Installing our R development environment on Ubuntu 20.04

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Step 1: Install R,  Here the link with instructions: How to instal R on Ubuntu 20.04
Adding the steps I followed because sometimes the links become unavailable:

Add GPG key:

$ sudo apt-key adv –keyserver –recv-keys E298A3A825C0D65DFD57CBB651716619E084DAB9 Output:Executing: /tmp/apt-key-gpghome.NtZgt0Un4R/ –keyserver –recv-keys E298A3A825C0D65DFD57CBB651716619E084DAB9 gpg: key 51716619E084DAB9: public key “Michael Rutter ” imported gpg: Total number processed: 1 gpg: imported: 1

Add repository:

$ sudo add-apt-repository ‘deb focal-cran40/’ Output:Hit:1 stable InRelease Hit:2 focal InRelease Hit:3 focal InRelease Hit:4 focal-updates InRelease Hit:5 focal-backports InRelease Get:6 focal-cran40/ InRelease [3 622 B] Hit:7 focal-security InRelease Get:8 focal-cran40/ Packages [31.6 kB] Fetched 35.3 kB in 2s (20.9 kB/s) Reading package lists… Done

Update repositories:

$ sudo apt update

Install R:

$ sudo apt install r-base

Step 2: Download and install rstudio, execellent R IDE:

R studio download link ***Select package Ubuntu 18/Debian 10 (64-bit deb package).
*In this case I am showing version 1.4.1106, please adjust to the version you are installing.
After downloading rstudio installation file: rstudio-1.4.1106-amd64.deb, it is a good practice(in some cases needed) to import RStudio’s public code-signing key prior to installation, please visit this page for more detail: RStudio Public Key

Showing RStudio install file verification process, first get public key:
$ gpg –keyserver –recv-keys 3F32EE77E331692F Output:gpg: key 3F32EE77E331692F: public key “RStudio, Inc. (code signing) ” imported gpg: Total number processed: 1 gpg: imported: 1
Verifying rstudio install file:
$ dpkg-sig –verify rstudio-1.4.1106-amd64.deb Output:Command ‘dpkg-sig’ not found, but can be installed with: sudo apt install dpkg-sig

Installing needed package:

$ sudo apt install dpkg-sig
verify again:
$ dpkg-sig –verify rstudio-1.4.1106-amd64.deb Output:Processing rstudio-1.4.1106-amd64.deb… GOODSIG _gpgbuilder FE8564CFF1AB93F1728645193F32EE77E331692F 1613072032

Once veryfied, to install the rstudio downloaded package, open a terminal window and from the folder where you downloaded rstudio, execute:
$ sudo dpkg -i rstudio-1.4.1106-amd64.deb

Showing my output because I got some errors:
$ sudo dpkg -i rstudio-1.4.1106-amd64.deb Output:Selecting previously unselected package rstudio. (Reading database … 192590 files and directories currently installed.) Preparing to unpack rstudio-1.4.1106-amd64.deb … Unpacking rstudio (1.4.1106) … dpkg: dependency problems prevent configuration of rstudio: rstudio depends on libclang-dev; however: Package libclang-dev is not installed. rstudio depends on libpq5; however: Package libpq5 is not installed. dpkg: error processing package rstudio (–install): dependency problems – leaving unconfigured Processing triggers for gnome-menus (3.36.0-1ubuntu1) … Processing triggers for desktop-file-utils (0.24-1ubuntu3) … Processing triggers for mime-support (3.64ubuntu1) … Processing triggers for hicolor-icon-theme (0.17-2) … Processing triggers for shared-mime-info (1.15-1) … Errors were encountered while processing: rstudio
Fixing the problem: Installing libclang-dev:
$ sudo apt install libclang-dev Output:Reading package lists… Done Building dependency tree Reading state information… Done You might want to run ‘apt –fix-broken install’ to correct these. The following packages have unmet dependencies: libclang-dev : Depends: libclang-10-dev (>= 10~) but it is not going to be installed rstudio : Depends: libpq5 but it is not going to be installed E: Unmet dependencies. Try ‘apt –fix-broken install’ with no packages (or specify a solution).

