Mastering Data Analysis With R

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Mastering Data Analysis With R

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Author : Gergely Daroczi
language : en
Publisher: Packt Publishing Ltd
Release Date : 2015-09-30

Mastering Data Analysis With R written by Gergely Daroczi 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 2015-09-30 with Computers categories.

Gain sharp insights into your data and solve real-world data science problems with R—from data munging to modeling and visualization About This Book Handle your data with precision and care for optimal business intelligence Restructure and transform your data to inform decision-making Packed with practical advice and tips to help you get to grips with data mining Who This Book Is For If you are a data scientist or R developer who wants to explore and optimize your use of R's advanced features and tools, this is the book for you. A basic knowledge of R is required, along with an understanding of database logic. What You Will Learn Connect to and load data from R's range of powerful databases Successfully fetch and parse structured and unstructured data Transform and restructure your data with efficient R packages Define and build complex statistical models with glm Develop and train machine learning algorithms Visualize social networks and graph data Deploy supervised and unsupervised classification algorithms Discover how to visualize spatial data with R In Detail R is an essential language for sharp and successful data analysis. Its numerous features and ease of use make it a powerful way of mining, managing, and interpreting large sets of data. In a world where understanding big data has become key, by mastering R you will be able to deal with your data effectively and efficiently. This book will give you the guidance you need to build and develop your knowledge and expertise. Bridging the gap between theory and practice, this book will help you to understand and use data for a competitive advantage. Beginning with taking you through essential data mining and management tasks such as munging, fetching, cleaning, and restructuring, the book then explores different model designs and the core components of effective analysis. You will then discover how to optimize your use of machine learning algorithms for classification and recommendation systems beside the traditional and more recent statistical methods. Style and approach Covering the essential tasks and skills within data science, Mastering Data Analysis provides you with solutions to the challenges of data science. Each section gives you a theoretical overview before demonstrating how to put the theory to work with real-world use cases and hands-on examples.

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!

Mastering R

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Author : Cybellium
language : en
Publisher: Cybellium Ltd
Release Date : 2023-09-06

Mastering R written by Cybellium and has been published by Cybellium Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-06 with Computers categories.

Cybellium Ltd is dedicated to empowering individuals and organizations with the knowledge and skills they need to navigate the ever-evolving computer science landscape securely and learn only the latest information available on any subject in the category of computer science including: - Information Technology (IT) - Cyber Security - Information Security - Big Data - Artificial Intelligence (AI) - Engineering - Robotics - Standards and compliance Our mission is to be at the forefront of computer science education, offering a wide and comprehensive range of resources, including books, courses, classes and training programs, tailored to meet the diverse needs of any subject in computer science. Visit https://www.cybellium.com for more books.

Mastering Data Analysis With R

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Author : Bharatendra Rai
language : en
Publisher:
Release Date : 2017

Mastering Data Analysis With R written by Bharatendra Rai and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.

"With its popularity as a statistical programming language rapidly increasing with each passing day, R is increasingly becoming the preferred tool of choice for data analysts and data scientists who want to make sense of large amounts of data as quickly as possible. R has a rich set of libraries that can be used for basic as well as advanced data analysis tasks. If you have a basic understanding of data analysis concepts and want to take your skills to the next level, this video is for you. Spanning over four hours, it contains carefully selected advanced data analysis concepts such as: cluster analysis; time-series analysis; Association mining; PCA (Principal Component Analysis); handling missing data; sentiment analysis; spatial data analysis with R and QGIS; advanced data visualization with R and ggplot2. Throughout the video, readers will use the various topics they've learned about to analyze real-world datasets from various industry sectors. By the end of the tutorial, readers will have a thorough understanding of advanced data analysis concepts and how to implement them in R."--Resource description page.

Complete Data Analysis Using R

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Author : Marco Lehmann
language : en
Publisher: SAGE
Release Date : 2022-11-10

Complete Data Analysis Using R written by Marco Lehmann and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-10 with Mathematics categories.

This book gets you up and running with using R in your research project, focusing on data analysis.

R Data Analysis Projects

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Author : Gopi Subramanian
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-11-17

R Data Analysis Projects written by Gopi Subramanian 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 2017-11-17 with Computers categories.

