Installing R and R studio

Data science is an exciting field that uses scientific approaches, procedures, algorithms, and systems to extract knowledge and insights from structured and unstructured data. R is a powerful language that is widely used for statistical analysis and data analysis. Before we start Installing R and RStudio, let’s learn a little about R. Developed in the nineties, the language has really developed and is used worldwide.

Reasons for Using R Language for Data Science

  • The style of coding is quite easy
  • It is open-source
  • Availability of instant access to over 7800 packages customized for various computation tasks.
  • The online community support is overwhelming. There are numerous forums to help you out.
  • A high-performance computing experience.
  • It’s one of the highly sought skills by analytics and data science companies.

It doesn’t matter if you have a Mac, Windows, or Linux PC. The steps will be similar.

Downloading and Installing R and RStudio

Open a browser and go to https://cran.r-project.org/.

 
Install R and R Studio

Download R for Windows

Select your operating system. Follow the prompts and download the latest version of R for your operating system. Download and run the file to install R. It’s just a standard installation. Leave everything with the default settings.

In Addition, We are going to need an IDE (Integrated Development Environment) to work with R. My personal preference is R Studio. Go to https://www.rstudio.com/ and click the “Download Free Desktop IDE” button. Choose the free version and download RStudio.

installing R and RStudio

RStudio Homepage

Go to “Download Free Desktop IDE” and download your preferred version.

Run the standard installation. Leave everything as default here too. We are ready to start Data Science and Machine Learning using the R language.

Let us continue this tutorial in our next article, Data Preprocessing and Importing the Libraries in R for Data Science

Here are some very useful Data Science Books

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5 Comments

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  2. […] out our Previous Tutorial on How to Install R and R Studio if you haven’t already and if you have, See you on the next […]

  3. […] the dataset from here, save it in that folder and set the folder as the working directory in RStudio. We’re going to use the data in the Salary_Data.csv file to build a Simple Linear Regression […]

  4. […] and welcome to this tutorial. We’re halfway in our data preprocessing phase. We’ve learned how to install R and RStudio, import the dataset, and take care of missing data using the R language. Now I’m going you show […]

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