{"id":18968,"date":"2026-09-27T07:06:18","date_gmt":"2026-09-27T07:06:18","guid":{"rendered":"https:\/\/www.simtrade.fr\/blog_simtrade\/?p=18968"},"modified":"2026-09-27T08:30:08","modified_gmt":"2026-09-27T08:30:08","slug":"how-to-install-and-run-r-on-your-computer-a-step-by-step-guide","status":"publish","type":"post","link":"https:\/\/www.simtrade.fr\/blog_simtrade\/how-to-install-and-run-r-on-your-computer-a-step-by-step-guide\/","title":{"rendered":"How to install and run R on your computer (A step-by-step guide)"},"content":{"rendered":"\n<p><a href=\"https:\/\/www.linkedin.com\/in\/hadrienpuche\" target=\"_blank\"><img decoding=\"async\" style=\"padding: 5px\" title=\"\" src=\"https:\/\/www.simtrade.fr\/blog_simtrade\/wp-content\/uploads\/2026\/06\/img_Hadrien_Puche_bis-scaled-e1781527786395.jpeg\" alt=\"Hadrien Puche\" width=\"133\" align=\"right\"><\/a><\/p>\n\n\n<p>Understanding and writing R code can be a valuable skill for your career. While general-purpose programming languages such as Python are more widely used, R is particularly well suited to statistical analysis, data visualization, and quantitative research.<\/p>\n\n<p>In this article, <a href=\"https:\/\/www.linkedin.com\/in\/hadrienpuche\" target=\"_blank\">Hadrien Puche<\/a> (ESSEC Business School, <i>Grande \u00c9cole<\/i> Program, Master in Management, 2023-2027) will help you to:<\/p>\n \n<ul>\n  <li>Understand the core components of the R statistical ecosystem for finance<\/li>\n  <li>Compare development setups (RStudio Desktop vs. Visual Studio Code)<\/li>\n  <li>Install the Base R engine alongside essential build tools (RTools \/ Xcode)<\/li>\n  <li>Set up RStudio Desktop as a purpose-built workspace<\/li>\n  <li>Install econometric packages via CRAN (like <code>quantmod<\/code>)<\/li>\n  <li>Run a test script<\/li>\n<\/ul>\n\n\n<h2>But first, what is R exactly ?<\/h2>\n\n<p>Historically, R was created in 1993 as an open-source implementation of the S language, developed at Bell Labs for statistical computing.<\/p>\n \n<p>Setting up your R workspace can be straightforward. We will rely on R&#8217;s centralized package network, CRAN (for Comprehensive R Archive Network), to manage all the dependencies efficiently. Let&#8217;s walk through deploying a professional quantitative workspace for R.<\/p>\n\n<div style=\"background-color: #f8f9fa;border-left: 4px solid #0056b3;padding: 15px;margin: 20px 0;border-radius: 4px\">\n  <h4 style=\"margin-top:0;color:#0056b3\">Quick vocabulary for beginners<\/h4>\n  <p style=\"font-size:14px;margin-bottom:8px\">Before we dive in, let\u2019s define a few technical terms you will encounter frequently:<\/p>\n  <ul style=\"font-size:13px;margin-bottom:0;padding-left:20px\">\n    <li><b>Package:<\/b> A collection of pre-written code created by other developers, made so that you don&#8217;t have to reinvent the wheel (like <code>quantmod<\/code> for downloading financial markets data).<\/li>\n    <li><b>Library:<\/b> A directory on your computer, where your installed packages are stored. You will use the <code>library()<\/code> command in your code to load them. While developers often use the terms package and library interchangeably, technically you <i>install a package<\/i> into your <i>library<\/i>.<\/li>\n    <li><b>Dependency:<\/b> A package that another package requires in order to work properly. R manages these dependencies automatically, so you do not have to take care of them, but do not be surprised if you download much more packages than what you asked for.