R Programming Fundamentals

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R Programming Fundamentals

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Author : Kaelen Medeiros
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-09-27

R Programming Fundamentals written by Kaelen Medeiros and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-27 with Computers categories.

Study data analysis and visualization to successfully analyze data with R Key FeaturesGet to grips with data cleaning methodsExplore statistical concepts and programming in R, including best practicesBuild a data science project with real-world examplesBook Description R Programming Fundamentals, focused on R and the R ecosystem, introduces you to the tools for working with data. To start with, you’ll understand you how to set up R and RStudio, followed by exploring R packages, functions, data structures, control flow, and loops. Once you have grasped the basics, you’ll move on to studying data visualization and graphics. You’ll learn how to build statistical and advanced plots using the powerful ggplot2 library. In addition to this, you’ll discover data management concepts such as factoring, pivoting, aggregating, merging, and dealing with missing values. By the end of this book, you’ll have completed an entire data science project of your own for your portfolio or blog. What you will learnUse basic programming concepts of R such as loading packages, arithmetic functions, data structures, and flow controlImport data to R from various formats such as CSV, Excel, and SQLClean data by handling missing values and standardizing fieldsPerform univariate and bivariate analysis using ggplot2Create statistical summary and advanced plots such as histograms, scatter plots, box plots, and interaction plotsApply data management techniques, such as factoring, pivoting, aggregating, merging, and dealing with missing values, on the example datasetsWho this book is for R Programming Fundamentals is for you if you are an analyst who wants to grow in the field of data science and explore the latest tools.

R Programming Fundamentals

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Author : Samik Sen
language : en
Publisher:
Release Date : 2018

R Programming Fundamentals written by Samik Sen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.

"R Programming Fundamentals, focused on R and the R ecosystem, introduces you to the tools for working with data. To start with, you'll understand you how to set up R and RStudio, followed by exploring R packages, functions, data structures, control flow, and loops. Once you have grasped the basics, you'll move on to studying data visualization and graphics. You'll learn how to build statistical and advanced plots using the powerful ggplot2 library. In addition to this, you'll discover data management concepts such as factoring, pivoting, aggregating, merging, and dealing with missing values. By the end of this course, you'll have completed an entire data science project of your own for your portfolio or blog."--Resource description page.

R Programming Fundamentals

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Author : Kaelen Medeiros
language : en
Publisher:
Release Date : 2018-09-27

R Programming Fundamentals written by Kaelen Medeiros and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-27 with Computers categories.

Study data analysis and visualization to successfully analyze data with R Key Features Get to grips with data cleaning methods Explore statistical concepts and programming in R, including best practices Build a data science project with real-world examples Book Description R Programming Fundamentals, focused on R and the R ecosystem, introduces you to the tools for working with data. To start with, you'll understand you how to set up R and RStudio, followed by exploring R packages, functions, data structures, control flow, and loops. Once you have grasped the basics, you'll move on to studying data visualization and graphics. You'll learn how to build statistical and advanced plots using the powerful ggplot2 library. In addition to this, you'll discover data management concepts such as factoring, pivoting, aggregating, merging, and dealing with missing values. By the end of this book, you'll have completed an entire data science project of your own for your portfolio or blog. What you will learn Use basic programming concepts of R such as loading packages, arithmetic functions, data structures, and flow control Import data to R from various formats such as CSV, Excel, and SQL Clean data by handling missing values and standardizing fields Perform univariate and bivariate analysis using ggplot2 Create statistical summary and advanced plots such as histograms, scatter plots, box plots, and interaction plots Apply data management techniques, such as factoring, pivoting, aggregating, merging, and dealing with missing values, on the example datasets Who this book is for R Programming Fundamentals is for you if you are an analyst who wants to grow in the field of data science and explore the latest tools.

R Programming By Example

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Author : Omar Trejo Navarro
language : en
Publisher:
Release Date : 2017-12-22

R Programming By Example written by Omar Trejo Navarro and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-22 with Computers categories.

