R Programming For Data Science
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R For Data Science
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Author : Hadley Wickham
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2023-06-08
R For Data Science written by Hadley Wickham and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-08 with Computers categories.
Use R to turn data into insight, knowledge, and understanding. With this practical book, aspiring data scientists will learn how to do data science with R and RStudio, along with the tidyverse—a collection of R packages designed to work together to make data science fast, fluent, and fun. Even if you have no programming experience, this updated edition will have you doing data science quickly. You'll learn how to import, transform, and visualize your data and communicate the results. And you'll get a complete, big-picture understanding of the data science cycle and the basic tools you need to manage the details. Updated for the latest tidyverse features and best practices, new chapters show you how to get data from spreadsheets, databases, and websites. Exercises help you practice what you've learned along the way. You'll understand how to: Visualize: Create plots for data exploration and communication of results Transform: Discover variable types and the tools to work with them Import: Get data into R and in a form convenient for analysis Program: Learn R tools for solving data problems with greater clarity and ease Communicate: Integrate prose, code, and results with Quarto
R Programming For Data Science
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Author : Roger D. Peng
language : en
Publisher:
Release Date : 2012-04-19
R Programming For Data Science written by Roger D. Peng and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-04-19 with R (Computer program language) categories.
Data science has taken the world by storm. Every field of study and area of business has been affected as people increasingly realize the value of the incredible quantities of data being generated. But to extract value from those data, one needs to be trained in the proper data science skills. The R programming language has become the de facto programming language for data science. Its flexibility, power, sophistication, and expressiveness have made it an invaluable tool for data scientists around the world. This book is about the fundamentals of R programming. You will get started with the basics of the language, learn how to manipulate datasets, how to write functions, and how to debug and optimize code. With the fundamentals provided in this book, you will have a solid foundation on which to build your data science toolbox.
R Programming For Data Analysis
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Author : Peter Simon
language : en
Publisher: Peter Simon
Release Date :
R Programming For Data Analysis 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.
Unlock the Power of Data with R Programming for Data Analysis — Your Complete Guide from Beginner to Expert! Are you eager to master data analytics using R programming but unsure where to start? Whether you're a student, aspiring data analyst, or professional looking to upskill, this book is the perfect starting point to learn R for data analysis and become proficient with one of the most powerful tools in the industry. What Makes This Book Your Ultimate Resource for Data Analysis Using R Software? This comprehensive guide covers everything you need to confidently use R software data analysis tools, starting from installation to mastering essential programming concepts. You’ll learn how to harness the full potential of the R language for data science and data analytics with R programming to unlock actionable insights from your data. Inside You’ll Discover: Step-by-step guidance on setting up R and RStudio, the leading R data analysis software, so you can get started quickly. Master core data structures in R language data analysis: vectors, lists, data frames, and factors—building blocks for efficient data analysis using R programming. Practical techniques for cleaning, transforming, and visualizing data—skills every R data analyst needs. How to apply data science with R basics to perform statistical analysis and modeling. Real-world examples that make learning intuitive and effective—like a top R programming course or R programming training session. Who Should Read This? Beginners wanting to learn R programming specifically for data science with R Analysts seeking to upgrade their skills using the best r analysis software Students enrolled in a data science with R course or anyone learning the r programming language course Professionals eager to master r coding language for actionable data analytics R programming Why Choose This Book Over Others? This isn’t just another technical manual. It’s designed to simplify the complexities of R programming for data analysis with clear explanations, practical exercises, and a focus on real-world applications. Whether you want to become a skilled R language for data analytics professional or simply want to understand your data better, this book makes it achievable. Start your journey to becoming a confident data analyst today. Scroll up and order R Programming for Data Analysis now—unlock insights, drive decisions, and transform data into success!
Beginning Data Science In R
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Author : Thomas Mailund
language : en
Publisher: Apress
Release Date : 2017-03-09
Beginning Data Science In R written by Thomas Mailund and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-09 with Computers categories.
Discover best practices for data analysis and software development in R and start on the path to becoming a fully-fledged data scientist. This book teaches you techniques for both data manipulation and visualization and shows you the best way for developing new software packages for R. Beginning Data Science in R details how data science is a combination of statistics, computational science, and machine learning. You’ll see how to efficiently structure and mine data to extract useful patterns and build mathematical models. This requires computational methods and programming, and R is an ideal programming language for this. This book is based on a number of lecture notes for classes the author has taught on data science and statistical programming using the R programming language. Modern data analysis requires computational skills and usually a minimum of programming. What You Will Learn Perform data science and analytics using statistics and the R programming language Visualize and explore data, including working with large data sets found in big data Build an R package Test and check your code Practice version control Profile and optimize your code Who This Book Is For Those with some data science or analytics background, but not necessarily experience with the R programming language.