<\/li>\n    <li><b>Build Tools (RTools \/ Xcode):<\/b> Background software required by your computer to translate (or &#8220;compile&#8221;) raw source code into executable instructions. R frequently compiles financial packages directly on your machine, making these essential to prevent errors.<\/li>\n  <\/ul>\n<\/div>\n \n\n<h2>Choosing your development environment: RStudio or Visual Studio Code ?<\/h2>\n \n<p>You generally have two choices when it comes to writing R code: RStudio Desktop and Visual Studio Code (VS Code).<\/p>\n \n<ul>\n    <li><b>RStudio Desktop:<\/b> An Integrated Development Environment (IDE) built specifically for R. It features a 4-pane layout that lets you simultaneously view your scripts, console, environment variables (dataframes loaded in memory), and charts.<\/li>\n    <li><b>Visual Studio Code:<\/b> VS Code is a highly versatile code editor. You can absolutely run R inside it by installing the <code>R<\/code> extension. This is a good choice if you plan to mix multiple programming languages in the same project, though configuring VS Code for R requires a bit more effort than RStudio.<\/li>\n<\/ul>\n \n<p style=\"text-align:center;margin:20px 0\">\n  <img decoding=\"async\" src=\"https:\/\/www.simtrade.fr\/blog_simtrade\/wp-content\/uploads\/2026\/09\/img_R_Studio_empty.png\" alt=\"RStudio Desktop 4-pane layout\" width=\"500\" style=\"margin-top:8px;border-radius:8px;max-width: 100%\">\n  <br>\n  <small style=\"color:#555\">RStudio Desktop Interface<\/small>\n<\/p>\n\n<p style=\"text-align:center;margin:20px 0\">\n  <img decoding=\"async\" src=\"https:\/\/www.simtrade.fr\/blog_simtrade\/wp-content\/uploads\/2026\/09\/img_VSC_R.png\" alt=\"Visual Studio Code running R\" width=\"500\" style=\"margin-top:8px;border-radius:8px;max-width: 100%\">\n  <br>\n  <small style=\"color:#555\">Visual Studio Code configured for R<\/small>\n<\/p>\n \n<p>For this guide, we will focus on setting up the core R engine and integrating it with <b>RStudio<\/b>, as it offers a purpose-built user experience for R.<\/p>\n \n \n<h2>Understanding the R architecture<\/h2>\n \n<p>The R architecture operates as follows:<\/p>\n \n<ul>\n    <li><b>Base R:<\/b> The underlying computational engine that calculates the math and runs the logic.<\/li>\n    <li><b>Build Tools (RTools \/ Xcode):<\/b> As defined above, R frequently compiles packages directly from source code on your machine. You need these background tools to prevent installation errors.<\/li>\n    <li><b>CRAN:<\/b> The Comprehensive R Archive Network. This is the centralized, strictly regulated global repository for R packages.<\/li>\n<\/ul>\n \n \n<h2>Step-by-step installation guide<\/h2>\n \n<h3>Step 1: Install the R core engine and Build Tools<\/h3>\n \n<p>First, we must install the computational engine. RStudio will not function without it.<\/p>\n \n<ol>\n    <li>Go to the official <a href=\"https:\/\/cran.r-project.org\/\" target=\"_blank\">CRAN Download Page<\/a>.<\/li>\n    <li><b>For Windows:<\/b> \n        <ul>\n            <li>Click <b>Download R for Windows<\/b> &gt; <b>base<\/b> &gt; Download the latest R executable and install it using default settings.<\/li>\n            <li>Go back to the Windows page, click <b>Rtools<\/b>, and install the version matching your R installation. This is critical for compiling quantitative packages later.<\/li>\n        <\/ul>\n    <\/li>\n    <li><b>For macOS:<\/b> \n        <ul>\n            <li>Click <b>Download R for macOS<\/b> and select the <code>.pkg<\/code> matching your chip (Apple Silicon or Intel).