eBook
Introduction to Data Science : Data Wrangling and Visualization with R
| Τίτλος: | Introduction to Data Science : Data Wrangling and Visualization with R |
|---|---|
| Περιγραφή: | Unlike the first edition, the new edition has been split into two books.Thoroughly revised and updated, this is the first book of the second edition of Introduction to Data Science: Data Wrangling and Visualization with R. It introduces skills that can help you tackle real-world data analysis challenges. These include R programming, data wrangling with dplyr, data visualization with ggplot2, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation with Quarto and knitr. The new edition includes additional material on data.table, locales, and accessing data through APIs. The book is divided into four parts: R, Data Visualization, Data Wrangling, and Productivity Tools. Each part has several chapters meant to be presented as one lecture and includes dozens of exercises. The second book will cover topics including probability, statistics and prediction algorithms with R.Throughout the book, we use motivating case studies. In each case study, we try to realistically mimic a data scientist's experience. For each of the skills covered, we start by asking specific questions and answer these through data analysis. Examples of the case studies included in the book are: US murder rates by state, self-reported student heights, trends in world health and economics, and the impact of vaccines on infectious disease rates.This book is meant to be a textbook for a first course in Data Science. No previous knowledge of R is necessary, although some experience with programming may be helpful. To be a successful data analyst implementing these skills covered in this book requires understanding advanced statistical concepts, such as those covered the second book. If you read and understand all the chapters and complete all the exercises in this book, and understand statistical concepts, you will be well-positioned to perform basic data analysis tasks and you will be prepared to learn the more advanced concepts and skills needed to become an expert. |
| Συγγραφείς: | Rafael A. Irizarry |
| Resource Type: | eBook. |
| Θέματα: | Information visualization--Computer programs, Data mining--Computer programs, R (Computer program language), Statistics--Data processing |
| Categories: | MATHEMATICS / Probability & Statistics / General |
| Βάση Δεδομένων: | eBook Index |
| FullText | Text: Availability: 0 |
|---|---|
| Header | DbId: edsebk DbLabel: eBook Index An: 3949128 RelevancyScore: 981 AccessLevel: 6 PubType: eBook PubTypeId: ebook PreciseRelevancyScore: 981.043701171875 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Introduction to Data Science : Data Wrangling and Visualization with R – Name: Abstract Label: Description Group: Ab Data: Unlike the first edition, the new edition has been split into two books.Thoroughly revised and updated, this is the first book of the second edition of Introduction to Data Science: Data Wrangling and Visualization with R. It introduces skills that can help you tackle real-world data analysis challenges. These include R programming, data wrangling with dplyr, data visualization with ggplot2, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation with Quarto and knitr. The new edition includes additional material on data.table, locales, and accessing data through APIs. The book is divided into four parts: R, Data Visualization, Data Wrangling, and Productivity Tools. Each part has several chapters meant to be presented as one lecture and includes dozens of exercises. The second book will cover topics including probability, statistics and prediction algorithms with R.Throughout the book, we use motivating case studies. In each case study, we try to realistically mimic a data scientist's experience. For each of the skills covered, we start by asking specific questions and answer these through data analysis. Examples of the case studies included in the book are: US murder rates by state, self-reported student heights, trends in world health and economics, and the impact of vaccines on infectious disease rates.This book is meant to be a textbook for a first course in Data Science. No previous knowledge of R is necessary, although some experience with programming may be helpful. To be a successful data analyst implementing these skills covered in this book requires understanding advanced statistical concepts, such as those covered the second book. If you read and understand all the chapters and complete all the exercises in this book, and understand statistical concepts, you will be well-positioned to perform basic data analysis tasks and you will be prepared to learn the more advanced concepts and skills needed to become an expert. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Rafael+A%2E+Irizarry%22">Rafael A. Irizarry</searchLink> – Name: TypePub Label: Resource Type Group: TypPub Data: eBook. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Information+visualization--Computer+programs%22">Information visualization--Computer programs</searchLink><br /><searchLink fieldCode="DE" term="%22Data+mining--Computer+programs%22">Data mining--Computer programs</searchLink><br /><searchLink fieldCode="DE" term="%22R+%28Computer+program+language%29%22">R (Computer program language)</searchLink><br /><searchLink fieldCode="DE" term="%22Statistics--Data+processing%22">Statistics--Data processing</searchLink> – Name: SubjectBISAC Label: Categories Group: Su Data: <searchLink fieldCode="ZK" term="%22MATHEMATICS+%2F+Probability+%26+Statistics+%2F+General%22">MATHEMATICS / Probability & Statistics / General</searchLink> |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=3949128 |
| RecordInfo | BibRecord: BibEntity: Classifications: – Code: 005.362 Scheme: ddc Type: prePub Languages: – Code: eng Text: English Subjects: – SubjectFull: Information visualization--Computer programs Type: general – SubjectFull: Data mining--Computer programs Type: general – SubjectFull: R (Computer program language) Type: general – SubjectFull: Statistics--Data processing Type: general Titles: – TitleFull: Introduction to Data Science : Data Wrangling and Visualization with R Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Rafael A. Irizarry – PersonEntity: Name: NameFull: Rafael A. Irizarry IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2025 – D: 09 M: 08 Type: profile Y: 2024 Identifiers: – Type: isbn-print Value: 9781032116556 – Type: isbn-electronic Value: 9781003220923 – Type: isbn-electronic Value: 9781040105504 – Type: isbn-electronic Value: 9781040105542 Titles: – TitleFull: Introduction to Data Science : Data Wrangling and Visualization with R Type: main |
| ResultId | 1 |