Beginner S Guide For Data Analysis Using R Programming
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Author : Jeeva Jose
language : en
Publisher: KHANNA PUBLISHING HOUSE
Release Date :
Beginner S Guide For Data Analysis Using R Programming written by Jeeva Jose and has been published by KHANNA PUBLISHING HOUSE this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
R programming is an efficient tool for statistical analysis of data. Data science has become critical to each field and the popularity of R is skyrocketing. Organization as large and diverse as Google, Facebook, Microsoft, Bank of America, Ford Motor Company, Mozilla, Thomas Cook, The New York Times, The National Weather Service, Twitter, ANZ Bank, Uber, Airbnb etc . have turned to R for reporting, analyzing and visualization of data, this book is for students and professionals of Mathematics, Statistics, Physics, Chemistry, Biology, Social Science and Medicine, Business, Engineering, Software, Information Technology, Sales, Bio Informatics, Pharmacy and any one, where data needs to be analyzed and represented graphically.
Beginning Data Science In R 4
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Author : Thomas Mailund
language : en
Publisher: Apress
Release Date : 2022-06-28
Beginning Data Science In R 4 written by Thomas Mailund and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-28 with Computers categories.
Discover best practices for data analysis and software development in R and start on the path to becoming a fully-fledged data scientist. Updated for the R 4.0 release, this book teaches you techniques for both data manipulation and visualization and shows you the best way for developing new software packages for R. Beginning Data Science in R 4, Second Edition details how data science is a combination of statistics, computational science, and machine learning. You’ll see how to efficiently structure and mine data to extract useful patterns and build mathematical models. This requires computational methods and programming, and R is an ideal programming language for this. Modern data analysis requires computational skills and usually a minimum of programming. After reading and using this book, you'll have what you need to get started with R programming with data science applications. Source code will be available to support your next projects as well. What You Will Learn Perform data science and analytics using statistics and the R programming language Visualize and explore data, including working with large data sets found in big data Build an R package Test and check your code Practice version control Profile and optimize your code Who This Book Is For Those with some data science or analytics background, but not necessarily experience with the R programming language.
R For Data Science
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Author : Dan Toomey
language : en
Publisher: Packt Publishing Ltd
Release Date : 2014-12-24
R For Data Science written by Dan Toomey 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 2014-12-24 with Computers categories.
If you are a data analyst who has a firm grip on some advanced data analysis techniques and wants to learn how to leverage the features of R, this is the book for you. You should have some basic knowledge of the R language and should know about some data science topics.
R Programming For Beginners
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Author : Anshuman Mishra
language : en
Publisher: Independently Published
Release Date : 2025-01-09
R Programming For Beginners written by Anshuman Mishra and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-09 with categories.
"R Programming for Beginners: Unlock the Power of Data" is designed as the ultimate guide for those who are new to programming and data analysis. Whether you're a student, professional, or someone just starting their journey with R, this book will provide you with the foundation needed to work confidently with data. Through easy-to-follow explanations, practical examples, and hands-on exercises, this book introduces the basic concepts of R programming, including its syntax, data structures, and built-in functions. You'll learn how to import, manipulate, and visualize data using R and develop a strong understanding of statistical analysis. By the end of this book, you will have the skills necessary to solve real-world problems using R and be well-prepared to dive into more advanced topics or data science projects. How to Study This Book 1. Follow the Structure Step-by-Step: Each chapter is designed to build upon the previous one. It's essential to go through the chapters sequentially to understand the logical flow of learning. Start from the basics and gradually move toward more complex topics. 2. Hands-On Practice: R programming is all about practice. Make sure to work through the exercises and examples provided in each chapter. Don't just read; actively try to write code, run it in RStudio, and experiment with different commands. The more you practice, the more comfortable you'll become with R. 3. Use the R Help System: If you encounter any difficulties or are unsure about a particular function, use R's built-in help system. Each chapter includes tips on how to search for documentation within RStudio or the online R community. 4. Learn by Solving Problems: After completing each chapter, challenge yourself by solving small problems. You can find simple datasets online and apply what you've learned to analyze them, or create your own datasets for practice. 5. Review and Reflect: After finishing each section, take a moment to review the key concepts. Try explaining them to someone else or write them down in your own words to solidify your understanding. Benefits of Studying This Book Solid Foundation in R Programming: This book is perfect for beginners, and it helps you develop a strong foundational knowledge of R. By learning the basics correctly, you'll set yourself up for success in more advanced topics in programming and data analysis. Practical, Hands-On Learning: Learning programming requires practice, and this book emphasizes that. With hands-on examples and exercises, you'll gain experience working with real data, making it easier to apply R in real-world scenarios. Data Science Skills: R is one of the most popular programming languages for data analysis, statistics, and visualization. By mastering R through this book, you will acquire essential data science skills, opening doors to numerous opportunities in fields like business, research, and technology. Understand Data Visualization: The book provides detailed coverage of data visualization techniques using R, particularly through the ggplot2 package. Mastering data visualization is an invaluable skill for anyone working with data and helps communicate insights effectively. Boost Confidence in Data-Driven Decision Making: By learning how to manipulate and analyze data, you will develop the ability to make informed, data-driven decisions. Whether you're conducting research, making business decisions, or pursuing academic goals, knowing R will give you the tools to work with data effectively. Prepare for Advanced Learning: This book serves as a stepping stone to more advanced R programming or data science topics.
