R 4 Data Science Quick Reference

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R 4 Data Science Quick Reference

R 4 Data Science Quick Reference 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 2022-11-12 with Computers categories.

In this handy, quick reference book you'll be introduced to several R data science packages, with examples of how to use each of them. All concepts will be covered concisely, with many illustrative examples using the following APIs: readr, dibble, forecasts, lubridate, stringr, tidyr, magnittr, dplyr, purrr, ggplot2, modelr, and more. With R 4 Data Science Quick Reference, you'll have the code, APIs, and insights to write data science-based applications in the R programming language. You'll also be able to carry out data analysis. All source code used in the book is freely available on GitHub.. What You'll Learn Implement applicable R 4 programming language specification features Import data with readr Work with categories using forcats, time and dates with lubridate, and strings with stringr Format data using tidyr and then transform that data using magrittr and dplyr Write functions with R for data science, data mining, and analytics-based applications Visualize data with ggplot2 and fit data to models using modelr Who This Book Is For Programmers new to R's data science, data mining, and analytics packages. Some prior coding experience with R in general is recommended.

R Data Science Quick Reference

R Data Science Quick Reference 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 2019-08-07 with Computers categories.

In this handy, practical book you will cover each concept concisely, with many illustrative examples. You'll be introduced to several R data science packages, with examples of how to use each of them. In this book, you’ll learn about the following APIs and packages that deal specifically with data science applications: readr, dibble, forecasts, lubridate, stringr, tidyr, magnittr, dplyr, purrr, ggplot2, modelr, and more. After using this handy quick reference guide, you'll have the code, APIs, and insights to write data science-based applications in the R programming language. You'll also be able to carry out data analysis. What You Will Learn Import data with readr Work with categories using forcats, time and dates with lubridate, and strings with stringr Format data using tidyr and then transform that data using magrittr and dplyr Write functions with R for data science, data mining, and analytics-based applications Visualize data with ggplot2 and fit data to models using modelr Who This Book Is For Programmers new to R's data science, data mining, and analytics packages. Some prior coding experience with R in general is recommended.

R For Data Science

R For Data Science written by Hadley Wickham and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-03 with Computers categories.

Learn how to use R to turn data into insight, knowledge, and understanding. Ideal for current and aspiring data scientists, this book introduces you to doing data science with R and RStudio, as well as 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. Each section in this edition includes exercises to help you practice what you've learned along the way. Updated for the latest tidyverse best practices, new chapters dive deeper into visualization and data wrangling, show you how to get data from spreadsheets, databases, and websites, and help you make the most of new programming tools. You'll learn how to: Visualize-create plots for data exploration and communication of results Transform-discover types of variables and the tools you can use 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 For Data Science

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.

Cover -- Copyright -- Table of Contents -- Preface -- What You Will Learn -- How This Book Is Organized -- What You Won't Learn -- Big Data -- Python, Julia, and Friends -- Nonrectangular Data -- Hypothesis Confirmation -- Prerequisites -- R -- RStudio -- The Tidyverse -- Other Packages -- Running R Code -- Getting Help and Learning More -- Acknowledgments -- Online Version -- Conventions Used in This Book -- Using Code Examples -- O'Reilly Online Learning -- How to Contact Us -- Part I. Explore -- Chapter 1. Data Visualization with ggplot2 -- Introduction -- Prerequisites -- First Steps -- The mpg Data Frame -- Creating a ggplot -- A Graphing Template -- Exercises -- Aesthetic Mappings -- Exercises -- Common Problems -- Facets -- Exercises -- Geometric Objects -- Exercises -- Statistical Transformations -- Exercises -- Position Adjustments -- Exercises -- Coordinate Systems -- Exercises -- The Layered Grammar of Graphics -- Chapter 2. Workflow: Basics -- Coding Basics -- What's in a Name? -- Calling Functions -- Exercises -- Chapter 3. Data Transformation with dplyr -- Introduction -- Prerequisites -- nycflights13 -- dplyr Basics -- Filter Rows with filter() -- Comparisons -- Logical Operators -- Missing Values -- Exercises -- Arrange Rows with arrange() -- Exercises -- Select Columns with select() -- Exercises -- Add New Variables with mutate() -- Useful Creation Functions -- Exercises -- Grouped Summaries with summarize() -- Combining Multiple Operations with the Pipe -- Missing Values -- Counts -- Useful Summary Functions -- Grouping by Multiple Variables -- Ungrouping -- Exercises -- Grouped Mutates (and Filters) -- Exercises -- Chapter 4. Workflow: Scripts -- Running Code -- RStudio Diagnostics -- Exercises -- Chapter 5. Exploratory Data Analysis -- Introduction -- Prerequisites -- Questions -- Variation -- Visualizing Distributions.

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Guide To U S Government Publications

Guide To U S Government Publications written by and has been published by Gale Cengage this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-08 with Language Arts & Disciplines categories.

This comprehensive yet concise annual annotated reference source catalogs the important series, periodicals and reference tools published by U.S. government agencies. Over the years, the index section of the Guide to U.S. Government Publications has expanded to more than 40,000 entries. Agencies and titles are indexed, followed by a keyword title index for quick and easy referencing. No other single resource provides historical and current information on U.S. government publications in one place.

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A world list of books in the English language.

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Government Reports Annual Index written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with Government reports announcements & index categories.