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Data Analysis and Visualization with R for beginners
Rating: 3.7 out of 5(13 ratings)
1,743 students

Data Analysis and Visualization with R for beginners

Data exploration and Visualization using R
Last updated 3/2026
English

What you'll learn

  • Install R and RStudio
  • Create new R Projects
  • Create R variables (objects)
  • Install and load R Packages
  • Import data into R Studio
  • Perform data wrangling on your data
  • Pipe several functions into a dataset using the Pipe function
  • Create data visualizations using graphs
  • Read data into a variable

Course content

3 sections29 lectures2h 1m total length
  • Introduction0:20
  • What is R
  • Installing R on Windows2:01
  • Installing R on Mac0:03
  • What is R Studio
  • Installing R studio on Windows1:50
  • Installing R Studio on Mac0:03
  • Exploring R Studio Default Interface9:32
  • Creating a new project in R Studio5:34
  • What are Packages0:44
  • How to install Packages4:19
  • Data sets vs Data frames0:17
  • Loading Packages6:38

Requirements

  • R and R Studio installation required. (This is covered in the course)

Description

R is a programming language. R is often used for statistical computing and graphical presentation to analyse and visualize data.

R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, …) and graphical techniques, and is highly extensible.

One of R’s strengths is the ease with which well-designed publication-quality plots can be produced, including mathematical symbols and formulae where needed.

R is available as Free Software under the terms of the Free Software Foundation’s GNU General Public License in source code form. It compiles and runs on a wide variety of UNIX platforms and similar systems (including FreeBSD and Linux), Windows and MacOS.

R is an integrated suite of software facilities for data manipulation, calculation and graphical display. It includes

  • an effective data handling and storage facility,

  • a suite of operators for calculations on arrays, in particular matrices,

  • a large, coherent, integrated collection of intermediate tools for data analysis,

  • graphical facilities for data analysis and display either on-screen or on hardcopy, and

  • a well-developed, simple and effective programming language which includes conditionals, loops, user-defined recursive functions and input and output facilities.


  • R can be extended (easily) via packages. There are about eight packages supplied with the R distribution and many more are available through the CRAN family of Internet sites covering a very wide range of modern statistics.


RStudio is an integrated development environment for R, a programming language for statistical computing and graphics. It is available in two formats: RStudio Desktop is a regular desktop application while RStudio Server runs on a remote server and allows accessing RStudio using a web browser.

Who this course is for:

  • Beginners to data analysis and visualization using R