R Programming
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Author : Daniel Daniel Bell
language : en
Publisher:
Release Date : 2020-06
R Programming written by Daniel Daniel Bell and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06 with categories.
2020- Second Edition, updated version. Get your copy!! Why Learn R? What are the reasons to learn R for Data Science? In this small textbook recommended for absolute beginners, the author tried to answer these types of questions. After reading this guide, maybe in one or two days, you will learn the basics of R programming and its utility for each Data Scientist. Indeed, R is a programming language and software environment for statistical analysis, graphics representation, and reporting. If you are trying to understand the R programming language as a beginner, this short book will give you enough understanding of almost all the concepts of the R language. The author will guide you through examples, how to program in R and how to use R for effective data analysis.Get your copy Now! Book Objectives This book is about R programming. The following are the objectives of the author: To familiarize you with the basics of R programming language. To help you understand the various fields where R can be applied and its use cases in each field. To equip you with R programming skills, both beginner and advanced skills. To introduce you to R programming for data analysis. To introduce you to R programming for machine learning. To help you understand and appreciate the power of R in statistical computing, data analysis, and scientific research. Who this Book is for? Anybody who is a complete beginner to R Programming. Anybody in need of advancing their R Programming skills. Professionals in computer programming. Professors, lecturers or tutors who are looking to find better ways to explain R programming to their students in the simplest and easiest way. Students and academicians, especially those focusing on R, Data Analysis,Machine Learning , computer science, and Databases development. Requirements The author expects you to have a computer installed with an operating system such as Linux, Windows or Mac OS X. What is inside the book? R BASICS R DATA TYPES R VARIABLES AND CONSTANTS R OPERATORS DECISION MAKING IN R R LOOPS R FUNCTIONS R CLASSES AND OBJECTS R FOR DATA SCIENCE R FOR MACHINE LEARNING From the Back Cover. R programming language is one of the most popular languages used by statisticians, data analysts, researchers to retrieve, clean, analyze, visualize and present data. This is a comprehensive book on how to get started with R programming, why you should learn it and how you can learn it. Daniel Bell begins by introducing the readers to the foundations of the R programming language. The aim is to help you understand, how the R interpreter works, the origin of the name R, how to set up the R programming environment, etc. The author has discussed the process of installing R on Windows, Linux and Mac OS. Moreover, the author has explored the basics of R programming including writing comments, using the R console, creating R script files, etc. The various features provided by R have been discussed in depth, including data types, variables, loops, decision making, functions, operators, classes, and objects, etc. The author has also discussed R for data science and R for machine learning. The book has been organized into chapters, with each chapter having many sub-chapters. R code scripts have been provided, alongside thorough explanations of the code and images showing the expected output upon the execution of every script. Get your copy
R Programming
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Author : Ajit Singh
language : en
Publisher:
Release Date : 2020-07-23
R Programming written by Ajit Singh and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-23 with categories.
Data science is an exciting discipline that allows you to turn raw data into understanding, insight, and knowledge. The goal of "R for Data Science" is to help you learn the most important tools in R that will allow you to do data science. After reading this book, you'll have the tools to tackle a wide variety of data science challenges, using the best parts of R. This book will teach you how to program in R. You'll go from loading data to writing your own functions (which will outperform the functions of other R users).This is an understandable approach to learning R. Visualizing and modeling data are complicated skills that require a programmer's full attention. It takes expertise, judgement, and focus to extract reliable insights from a data set. This book proudly focuses on small, in-memory datasets. This is the right place to start because you can't tackle big data unless you have experience with small data. I think R is a great place to start your data science journey because it is an environment designed from the ground up to support data science. R is not just a programming language, but it is also an interactive environment for doing data science. Simply In Depth....