Introduction to R programming language /
Nady, Mohsen, author.
Introduction to R programming language / Mohsen Nady. - Ontario, Canada : Arcler Press, c2022. - xiii, 432 pages : color illustrations.
To access the E-Book : https://www.bibliotex.com/ (Log-in/Register is required).
Includes bibliographical references and index.
Chapter 1 : Installing R and Rstudio
Chapter 2 :Getting started with R and Rstudio
Chapter 3 :Objects and files
Chapter 4 : Vectors and lists
Chapter 5 : Matrices and dataframes
Chapter 6 : Factors and missing values
Chapter 7 : Subsetting objects
Chapter 8 : Dates and times
Chapter 9 : Importing data
Chapter 10 : Basic data wrangling with Tidyverse
Chapter 11 : Data visualization using GGPLOT2
This book covers some introductory steps in using R programming language as a data science tool. The data science field has evolved so much recently with incredible quantities of generated data. To extract value from those data, one needs to be trained in the proper data science skills like statistical analysis, data cleaning, data visualization, and machine learning. R is now considered the centerpiece language for doing all these data science skills because it has many useful packages that not only can perform all the previous skills, but also, has additional packages that was developed by different scientists in diverse fields. These fields include, but are not limited to, business, marketing, microbiology, social science, geography, genomics, environmental science, etc. Furthermore, R is free software and can run on all major platforms: Windows, Mac Os, and UNIX/Linux.
In English text.
9781774692240 (e-book)
R (Computer program language).
Big data--Computer programs.
Mathematical statistical--Data processing.
EBOP QA 276.45.R3 / N33 2022
Introduction to R programming language / Mohsen Nady. - Ontario, Canada : Arcler Press, c2022. - xiii, 432 pages : color illustrations.
To access the E-Book : https://www.bibliotex.com/ (Log-in/Register is required).
Includes bibliographical references and index.
Chapter 1 : Installing R and Rstudio
Chapter 2 :Getting started with R and Rstudio
Chapter 3 :Objects and files
Chapter 4 : Vectors and lists
Chapter 5 : Matrices and dataframes
Chapter 6 : Factors and missing values
Chapter 7 : Subsetting objects
Chapter 8 : Dates and times
Chapter 9 : Importing data
Chapter 10 : Basic data wrangling with Tidyverse
Chapter 11 : Data visualization using GGPLOT2
This book covers some introductory steps in using R programming language as a data science tool. The data science field has evolved so much recently with incredible quantities of generated data. To extract value from those data, one needs to be trained in the proper data science skills like statistical analysis, data cleaning, data visualization, and machine learning. R is now considered the centerpiece language for doing all these data science skills because it has many useful packages that not only can perform all the previous skills, but also, has additional packages that was developed by different scientists in diverse fields. These fields include, but are not limited to, business, marketing, microbiology, social science, geography, genomics, environmental science, etc. Furthermore, R is free software and can run on all major platforms: Windows, Mac Os, and UNIX/Linux.
In English text.
9781774692240 (e-book)
R (Computer program language).
Big data--Computer programs.
Mathematical statistical--Data processing.
EBOP QA 276.45.R3 / N33 2022