How to Install R on DigitalOcean Ubuntu 16.04: A Simple Guide

R is a popular programming language for statistical computing and graphics. Installing R on a DigitalOcean Ubuntu 16.04 server provides access to powerful data analysis and visualization tools. This guide will walk you through the step-by-step process of installing R on your DigitalOcean server efficiently.

Benefits of Using R on DigitalOcean

Efficient Data Handling: R simplifies complex data manipulation tasks.
Powerful Visualization Tools: Offers a wide range of statistical and graphical techniques.
Scalability: DigitalOcean provides robust infrastructure and user-friendly deployment.
Extensive Package Support: R has a vast repository of packages for data science, machine learning, and bioinformatics.
Community Support: A large community of R developers provides documentation, tutorials, and troubleshooting help.

Prerequisites for Installation

Before proceeding, ensure you have:

A DigitalOcean account
A Droplet running Ubuntu 16.04
Root or sudo access
A configured firewall allowing SSH (port 22) and RStudio (port 8787)

Step 1: Setting Up Your DigitalOcean Account

Sign up on the DigitalOcean website.
Add a valid payment method.
Create a new Droplet, selecting Ubuntu 16.04 as the operating system.
Choose a plan based on your resource needs.
Set up SSH keys for secure access.
Finalize and deploy your Droplet.

Visit: Buy DigitalOcean Account

Step 2: Preparing the Ubuntu 16.04 Server

Log in via SSH:
```
ssh root@your_server_ip
```

Update and upgrade the system:

sudo apt-get update && sudo apt-get upgrade -y

Install required dependencies:

sudo apt-get install gdebi-core libapparmor1 libcurl4-openssl-dev libssl-dev libxml2-dev libcairo2-dev libxt-dev -y

Verify Ubuntu version:
```
lsb_release -a
```

Step 3: Installing R on Ubuntu 16.04

Add the CRAN repository and key:

sudo apt-key adv --keyserver keyserver.ubuntu.com --recv-keys E298A3A825C0D65DFD57CBB651716619E084DAB9
sudo add-apt-repository 'deb https://cloud.r-project.org/bin/linux/ubuntu xenial-cran40/'

Update the package list again:
```
sudo apt-get update
```
Install R:
```
sudo apt-get install r-base -y
```
Verify installation:
```
R --version
```

Step 4: Configuring the R Environment

Set Locale for R:
```
export LANG=en_US.UTF-8
```

Managing R Packages:

Install a package:
```
install.packages("ggplot2")
```
Load a package:
```
library(ggplot2)
```

Update packages:

update.packages(ask = FALSE, checkBuilt = TRUE)

Remove a package:
```
remove.packages("ggplot2")
```

Install RStudio (Optional but Recommended):

sudo apt-get install gdebi-core
wget https://download1.rstudio.org/desktop/bionic/amd64/rstudio-1.4.1103-amd64.deb
sudo gdebi rstudio-1.4.1103-amd64.deb

Launch RStudio from the command line:
```
rstudio
```

Step 5: Testing the R Installation

Start the R console:
```
R
```

Run sample R commands:

version$version.string
vec <- c(1, 2, 3)
mean(vec)

Create a sample plot:
```
plot(cars)
```

Step 6: Securing Your R Installation

Set up a firewall:
```
sudo ufw allow OpenSSH
sudo ufw enable
```

Enable automatic security updates:

sudo apt-get install unattended-upgrades
sudo dpkg-reconfigure unattended-upgrades

Create a non-root user for security:
```
adduser ruser
usermod -aG sudo ruser
```

Troubleshooting Common Issues

Handling Installation Errors

Double-check command syntax.
Ensure the CRAN repository is properly added.
Refer to the official R documentation.

Connectivity Issues

Ensure a stable internet connection.
Check firewall settings.
Restart the networking service if needed:
```
sudo systemctl restart networking
```

Conclusion

Installing R on DigitalOcean Ubuntu 16.04 is a straightforward process that enhances your data analysis capabilities. By following this guide, you can successfully set up R on your server and leverage its powerful features for statistical computing and visualization. Regular updates and security measures will ensure smooth and safe operations. Happy coding!

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John Stone

A seasoned cloud computing expert with over 10 years of experience in the tech industry. Specializing in cloud infrastructure and optimization, John has helped numerous startups and enterprises transition to efficient and scalable cloud solutions.