<\/li>\n            <li>To ensure packages compile correctly, open your Mac <b>Terminal<\/b> and run <code>xcode-select --install<\/code> to get the necessary developer tools.<\/li>\n        <\/ul>\n    <\/li>\n<\/ol>\n \n \n<h3>Step 2: Install RStudio<\/h3>\n \n<p>Now, we install the integrated development environment (IDE) that we will use to write and execute R code.<\/p>\n \n<ol>\n    <li>Head to the <a href=\"https:\/\/posit.co\/download\/rstudio-desktop\/\" target=\"_blank\">Posit RStudio Desktop website<\/a>.<\/li>\n    <li>Download the free version corresponding to your operating system (Windows or MacOS).<\/li>\n    <li>Run the installer. RStudio will automatically detect the base R engine you deployed in Step 1.<\/li>\n<\/ol>\n \n \n<h3>Step 3: Install libraries from CRAN<\/h3>\n \n<p>Because R uses a centralized package repository, we can install our financial tools directly into RStudio and do not have to install any other software.<\/p>\n \n<ol>\n    <li>Launch <b>RStudio<\/b>.<\/li>\n    <li>In the <b>Console<\/b> pane (bottom-left), type the following command and press Enter. This will reach out to CRAN and download the essential tools for market data and time-series analysis:<\/li>\n<\/ol>\n \n<pre style=\"background-color: #f6f8fa;border: 1px solid #d0d7de;border-radius: 6px;padding: 16px;font-size: 13px;line-height: 1.45\">\n<code style=\"font-family: monospace;white-space: pre\">\n<span style=\"color: #6a737d\"># Install quantmod for data retrieval, xts for time-series, and PerformanceAnalytics for risk metrics<\/span>\ninstall.packages(c(\"quantmod\", \"xts\", \"PerformanceAnalytics\", \"ggplot2\"))\n<\/code>\n<\/pre>\n\n<div style=\"background-color: #fff8c5;border: 1px solid #d4a72c;border-radius: 6px;padding: 12px;margin: 15px 0;font-size: 13px\">\n  <b>\ud83d\udca1 Quick fix tip:<\/b> If RStudio asks <i>&#8220;Do you want to install from sources the package which needs compilation?&#8221;<\/i>, type <b>Yes<\/b> (or <code>Y<\/code>) in the console and press Enter. This is why we installed RTools\/Xcode in Step 1.\n<\/div>\n \n<p style=\"text-align:center;margin:20px 0\">\n  <img decoding=\"async\" src=\"https:\/\/www.simtrade.fr\/blog_simtrade\/wp-content\/uploads\/2026\/09\/img_packages_download.png\" alt=\"a screenshot of the output of the script when downloading the packages\" width=\"500\" style=\"margin-top:8px;border-radius:8px;max-width: 100%\">\n  <br>\n<\/p>\n\n \n<h2>Checking that everything is working as intended<\/h2>\n \n<p>Let&#8217;s verify your infrastructure by writing a short script that pulls actual market data.<\/p>\n \n<ol>\n    <li>In RStudio, go to <b>File &gt; New File &gt; R Script<\/b>.<\/li>\n    <li>Paste the following quantitative code into the top-left editor pane.<\/li>\n    <li><b>Highlight all the text<\/b> and press <code>Ctrl+Enter<\/code> (Windows) or <code>Cmd+Enter<\/code> (macOS) to run it.<\/li>\n<\/ol>\n \n<pre style=\"background-color: #f6f8fa;border: 1px solid #d0d7de;border-radius: 6px;padding: 16px;font-family: monospace;font-size: 13px;line-height: 1.45;margin: 0\"><code><span style=\"color: #6a737d\"># Load the quantitative financial modeling library<\/span>\nlibrary(quantmod)\n \n<span style=\"color: #6a737d\"># Download historical financial data for Apple via Yahoo Finance API<\/span>\ngetSymbols(\"AAPL\", src = \"yahoo\", from = \"2023-01-01\", to = \"2024-01-01\", auto.assign = TRUE)\n \n<span style=\"color: #6a737d\"># Display the first 5 rows of the time-series array in the console<\/span>\nprint(head(AAPL))\n \n<span style=\"color: #6a737d\"># Generate a financial chart with volume and Bollinger Bands for volatility analysis<\/span>\nchartSeries(AAPL, \n            