Get valuable insights from your data by building data analysis systems from scratch with R. About This Book A handy guide to take your understanding of data analysis with R to the next level Real-world projects that focus on problems in finance, network analysis, social media, and more From data manipulation to analysis to visualization in R, this book will teach you everything you need to know about building end-to-end data analysis pipelines using R Who This Book Is For If you are looking for a book that takes you all the way through the practical application of advanced and effective analytics methodologies in R, then this is the book for you. A fundamental understanding of R and the basic concepts of data analysis is all you need to get started with this book. What You Will Learn Build end-to-end predictive analytics systems in R Build an experimental design to gather your own data and conduct analysis Build a recommender system from scratch using different approaches Use and leverage RShiny to build reactive programming applications Build systems for varied domains including market research, network analysis, social media analysis, and more Explore various R Packages such as RShiny, ggplot, recommenderlab, dplyr, and find out how to use them effectively Communicate modeling results using Shiny Dashboards Perform multi-variate time-series analysis prediction, supplemented with sensitivity analysis and risk modeling In Detail R offers a large variety of packages and libraries for fast and accurate data analysis and visualization. As a result, it's one of the most popularly used languages by data scientists and analysts, or anyone who wants to perform data analysis. This book will demonstrate how you can put to use your existing knowledge of data analysis in R to build highly efficient, end-to-end data analysis pipelines without any hassle. You'll start by building a content-based recommendation system, followed by building a project on sentiment analysis with tweets. You'll implement time-series modeling for anomaly detection, and understand cluster analysis of streaming data. You'll work through projects on performing efficient market data research, building recommendation systems, and analyzing networks accurately, all provided with easy to follow codes. With the help of these real-world projects, you'll get a better understanding of the challenges faced when building data analysis pipelines, and see how you can overcome them without compromising on the efficiency or accuracy of your systems. The book covers some popularly used R packages such as dplyr, ggplot2, RShiny, and others, and includes tips on using them effectively. By the end of this book, you'll have a better understanding of data analysis with R, and be able to put your knowledge to practical use without any hassle. Style and approach This book takes a unique, learn-as-you-do approach, as you build on your understanding of data analysis progressively with each project. This book is designed in a way that implementing each project will empower you with a unique skill set, and enable you to implement the next project more confidently.

An Introduction To R And Python For Data Analysis

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Author : Taylor R. Brown
language : en
Publisher: CRC Press
Release Date : 2023-06-28

An Introduction To R And Python For Data Analysis written by Taylor R. Brown and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-28 with Mathematics categories.

An Introduction to R and Python for Data Analysis helps teach students to code in both R and Python simultaneously. As both R and Python can be used in similar manners, it is useful and efficient to learn both at the same time, helping lecturers and students to teach and learn more, save time, whilst reinforcing the shared concepts and differences of the systems. This tandem learning is highly useful for students, helping them to become literate in both languages, and develop skills which will be handy after their studies. This book presumes no prior experience with computing, and is intended to be used by students from a variety of backgrounds. The side-by-side formatting of this book helps introductory graduate students quickly grasp the basics of R and Python, with the exercises providing helping them to teach themselves the skills they will need upon the completion of their course, as employers now ask for competency in both R and Python. Teachers and lecturers will also find this book useful in their teaching, providing a singular work to help ensure their students are well trained in both computer languages. All data for exercises can be found here: https://github.com/tbrown122387/r_and_python_book/tree/master/data. Instructors can access the solutions manual via the book's website. Key features: - Teaches R and Python in a "side-by-side" way. - Examples are tailored to aspiring data scientists and statisticians, not software engineers. - Designed for introductory graduate students. - Does not assume any mathematical background.

Beginner S Guide To R Programming

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Author : Agasti Khatri
language : en
Publisher: Educohack Press
Release Date : 2025-02-20

Beginner S Guide To R Programming written by Agasti Khatri and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-20 with Computers categories.