This step-by-step guide demonstrates how to build simple-to-advanced applications through examples in R using modern tools. Key Features Get a firm hold on the fundamentals of R through practical hands-on examples Get started with good R programming fundamentals for data science Exploit the different libraries of R to build interesting applications in R Book Description R is a high-level statistical language and is widely used among statisticians and data miners to develop analytical applications. Often, data analysis people with great analytical skills lack solid programming knowledge and are unfamiliar with the correct ways to use R. Based on the version 3.4, this book will help you develop strong fundamentals when working with R by taking you through a series of full representative examples, giving you a holistic view of R. We begin with the basic installation and configuration of the R environment. As you progress through the exercises, you'll become thoroughly acquainted with R's features and its packages. With this book, you will learn about the basic concepts of R programming, work efficiently with graphs, create publication-ready and interactive 3D graphs, and gain a better understanding of the data at hand. The detailed step-by-step instructions will enable you to get a clean set of data, produce good visualizations, and create reports for the results. It also teaches you various methods to perform code profiling and performance enhancement with good programming practices, delegation, and parallelization. By the end of this book, you will know how to efficiently work with data, create quality visualizations and reports, and develop code that is modular, expressive, and maintainable. What you will learn Discover techniques to leverage R's features, and work with packages Perform a descriptive analysis and work with statistical models using R Work efficiently with objects without using loops Create diverse visualizations to gain better understanding of the data Understand ways to produce good visualizations and create reports for the results Read and write data from relational databases and REST APIs, both packaged and unpackaged Improve performance by writing better code, delegating that code to a more efficient programming language, or making it parallel Who this book is for This books is for aspiring data science professionals or statisticians who would like to learn about the R programming language in a practical manner. Basic programming knowledge is assumed.

R Programming By Example

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Author : Omar Trejo
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-12-22

R Programming By Example written by Omar Trejo and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-22 with Computers categories.

This step-by-step guide demonstrates how to build simple-to-advanced applications through examples in R using modern tools. About This Book Get a firm hold on the fundamentals of R through practical hands-on examples Get started with good R programming fundamentals for data science Exploit the different libraries of R to build interesting applications in R Who This Book Is For This books is for aspiring data science professionals or statisticians who would like to learn about the R programming language in a practical manner. Basic programming knowledge is assumed. What You Will Learn Discover techniques to leverage R's features, and work with packages Perform a descriptive analysis and work with statistical models using R Work efficiently with objects without using loops Create diverse visualizations to gain better understanding of the data Understand ways to produce good visualizations and create reports for the results Read and write data from relational databases and REST APIs, both packaged and unpackaged Improve performance by writing better code, delegating that code to a more efficient programming language, or making it parallel In Detail R is a high-level statistical language and is widely used among statisticians and data miners to develop analytical applications. Often, data analysis people with great analytical skills lack solid programming knowledge and are unfamiliar with the correct ways to use R. Based on the version 3.4, this book will help you develop strong fundamentals when working with R by taking you through a series of full representative examples, giving you a holistic view of R. We begin with the basic installation and configuration of the R environment. As you progress through the exercises, you'll become thoroughly acquainted with R's features and its packages. With this book, you will learn about the basic concepts of R programming, work efficiently with graphs, create publication-ready and interactive 3D graphs, and gain a better understanding of the data at hand. The detailed step-by-step instructions will enable you to get a clean set of data, produce good visualizations, and create reports for the results. It also teaches you various methods to perform code profiling and performance enhancement with good programming practices, delegation, and parallelization. By the end of this book, you will know how to efficiently work with data, create quality visualizations and reports, and develop code that is modular, expressive, and maintainable. Style and Approach This is an easy-to-understand guide filled with real-world examples, giving you a holistic view of R and practical, hands-on experience.

R Programming For Beginners

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Author : Peter Simon
language : en
Publisher: Peter Simon
Release Date :

R Programming For Beginners written by Peter Simon and has been published by Peter Simon this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.

