Introduction to R programming language / Mohsen Nady.
Material type:
TextPublication details: Ontario, Canada : Arcler Press, c2022.Description: xiii, 432 pages : color illustrationsContent type: - text
- computer
- online resource
- 9781774692240 (e-book)
- EBOP QA 276.45.R3 N33 2022
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Cavite State University - CCAT Campus | Electronic Resources | ER | EBOP QA 276.45.R3 N33 2022 (Browse shelf(Opens below)) | 1 | Available | EBOP0000087 |
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| EBOP QA 76.77 O64 2018 Operating Systems / | EBOP QA 76.87 S73 2019 Applied neural networks and soft computing / Ivan Stanimirovic | EBOP QA 76.575 A38 2022 Advances in multimedia / | EBOP QA 276.45.R3 N33 2022 Introduction to R programming language / | EBOP QA 184 M66 2018 Linear algebra : theorems and applications / | EBOP QA 241 N86 2020 Number theory with applications to cryptography / | EBOP QA 263 M48 2018 Methods of matrix algebra / |
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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.
EBOP00087 1
In English text.
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