Discover the world of data analysis with "Beginner's Guide to R Programming." This comprehensive resource is crafted to help individuals learn the R programming language and explore its diverse applications. Whether you're a complete beginner or an experienced analyst, our book offers a structured learning path that starts with the basics and progresses to advanced topics like statistical analysis, data visualization, and machine learning. Each chapter includes practical examples, exercises, and real-world case studies, encouraging hands-on experimentation with R code. You'll delve into data types, functions, data manipulation, statistical analysis, data visualization, and more, building a solid foundation in R programming and data analysis. Complex concepts are explained in clear, easy-to-understand language, with visual aids, code snippets, and step-by-step tutorials to help you grasp key ideas effectively. The book emphasizes practical applications of R in real-world scenarios, showcasing how you can use R to solve problems, analyze data, make informed decisions, and communicate insights. With access to supplementary resources, including downloadable datasets, code samples, and additional exercises, you'll further enhance your learning experience and practice your skills.

R For Basic And Applied Sciences

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Author : JANARDHAN KADARI
language : en
Publisher: Shashwat Publication
Release Date : 2023-11-22

R For Basic And Applied Sciences written by JANARDHAN KADARI and has been published by Shashwat Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-22 with Computers categories.

R is a Statistcal programming language. R is Free and open source. R is an interpreted language not a compiled one. The R programming environment contains the range of tools for parallel computing, machine and deep learning and for working with big Data, including Torch and Tensar flow facilitating construction and implementation of neural networks. The Bioconductor repository contains over a thousand of software packages written in R for analyzing data sets from CDNA microarrays to copy-number variation and epigenomics (Robert Gentleman-Sorin Draghicia). Due to Data Handling and Modeling capabilities and its flexibility, R is becoming the most widely used software in bioinformatics. The R program is built from a variety of packages. These packages are libraries of commands. The Packages are available from the CRAN website. The current R is the result of a collaborative effort of the R core Group. R has many functions for statistical analysis and graphics. R has an effective data handling and storage facility. R provides operators for calculation on arrays, vectors, lists and matrices. This Book Covers all these with suitable examples. R has a collection of tools for data analysis. Keeping in view the Beginners apprehensions the Book provides the Salient Features of Descriptive Statistics & Covers the specific R tools for Statistical analysis. Throughout the Book examples are accompanied by R commands for easy reference. This Book Covers data handling, graphics, and a wide range of Statistical techniques. The Book would be of immense help to basic sciences, Engineering, Business Statistics, medicine streams, Biotechnology, Pharma, Bioinformatics, Genetics and Epidemiology.

Python For R Users

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Author : Ajay Ohri
language : en
Publisher: John Wiley & Sons
Release Date : 2017-11-01

Python For R Users written by Ajay Ohri and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-01 with Computers categories.

The definitive guide for statisticians and data scientists who understand the advantages of becoming proficient in both R and Python The first book of its kind, Python for R Users: A Data Science Approach makes it easy for R programmers to code in Python and Python users to program in R. Short on theory and long on actionable analytics, it provides readers with a detailed comparative introduction and overview of both languages and features concise tutorials with command-by-command translations—complete with sample code—of R to Python and Python to R. Following an introduction to both languages, the author cuts to the chase with step-by-step coverage of the full range of pertinent programming features and functions, including data input, data inspection/data quality, data analysis, and data visualization. Statistical modeling, machine learning, and data mining—including supervised and unsupervised data mining methods—are treated in detail, as are time series forecasting, text mining, and natural language processing. • Features a quick-learning format with concise tutorials and actionable analytics • Provides command-by-command translations of R to Python and vice versa • Incorporates Python and R code throughout to make it easier for readers to compare and contrast features in both languages • Offers numerous comparative examples and applications in both programming languages • Designed for use for practitioners and students that know one language and want to learn the other • Supplies slides useful for teaching and learning either software on a companion website Python for R Users: A Data Science Approach is a valuable working resource for computer scientists and data scientists that know R and would like to learn Python or are familiar with Python and want to learn R. It also functions as textbook for students of computer science and statistics. A. Ohri is the founder of Decisionstats.com and currently works as a senior data scientist. He has advised multiple startups in analytics off-shoring, analytics services, and analytics education, as well as using social media to enhance buzz for analytics products. Mr. Ohri's research interests include spreading open source analytics, analyzing social media manipulation with mechanism design, simpler interfaces for cloud computing, investigating climate change and knowledge flows. His other books include R for Business Analytics and R for Cloud Computing.