name = \"Apple Inc. (AAPL) Historical Prices\", \n            theme = chartTheme(\"white\"), \n            TA = c(addVo(), addBBands()))<\/code><\/pre>\n \n<p style=\"text-align:center;margin:20px 0\">\n  <img decoding=\"async\" src=\"https:\/\/www.simtrade.fr\/blog_simtrade\/wp-content\/uploads\/2026\/09\/img_R_Studio_test_script.png\" alt=\"A screenshot of R Studio after running the test script\" width=\"500\" style=\"margin-top:8px;border-radius:8px;max-width: 100%\">\n  <br>\n  <small style=\"color:#555\">After running the script, your R Studio should look like this<\/small>\n<\/p>\n\n\n<p>If the <code>AAPL<\/code> dataset appears in your top-right Environment pane, the data prints in your Console, and a professional candlestick chart renders in your bottom-right Plots pane, your R setup is fully operational.<\/p>\n \n \n<h2>Next steps &amp; use cases<\/h2>\n \n<p>With R correctly configured, you are now equipped to tackle complex econometric and financial challenges. A good next step would be to learn how to download financial data with R.<\/p>\n\n<p>You can learn how to do so in this article: <a href=\"#\">How to download financial data with R<\/a><\/p>\n\n\n<h2>About the Author<\/h2> \n\n<p>This article was written in September 2026 by <a href=\"https:\/\/www.linkedin.com\/in\/hadrienpuche\" target=\"_blank\">Hadrien PUCHE<\/a> (ESSEC Business School, <i>Grande \u00c9cole<\/i> Program, Master in Management, 2023-2027).<\/p>\n\n<p>&nbsp;&nbsp;&nbsp;\u25b6 Discover all articles by <a href=\"https:\/\/www.simtrade.fr\/blog_simtrade\/author\/hpuche\/\" target=\"_parent\">Hadrien PUCHE<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Understanding and writing R code can be a valuable skill for your career. While general-purpose programming languages such as Python are more widely used, R is particularly well suited to statistical analysis, data visualization, and quantitative research. In this article, Hadrien Puche (ESSEC Business School, Grande \u00c9cole Program, Master in Management, 2023-2027) will help you &#8230; <a title=\"How to install and run R on your computer (A step-by-step guide)\" class=\"read-more\" href=\"https:\/\/www.simtrade.fr\/blog_simtrade\/how-to-install-and-run-r-on-your-computer-a-step-by-step-guide\/\" aria-label=\"Read more about How to install and run R on your computer (A step-by-step guide)\">Read more<\/a><\/p>\n","protected":false},"author":163,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[5],"tags":[],"class_list":["post-18968","post","type-post","status-publish","format-standard","hentry","category-contributors"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v26.3 (Yoast SEO v27.2) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>How to install and run R on your computer (A step-by-step guide) - SimTrade blog<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.simtrade.fr\/blog_simtrade\/how-to-install-and-run-r-on-your-computer-a-step-by-step-guide\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"How to install and run R on your computer (A step-by-step guide)\" \/>\n<meta property=\"og:description\" content=\"Understanding and writing R code can be a valuable skill for your career. While general-purpose programming languages such as Python are more widely used, R is particularly well suited to statistical analysis, data visualization, and quantitative research. In this article, Hadrien Puche (ESSEC Business School, Grande \u00c9cole Program, Master in Management, 2023-2027) will help you ... 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