---
title: R-programming-on-ubuntu-24.04
description: Spin up R Programming on Ubuntu 24.04 LTS instantly. A pre-configured statistical computing and data analysis environment featuring R, Git, cURL, and …
product: Marketplace
url: https://docs.digitalocean.com/products/marketplace/catalog/r-programming-on-ubuntu-24-04/
last_updated: "2026-06-22"
---

> **For AI agents:** The documentation index is at [https://docs.digitalocean.com/llms.txt](https://docs.digitalocean.com/llms.txt). Markdown versions of pages use the same URL with `index.html.md` in place of the HTML page (for example, append `index.html.md` to the directory path instead of opening the HTML document).

# R-programming-on-ubuntu-24.04

Generated on 22 Jun 2026 from [the R-programming-on-ubuntu-24.04 catalog page](https://marketplace.digitalocean.com/apps/r-programming-on-ubuntu-24-04)

**R** is a free, open-source programming language and software environment widely used for statistical computing, data analysis, machine learning, data visualization, and research. It provides a rich ecosystem of packages and libraries that enable users to perform advanced analytics, build predictive models, generate reports, and create high-quality visualizations across various domains.

This pre-configured 1-Click App deploys **R Programming on Ubuntu 24.04 LTS** with essential development tools installed and configured, including R, Git, cURL, and Wget. The application is designed to provide a reliable, scalable, and user-friendly environment for data scientists, researchers, analysts, and developers, allowing them to quickly start developing, testing, and running R-based applications and analytical workflows on DigitalOcean.

## Software Included

*This Marketplace listing does not include a detailed software list.*

## Creating an App using the Control Panel

Click the **Deploy to DigitalOcean** button to create a Droplet based on this 1-Click App. If you aren’t logged in, this link will prompt you to log in with your DigitalOcean account.

[![Deploy to DO](https://www.deploytodo.com/do-btn-blue.svg)](https://cloud.digitalocean.com/droplets/new?image=apps4rent-rprogrammingonub)

## Creating an App using the API

In addition to creating a Droplet from the R-programming-on-ubuntu-24.04 1-Click App using the control panel, you can also use the [DigitalOcean API](https://docs.digitalocean.com/reference/api). As an example, to create a 4GB R-programming-on-ubuntu-24.04 Droplet in the SFO2 region, you can use the following `curl` command. You need to either save your [API access token](https://docs.digitalocean.com/reference/api/create-personal-access-token/index.html.md) to an environment variable or substitute it in the command below.

```shell
curl -X POST -H 'Content-Type: application/json' \
         -H 'Authorization: Bearer '$TOKEN'' -d \
        '{"name":"choose_a_name","region":"sfo2","size":"s-2vcpu-4gb","image":"apps4rent-rprogrammingonub"}' \
        "https://api.digitalocean.com/v2/droplets"
```

## Getting Started After Deploying R-programming-on-ubuntu-24.04

### Getting Started After Deploying R Programming on Ubuntu 24.04

Once the **R Programming on Ubuntu 24.04** One-Click Droplet is created, you can log into it as root. Make sure to substitute the Droplet’s public IPv4 address.

```
ssh root@your_droplet_public_ipv4
```

R and the required development tools are already installed and ready to use.

To verify the installation, run the following commands:

- `R --version` : Verify the installed R version.
- `Rscript --version` : Verify the installed Rscript version.
- `git --version` : Verify the installed Git version.
- `curl --version` : Verify the installed cURL version.
- `wget --version` : Verify the installed Wget version.

Start an interactive R session:

```
R
```

Exit the R console:

```
q()
```

Useful R commands:

```
R
Rscript script.R
Rscript --version
```

Check the installation paths:

```
which R
which Rscript
```

View installed R packages:

```
dpkg -l | grep r-base
```

After logging in for the first time, you can:

- Create and run R scripts.
- Install additional R packages from CRAN.
- Perform statistical analysis and data visualization.
- Build machine learning and data science projects.
- Use Git for version control and collaboration.

This environment is ready for statistical computing, data analysis, research, and development workloads on DigitalOcean.