R Programming for Beginners: Master the Fundamentals of R, Even with Zero Coding Experience The Ultimate Beginner’s Guide to Learning R—Perfect for First-Time Coders, Data Enthusiasts, and Future Analysts! Ready to dive into the world of data but not sure where to start? Whether you're exploring data science with R, planning to take an R programming online course, or just curious about coding, R Programming for Beginners is your go-to guide for mastering the essentials of the R programming language—no technical background needed. This book is more than just a read—it's a hands-on R course for beginners that walks you step by step through real-world examples, making learning R programming for beginners simple, effective, and even fun. 🔍 What This R Programming Book Covers: ✅ Introduction to R Software for Beginners Learn what R is, how to install and use R Studio for beginners, and why it's one of the top tools for data analysis and statistical computing. ✅ Essential R Programming Language Basics Master the core concepts: Data types and variables Vectors, matrices, and data frames Control structures (if statements, loops) Writing custom functions Basic R programs for data manipulation and cleaning ✅ Hands-On Practice for Real Learning Apply what you learn with practical examples and exercises—just like a real R programming course for beginners or an R programming tutorial for beginners would provide. 🎯 Why This Is the Best Way to Learn R Programming Online: 📘 Structured Like an R Programming Language Online Course – With clear progression and learning checkpoints. 💡 Beginner-Friendly Explanations – No jargon. Just step-by-step help for anyone who wants to learn R programming the right way. 💻 Perfect Alternative to an R Software Online Course – Learn at your own pace, with full control. 📊 Built for Data Analysis – This is not just theory—you'll learn how to apply R to real data. 🔧 Your First Step into Data Science with R – Ideal for building a strong foundation before advancing to machine learning, statistics, or big data. 👨‍🏫 Who This R Programming Training Is For: Absolute beginners who want a friendly R language tutorial for beginners Students looking to learn R language for beginners without overwhelming content Professionals starting a data career and seeking an easy-to-follow R software tutorial for beginners Self-learners who want a book-based R programming language course that replaces expensive bootcamps Anyone interested in R programming for dummies-style guidance, minus the fluff 🎁 Bonus Learning Tools Included: Practice datasets and sample code Clear R exercises with solutions Downloadable materials via our R language website Recommendations for the best tools to learn R language online Guidance on how to continue with an R programming online course after completing this book ✅ Start Your R Coding Journey Today If you’ve been searching for a beginner R tutorial that makes sense, or a way to learn R programming without frustration, this is the book for you. Whether you’re taking your first steps or using it as a supplement to an R programming language online course, this beginner guide will help you learn R language fast and with confidence. 🛒 Scroll up and get your copy today—start your journey with R, the powerful programming language for data science, now!

Learn R For Applied Statistics

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Author : Eric Goh Ming Hui
language : en
Publisher: Apress
Release Date : 2018-11-30

Learn R For Applied Statistics written by Eric Goh Ming Hui and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-30 with Computers categories.

Gain the R programming language fundamentals for doing the applied statistics useful for data exploration and analysis in data science and data mining. This book covers topics ranging from R syntax basics, descriptive statistics, and data visualizations to inferential statistics and regressions. After learning R’s syntax, you will work through data visualizations such as histograms and boxplot charting, descriptive statistics, and inferential statistics such as t-test, chi-square test, ANOVA, non-parametric test, and linear regressions. Learn R for Applied Statistics is a timely skills-migration book that equips you with the R programming fundamentals and introduces you to applied statistics for data explorations. What You Will Learn Discover R, statistics, data science, data mining, and big data Master the fundamentals of R programming, including variables and arithmetic, vectors, lists, data frames, conditional statements, loops, and functions Work with descriptive statistics Create data visualizations, including bar charts, line charts, scatter plots, boxplots, histograms, and scatterplots Use inferential statistics including t-tests, chi-square tests, ANOVA, non-parametric tests, linear regressions, and multiple linear regressions Who This Book Is For Those who are interested in data science, in particular data exploration using applied statistics, and the use of R programming for data visualizations.

Fundamentals Of Data Science

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Author : Dr. N. Bharathi, Dr. Jayshri Harde, Mr. Pradeep Kumar Tiwari, Mr. Abhendra Pratap Singh
language : en
Publisher: BR Publications
Release Date : 2025-09-16

Fundamentals Of Data Science written by Dr. N. Bharathi, Dr. Jayshri Harde, Mr. Pradeep Kumar Tiwari, Mr. Abhendra Pratap Singh and has been published by BR Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-16 with Computers categories.

