Tidyverse Skills for Data Science in R
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Tidyverse Skills for Data Science in R

About the Book

This book is intended for data scientists with some familiarity with the R programming language who are seeking to do data science using the Tidyverse family of packages. Through 5 chapters, you will cover importing, wrangling, visualizing, and modeling data using the powerful Tidyverse packages, including the new Tidymodels framework. The Tidyverse packages provide a simple but powerful approach to data science which scales from the most basic analyses to massive data deployments. This book covers the entire life cycle of a data science project and presents specific tidy tools for each stage.

About the Authors

Carrie Wright
Carrie Wright

Carrie Wright is a Research Associate in the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health. She is faculty member of the Johns Hopkins Data Science Lab, where her work focuses on making data science and bioinformatics more approachable to a variety of audiences. She is also a faculty member of the open case studies project (https://www.opencasestudies.org) and a co-founder of the LIBD rstats club (http://research.libd.org/rstatsclub), a community designed to encourage others to learn more about R programming and statistics. Learn more about Carrie at https://carriewright11.github.io/.

Shannon Ellis
Shannon Ellis

Shannon Ellis is an Assistant Teaching Professor in the Cognitive Science Department at UC San Diego.

Roger D. Peng
Roger D. Peng

Roger D. Peng is a Professor of Biostatistics at the Johns Hopkins Bloomberg School of Public Health where his research focuses on the development of statistical methods for addressing environmental health problems. He is the author of the popular book R Programming for Data Science and 10 other books on data science and statistics. He is also the co-creator of the Johns Hopkins Data Science Specialization, the Simply Statistics blog where he writes about statistics for the public, the Not So Standard Deviations podcast with Hilary Parker, and The Effort Report podcast with Elizabeth Matsui. Roger is a Fellow of the American Statistical Association and is the recipient of the Mortimer Spiegelman Award from the American Public Health Association, which honors a statistician who has made outstanding contributions to public health. He can be found on Twitter and GitHub at @rdpeng.

Table of Contents

  • 1. Introduction to the Tidyverse
    • About This Course
    • Tidy Data
    • From Non-Tidy –> Tidy
    • The Data Science Life Cycle
    • The Tidyverse Ecosystem
    • Data Science Project Organization
    • Data Science Workflows
    • Case Studies
  • 2. Importing Data in the Tidyverse
    • About This Course
    • Tibbles
    • Spreadsheets
    • CSVs
    • TSVs
    • Delimited Files
    • Exporting Data from R
    • JSON
    • XML
    • Databases
    • Web Scraping
    • APIs
    • Foreign Formats
    • Images
    • googledrive
    • Case Studies
  • 3. Wrangling Data in the Tidyverse
    • About This Course
    • Tidy Data Review
    • Reshaping Data
    • Data Wrangling
    • Working With Factors
    • Working With Dates and Times
    • Working With Strings
    • Working With Text
    • Functional Programming
    • Exploratory Data Analysis
    • Case Studies
  • 4. Visualizing Data in the Tidyverse
    • About This Course
    • Data Visualization Background
    • Plot Types
    • Making Good Plots
    • Plot Generation Process
    • ggplot2: Basics
    • ggplot2: Customization
    • Tables
    • ggplot2: Extensions
    • Case Studies
  • 5. Modeling Data in the Tidyverse
    • About This Course
    • The Purpose of Data Science
    • Types of Data Science Questions
    • Data Needs
    • Descriptive and Exploratory Analysis
    • Inference
    • Linear Modeling
    • Multiple Linear Regression
    • Beyond Linear Regression
    • More Statistical Tests
    • Hypothesis Testing
    • Prediction Modeling
    • The tidymodels Ecosystem
    • Case Studies
    • Summary of tidymodels
  • About the Authors

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