very basic R nodes in KNIME - knime.in, knime.out and handle Flow Variables
The Component will provide you with a curated R version in a conda environment "knime_r_environment"
You will need a working Miniforge (https://github.com/conda-forge/miniforge) or Miniconda (https://docs.conda.io/en/latest/miniconda.html) or Anaconda environment. As an alternative you could install your own R/RStudio and point KNIME to it without propagation.
In the /data/ folder there will be an Excel File my_r_packages_<YYYY-MM-DD_HH-mm-ss>.xlsx that would contain a list of R packages from the installation.
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# you will need a working Anaconda oder Miniconda installation
# please note - the popular Anaconda package has changed its licensing recently.
# So make sure you comply with that. Or use Miniconda with conda-forge for the time being
# https://docs.conda.io/en/latest/miniconda.html

# following: https://hub.knime.com/marcelw/spaces/Public/latest/Conda_Environment_Propagation_for_R~WqCc-xp5owF0HC4p

conda create -n knime_r_environment -c defaults -c conda-forge r-base r-rserve r-essentials

# you might have to install a special version of RServe > 1.8.6
conda install -c conda-forge r-rserve=1.8_7

#
# To activate this environment, use
#

conda activate knime_r_environment

#
# To deactivate an active environment, use
#
# $ conda deactivate

# install in one step
conda install -c conda-forge r-ggplot2 r-sessioninfo r-foreign r-readr r-readxl r-cairo

# install in individual steps
conda install -c conda-forge r-sessioninfo
conda install -c conda-forge r-foreign
conda install -c conda-forge r-readr
conda install -c conda-forge r-cairo

# if you want to use h2o from within KNIME
conda install -c conda-forge r-h2o

# check the conda environments
conda info --envs

	Go back to parent directory
	data
	metanodes
	model
	kn_deeplearn_010_prepare_adult_dataset
	kn_deeplearn_050_tensorflow2_basic_mlp
	kn_deeplearn_100_keras_basic
	kn_deeplearn_200_h2o_automl_dl
	kn_deeplearn_900_collect_results