So, I ran it: $ sudo apt –fix-broken install
Running again the install and it worked just fine: 
$ sudo dpkg -i rstudio-1.4.1106-amd64.deb 
After this you will have your basic R development environment. The next thing to do is to install R packages, to have a more complete development environment.

Step 3: Install a series of Ubuntu packages needed before installing R packages:

Open a terminal window and run all the next installation commands:

sudo apt-get install libcurl4-openssl-dev
sudo apt-get install libssl-dev
sudo apt-get install libxml2-dev
sudo apt install libmariadbclient-dev
sudo apt-get install libpq-dev
sudo apt-get install unixodbc unixodbc-dev
sudo apt-get install libcairo2-dev
sudo apt-get install libgtk2.0-dev

The other important thing to do before installing R packages is to install Java and set it as default, for this installation I am using Java 8.

This is a good reference article about: How To Install Java 8 on Ubuntu 20.04/18.04/16.04

For short on Ubuntu 20.04, from a command window run this instructions:
$ sudo su Install Java 8: # apt install openjdk-8-jdk Check Java version to test it was installed: # java -version You should get a similar output like this:openjdk version “1.8.0_282” OpenJDK Runtime Environment (build 1.8.0_282-8u282-b08-0ubuntu1~20.04-b08) OpenJDK 64-Bit Server VM (build 25.282-b08, mixed mode) Configure Java:# cd /usr/lib/jvm # ln -s /usr/lib/jvm/java-8-openjdk-amd64 /usr/lib/jvm/default-java # export LD_LIBRARY_PATH=/usr/lib/jvm/default-java/lib:$LD_LIBRARY_PATH # export JAVA_HOME=/usr/lib/jvm/default-java # R CMD javareconf KEEP THIS TERMINAL WINDOW OPEN AS IT IS NOW AND CONTINUE TO THE R PACKAGES INSTALLATION


On the same terminal above, run R: #R 
Now continue to the R packages installation: 
tidyverse -> Opinionated collection of R packages designed for data science.
install.packages( “tidyverse”, dependencies = TRUE )

data.table -> Fast manipulation of large datasets.
install.packages( “data.table”, dependencies = TRUE )

sqldf -> Run SQL instructions on your datasets.
install.packages( “sqldf”, dependencies = TRUE )

stringdist -> Computes string distances, very useful when creating clusters of catalog descriptions.
install.packages( “stringdist”, dependencies = TRUE )

RODBC -> Database access.
install.packages( “RODBC”, dependencies = TRUE )

xts -> Non regular time series package
install.packages( “xts”, dependencies = TRUE )

dygraphs -> Nice graphs for R
install.packages( “dygraphs”, dependencies = TRUE )

openxlsx -> Read, Write and Edit XLSX Files
install.packages( “openxlsx”, dependencies = TRUE )

lubridate -> Dates handling.
install.packages( “lubridate”, dependencies = TRUE )

forecast -> ARIMA and forecast package
install.packages( “forecast”, dependencies = TRUE )

mailR -> Send email from R
install.packages( “mailR”, dependencies = TRUE )

gbm -> gbm ( Gradient Boosting Machine )algorithm for R
install.packages( “gbm”, dependencies = TRUE )

gbm ->  xgboost algorithm for R
install.packages( “xgboost”, dependencies = TRUE )

aTSA -> Time Series Analysis
install.packages( “aTSA”, dependencies = TRUE )

rattle -> Tab-oriented user interface that is similar to Microsoft Office’s ribbon interface. It makes getting started with data mining in R very easy.
install.packages( “rattle”, dependencies = TRUE )

Rcmdr -> R Commander. A platform-independent basic-statistics GUI (graphical user interface) for R, based on the tcltk package.
install.packages( “Rcmdr”, dependencies = TRUE )

itsmr -> Time Series Analysis Using the Innovations Algorithm. Provides functions for modeling and forecasting time series data.
install.packages( “itsmr”, dependencies = TRUE )

stlplus  -> A new implementation of STL. Allows for NA values, local quadratic smoothing, post-trend smoothing, and endpoint blending. The usage is very similar to that of R’s built-in stl().
install.packages( “stlplus”, dependencies = TRUE )

TSA -> Useful to compute data seasonality.
install.packages( “TSA”, dependencies = TRUE )

Enjoy it!!!.

Carlos Kassab

More information about R:

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