├── 2018_03_14_computationally_reproducible_research ├── 2018_03_14_computational_reproducibility.pdf ├── RMarkdown_example_1.Rmd ├── RMarkdown_example_2.R └── computationally_reproducible_research.R ├── Contributors.md ├── LICENSE ├── Meeting_RScripts ├── 111027_plotting_Rogier_de_Jong.r.R ├── 161019_playing_around_with_graphs_LucSteinbuch.R ├── 170614_Ruser_basic_stuff.R ├── 2019-04-15_Efficient data.frame manipulation with dplyr and data.table.R ├── 20200217-AWS_cloud.R ├── CSV_files │ └── Developmenttime.csv ├── Good_practise_data_structure.R ├── MakingPlots2_27Jan2015.R ├── R Raster processing.R ├── Rdemo_Functional+ParallelProgramming.R ├── conditionals_loop_apply.R ├── ggplot2.R ├── replacements.r └── spark │ ├── SparkR-VITO.R │ ├── SparkR-local.r │ └── spark-submit-vito.sh ├── Presentations ├── 2017-05-17_Brede_Intro_to_parallel_programming_R.pptx ├── 2018-04-19_Data Types and Data Modelling in R.R ├── 20180116 - Calling C++ code from R using Rcpp.pdf ├── 2018_06_06_git_dainius.pdf ├── 2019-04-15_Efficient data.frame manipulation with dplyr and data.table.pptx ├── IOSLIDESforR_by Paul Torfs.zip ├── NA.txt ├── R Raster processing.R ├── R Raster processing.pdf ├── Rmarkdown.pptx ├── Wehrens_20161214 │ ├── beamerthemewurnew.sty │ ├── lecture.R │ ├── lecture.Rnw │ ├── lecture.pdf │ └── wainer.pdf ├── functions_loop_apply.R ├── pheno_data_and_markers.Rdata └── survey_RuserGroup.pdf.pdf └── README.md /2018_03_14_computationally_reproducible_research/2018_03_14_computational_reproducibility.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/wageningen/RUsers/HEAD/2018_03_14_computationally_reproducible_research/2018_03_14_computational_reproducibility.pdf -------------------------------------------------------------------------------- /2018_03_14_computationally_reproducible_research/RMarkdown_example_1.Rmd: 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