Ross Ihaka and Robert Gentleman developed a programming language and free software called R in 1993. R is a programming language for mathematical analysis, illustrations, and reporting. The language was named after the first letter of the two developers, Ross and Robert. This language is used in academics and big companies such as Google, Facebook, etc. R writes most of the R libraries, and heavy computation tasks are exceptional.

It also consists of many libraries that are designed only for data science. A variety of tools used to capture the right model for your data is provided by R language.

There are many books that you can use to learn R programming languages. You don’t have to worry about searching for the best books to learn to program because we got you. Look for the systematically arranged book written in a simple language that you can understand with any struggles. A generalized book is what you should go for. You should ask yourself many questions when learning the R programming language.

Top Rated R Programming Books of December 2024

1

R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics

Rating is 5 out of 5

R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics

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2

R in Action: Data Analysis and Graphics with R

Rating is 4.9 out of 5

R in Action: Data Analysis and Graphics with R

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3

Python and R for the Modern Data Scientist: The Best of Both Worlds

Rating is 4.8 out of 5

Python and R for the Modern Data Scientist: The Best of Both Worlds

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4

R for Data Science: Import, Tidy, Transform, Visualize, and Model Data

Rating is 4.7 out of 5

R for Data Science: Import, Tidy, Transform, Visualize, and Model Data

O Reilly Media

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5

Hands-On Programming with R: Write Your Own Functions and Simulations

Rating is 4.6 out of 5

Hands-On Programming with R: Write Your Own Functions and Simulations

O Reilly Media

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6

The Book of R: A First Course in Programming and Statistics

Rating is 4.5 out of 5

The Book of R: A First Course in Programming and Statistics

No Starch Press

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7

The Art of R Programming: A Tour of Statistical Software Design

Rating is 4.4 out of 5

The Art of R Programming: A Tour of Statistical Software Design

No Starch Press

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8

Learning R: A Step-by-Step Function Guide to Data Analysis

Rating is 4.3 out of 5

Learning R: A Step-by-Step Function Guide to Data Analysis

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9

A First Course in Statistical Programming with R

Rating is 4.2 out of 5

A First Course in Statistical Programming with R

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10

Rating is 4.1 out of 5

Discovering Statistics Using R

Sage Publications (CA)

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11

Machine Learning with R: Expert techniques for predictive modeling, 3rd Edition

Rating is 4 out of 5

Machine Learning with R: Expert techniques for predictive modeling, 3rd Edition

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12

Beyond Spreadsheets with R: A beginner's guide to R and RStudio

Rating is 3.9 out of 5

Beyond Spreadsheets with R: A beginner's guide to R and RStudio

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What is R language used for?

R programming language has many uses. The uses are listed below;

Statistical inference

The R programming language and its libraries execute many statistical and graphical operations. The techniques include linear and non-linear modeling, time series analysis, classification, and many others. The users of R’s standard functions can easily follow the algorithmic choices created since it is written in the R language.

Production of publication-quality graphs such as mathematical symbols is dependent on the power of R in static graphics. The supplementary packages of R also have dynamic and interactive graphics.

Data analysis

The data analysis process has been made easy by using the R programming language. Data scientic use this language to come up with an understanding of how we live. It can help when coming up with the right results about the usage of money in the finance sector or the number of crimes committed in a certain period.

Data journalists also use this language to generate the right and correct graphics to tell a story.

Programming

The users of the R language can access it through a command-line interpreter. This makes it an interpreted language. R language supports matrix arithmetic just like APL and MATLAB languages. Its structure includes vectors, arrays, etc. S-expressions represent the date and code in the R language. The R language supports procedural programming and object-oriented programming. R is in charge of the general matrix calculation toolbox, apart from mostly being used by statisticians and practitioners.

Research

Academic and research mostly use the R programming language. The R language is taught in schools for courses that involve statistical computing. Many schools introduce the R programming language before teaching statistics and data analysis to their students.

Retail and e-commerce

R programming language is used for risk assessment and to create marketing strategies in retail and e-commerce.

Why is R so popular?

In Data Science, R programming language is the most popularly used programming language. It also analyses both structured and unstructured data, which has made it the standard language for performing statistical operations. You can execute the code since it is interpreted.

R has made calculations involving vectors easy since it is a vector language. Its popularity has been made possible because it can perform any task since it is a statistical language. Besides being great in the technical field, it is also the best business world. It is a gateway to the highest-paying jobs in the world. It is also popular because it is open-source and can be freely accessed by users. It is also used in many industries while enjoying great support from the community.

Is R an easy programming language?

R language is the easiest programming language you can ever come across. Any beginner of programming is advised to start with the R programming language since it is the easiest. The fact that you don’t need to have experience in coding before taking it up has also made it easier compared to the rest. The presence of a tidyverse collection of packages has made it easier to learn.

Should I Learn R or Python First?

Python and R programming languages are both in demand, and with a piece of knowledge in any of the two, you can tackle any data analytic task. You can choose any of the two programming languages depending on your interest, career goal, and your preference.

Python and R language are both regarded as relatively easy to learn. Python was created for software development(you can find some python code examples devhubby), and if you have knowledge or experience in either java or c++, learning python will be easier than learning R. On the other hand, if you have experience in statistics, learning R will be easier. The learning curve of python is smoother, while R tends to be “harder” at the beginning and becomes easier the most of know-how to use its features.

Even though both python and R can be used to do the same task, they differ in strength. You should focus more on one of the two depending on which fits the task you intend to tackle.

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