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R computation

The R computation reads from /input and writes results to /output.

It can execute standard R 4.3.2 code with the following supported libraries.

R computation example

Library versions
  • Hmisc (5.1.1)
  • pROC (1.18.4)
  • ggplot2 (3.4.4)
  • ggmosaic (0.3.3)
  • dplyr (1.1.3)
  • ggforce (0.4.1)
  • lubridate (1.9.3)
  • lme4 (1.1.34)
  • coxme (2.2.18.1)
  • cmprsk (2.2.11)
  • msm (1.7)
  • randomForestSRC (3.2.2)
  • survminer (0.4.9)
  • tidyverse (2.0.0)
  • corrplot (0.9.2)
  • readxl (1.4.3)
  • lime (0.5.3)
  • e1071 (1.7-13)
  • effects (4.2-2)
  • lmtest (0.9-40)
  • AER (1.2-10)
  • sandwich (3.0-2)
  • vcd (1.4-11)
  • mclust (6.0.0)
  • lcmm (2.1.0)
  • openxlsx (4.2.5.2)
  • xgboost (1.7.5.1)
  • conflicted (1.2.0)
  • factoextra (1.0.7)
  • naniar (1.0.0)
note

The list of available libraries is not exhaustive.

Note that by default the R computations cannot access the network or internet. Also note that GPU-computations are currently not supported.

Input

The R computation can access data from datasets and computations which have been listed as its dependencies in the Available data section from the /input directory.

The paths differ based on the type of the dependency:

  • A Table dataset Table 1 can be loaded as /input/Table 1/dataset.csv
  • A File dataset File 1 can be loaded as /input/File 1
  • The results of a depending Python or R computation can be loaded under /input/<computation name>/<filename> the same way those results have been written to /output/<filename> in the depending computation
  • The results of a SQL computation can be loaded under /input/<computation name>/dataset.csv

Tmp

Computations can write intermediate results to a /tmp directory. Those files will not be part of the output.

Output

The computation should write results to the /output directory. The results as well as any text streamed to stdout are accessible by all users with data analyst permission on the computation.