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210123 ||| eng |
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|a 9781491910337
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|a 1491910364
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|a 1491910348
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|a 9781491910368
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|a 1491910399
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|a QA76
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|a Wickham, Hadley
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|a R for data science
|b import, tidy, transform, visualize, and model data
|c Hadley Wickham & Garrett Grolemund
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|a First edition
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|a Sebastopol, CA
|b O'Reilly Media
|c 2016
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| 300 |
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|a 1 online resource
|b illustrations (some color)
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|a Includes bibliographical references and index
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|a 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 Safari; 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
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|a 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; Typical Values; Unusual Values; Exercises; Missing Values; Exercises; Covariation
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|a Parsing a VectorNumbers; Strings; Factors; Dates, Date-Times, and Times; Exercises; Parsing a File; Strategy; Problems; Other Strategies; Writing to a File; Other Types of Data; Chapter 9. Tidy Data with tidyr; Introduction; Prerequisites; Tidy Data; Exercises; Spreading and Gathering; Gathering; Spreading; Exercises; Separating and Pull; Separate; Unite; Exercises; Missing Values; Exercises; Case Study; Exercises; Nontidy Data; Chapter 10. Relational Data with dplyr; Introduction; Prerequisites; nycflights13; Exercises; Keys; Exercises; Mutating Joins; Understanding Joins; Inner Join
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|a Aesthetic MappingsExercises; 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
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|a A Categorical and Continuous VariableExercises; Two Categorical Variables; Exercises; Two Continuous Variables; Exercises; Patterns and Models; ggplot2 Calls; Learning More; Chapter 6. Workflow: Projects; What Is Real?; Where Does Your Analysis Live?; Paths and Directories; RStudio Projects; Summary; Part II. Wrangle; Chapter 7. Tibbles with tibble; Introduction; Prerequisites; Creating Tibbles; Tibbles Versus data.frame; Printing; Subsetting; Interacting with Older Code; Exercises; Chapter 8. Data Import with readr; Introduction; Prerequisites; Getting Started; Compared to Base R; Exercises
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|a Electronic data processing / fast
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|a Data mining / fast
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|a Data Mining
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|a Big data / fast
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|a COMPUTERS / Computer Science / bisacsh
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|a Big data / http://id.loc.gov/authorities/subjects/sh2012003227
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|a COMPUTERS / Data Processing / bisacsh
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|a Données volumineuses
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|a R / Programm / gnd / http://d-nb.info/gnd/4705956-4
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|a Databases / fast
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|a Data mining / http://id.loc.gov/authorities/subjects/sh97002073
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|a COMPUTERS / Machine Theory / bisacsh
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|a Databases / http://id.loc.gov/authorities/subjects/sh86007767
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|a R (Computer program language) / http://id.loc.gov/authorities/subjects/sh2002004407
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|a R (Langage de programmation)
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|a COMPUTERS / Hardware / General / bisacsh
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|a COMPUTERS / Reference / bisacsh
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|a R (Computer program language) / fast
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|a COMPUTERS / Computer Literacy / bisacsh
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|a Electronic data processing / http://id.loc.gov/authorities/subjects/sh85042288
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|a Exploration de données (Informatique)
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|a COMPUTERS / Information Technology / bisacsh
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| 700 |
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|a Grolemund, Garrett
|e author
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|a eng
|2 ISO 639-2
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|b OREILLY
|a O'Reilly
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| 776 |
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|z 1491910364
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| 776 |
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|z 9781491910399
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| 776 |
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|z 1491910348
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| 776 |
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|z 149191033X
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| 776 |
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|z 9781491910368
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| 776 |
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|z 9781491910344
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| 776 |
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|z 9781491910337
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| 856 |
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|u https://learning.oreilly.com/library/view/~/9781491910382/?ar
|x Verlag
|3 Volltext
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|a 004
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|a 500
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|a "This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience"--
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