
#>
#> Matrix products: default
#> BLAS: /usr/lib/libblas/libblas.so.3.6.0
#> LAPACK: /usr/lib/lapack/liblapack.so.3.6.0
#>
#> locale:
#> [1] LC_CTYPE=en_GB.UTF-8 LC_NUMERIC=C
#> [3] LC_TIME=fr_FR.UTF-8 LC_COLLATE=en_GB.UTF-8
#> [5] LC_MONETARY=fr_FR.UTF-8 LC_MESSAGES=en_GB.UTF-8
#> [7] LC_PAPER=fr_FR.UTF-8 LC_NAME=C
#> [9] LC_ADDRESS=C LC_TELEPHONE=C
#> [11] LC_MEASUREMENT=fr_FR.UTF-8 LC_IDENTIFICATION=C
#>
#> attached base packages:
#> [1] stats graphics grDevices utils datasets methods base
#>
#> loaded via a namespace (and not attached):
#> [1] compiler_3.6.3 magrittr_1.5 tools_3.6.3 htmltools_0.4.0
#> [5] yaml_2.2.1 Rcpp_1.0.4.6 stringi_1.4.6 rmarkdown_2.1
#> [9] knitr_1.28 stringr_1.4.0 xfun_0.14 digest_0.6.25
#> [13] rlang_0.4.6 evaluate_0.14