Fundamentals of Data Science” provides a comprehensive introduction to the principles, methodologies, and practical applications of data-driven analysis. The book explores the complete data science pipeline — from data collection, preprocessing, and visualization to statistical modeling, machine learning, and decision-making.

E Learning And Enhancing Soft Skills

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Author : Eugenia Smyrnova-Trybulska
language : en
Publisher: Springer Nature
Release Date : 2025-03-10

E Learning And Enhancing Soft Skills written by Eugenia Smyrnova-Trybulska and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-10 with Education categories.

This volume E-Learning and Enhancing Soft Skills is a collection of articles by participants of the 16th annual scientific international conference “Theoretical and Practical Aspects of Distance Learning: E-Learning and Enhancing of Soft Skills. This conference, held on the 14th and 15th October 2024 in hybrid mode, is organized by the Faculty of Arts and Educational Sciences in Cieszyn, the Faculty of Social Sciences, the Institute of Pedagogy, the Faculty of Science and Technology, the Institute of Computer Science, University of Silesia in Katowice, Poland. Co-organizers and partners included: University of Ostrava (UO), Czech Republic, Silesian University in Opava (SU), Czech Republic, Constantine the Philosopher University in Nitra (UKF) Slovakia, University of Extremadura (UEx), Spain, University of Twente (UT), The Netherlands, Lisbon Lucíada University (LU), Portugal, Curtin University in Perth (CU), Australia, Borys Grinchenko Kyiv University (BGKU), Ukraine, Dniprovsk State Technical University (DSTU), Ukraine, IADIS - International Association for Development, of the Information Society, a non-profit association, Polish Pedagogical Society, Branch in Cieszyn, Polish Scientific Society for Internet Education, Association of Academic E-learning, Poland. Experts on e-learning from different countries provide insights into their studies, present their recent research results and discuss their further scientific work. The authors include experts, well-known scholars, young researchers, highly trained academic lecturers with long experience in the field of e-learning, AI and robotics in education, MOOCs, teacher training an area digutak and soft skills, m-learning, smart technologies, VR/AR; PhD students, distance course developers, authors of multimedia teaching materials, designers of websites and digital educational resources. This monograph therefore describes the theoretical, methodological and practical issues in the field of e-learning and the developing of key competencies and soft skills, contemporary models of education in the era of artificial intelligence, proposing solutions to important problems and showing the road to further research in this field. Built from the findings of an international retinue of scholars, this work will be of particular interest to academic researchers, educators, courseware designers, corporate trainers, and educational technology practitioners.

Introduction To Data Science

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Author : Dr. Sushil Dohare
language : en
Publisher: Xoffencerpublication
Release Date : 2023-04-06

Introduction To Data Science written by Dr. Sushil Dohare and has been published by Xoffencerpublication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-06 with Computers categories.

The response to this inquiry is not at all easy to comprehend. I'm not sure how simple it is to discover someone who has a complete comprehension of what data science is, but I am certain that it would be challenging to locate two individuals who have fewer than three points of view on the topic. I am not sure how simple it is to locate someone who is well-versed in all aspects of what data science entails. Finding a person who is well-versed in all facets of data science may not be as simple as it initially appears to be. I cannot give you a definite answer. It's safe to say that it's a buzzword, and it seems like every data scientist desires it these days; as a result, having a background in data science is a useful thing to add to a résumé. Because of this, the role of "data scientist" has become increasingly common. But what exactly does it mean? Because I am unable to provide you with a definition that the vast majority of people will comprehend, I will instead provide you with the definition that I personally employ: The branch of study known as "Data Science" concentrates on the process of deriving information from other types of information that has been gathered. Data This description touches on so many different areas and almost encompasses so much ground that it is almost incomprehensible. It's not a mystery to me at all. Having said that, I believe that the discipline of data science encompasses a huge breadth of subject areas and subfields. There is nothing that makes me feel less ashamed than that. It is possible that the purpose of any scientific endeavor is to gather information from the evidence that has been gathered, and you may be correct if you argue this point. On the other hand, I would contend that the scientific approach entails more than simply transforming unprocessed data into information that can be understood. This is what I refer to when I make a declaration like this.