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Use R! ggplot2: Elegant Graphics for Data Analysis, (Paperback)
CZK 1338
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This book will be useful to everyone who has struggled with displaying data in an informative and attractive way.
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- This new edition to the classic book by ggplot2 creator Hadley Wickham highlights compatibility with knitr and RStudio. ggplot2 is a data visualization package for R that helps users create data graphics, including those that are multi-layered, with ease. With ggplot2, it's easy to: produce handsome, publication-quality plots with automatic legends created from the plot specificationsuperimpose multiple layers (points, lines, maps, tiles, box plots) from different data sources with automatically adjusted common scalesadd customizable smoothers that use powerful modeling capabilities of R, such as loess, linear models, generalized additive models, and robust regressionsave any ggplot2 plot (or part thereof) for later modification or reusecreate custom themes that capture in-house or journal style requirements and that can easily be applied to multiple plotsapproach a graph from a visual perspective, thinking about how eachcomponent of the data is represented on the final plot This book will be useful to everyone who has struggled with displaying data in an informative and attractive way. Some basic knowledge of R is necessary (e.g., importing data into R). ggplot2 is a mini-language specifically tailored for producing graphics, and you'll learn everything you need in the book. After reading this book you'll be able to produce graphics customized precisely for your problems, and you'll find it easy to get graphics out of your head and on to the screen or page.
| Book format | Paperback |
| Fiction/nonfiction | Non-Fiction |
| Genre | Computing & Internet |
| Publication date | June, 2016 |
| Pages | 260 |
| Subgenre | Mathematical & Statistical Software |
| Series title | Use R! |
| Edition | 2nd Edition |
| Publisher | Springer International Publishing |
| Original languages | English |
| Language | English |
| Edu focus | Mathematics |
| Educational level | General |
| Is collectible | N |
| Binding type | Perfect Binding |
| Recording time | 0 min |
| Retail packaging | Single Piece |
| Assembled product dimensions (l x w x h) | 6.14 x 0.58 x 9.21 in (15.6 x 1.5 x 23.4 cm) |
| Assembled product weight | 0.87 lb (390 grams) |
| Bisac subject heading | Computers |
Who Should Buy?
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Data Analysts
This book provides comprehensive techniques for data visualization, essential for analysts seeking to interpret data effectively.
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Statisticians
Statisticians can leverage ggplot2 for creating high-quality graphical representations of statistical data.
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R Beginners
New users of R will find practical guidance in mastering ggplot2 for data visualization and analysis.
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Absolute Beginners
Complete novices to programming may struggle without prior knowledge of R or basic data analysis principles.
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Hadley Wickham All Books Editorial Review
Use R! ggplot2: Elegant Graphics for Data Analysis, (Paperback) is an insightful resource designed for those venturing into the world of data visualization using R programming. This 2nd Edition published by Springer International Publishing in June 2016, spans 260 pages and focuses on Mathematical & Statistical Software within the field of computing. The paperback format is user-friendly, making it ideal for both beginners and more experienced users looking to refine their skills in creating elegant graphics. Readers have praised its clear explanations and practical examples, asserting that this book is essential for anyone serious about mastering ggplot2 in R.
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Klady
- User-friendly paperback format for easy reading
- Offers practical examples for beginners
- Covers ggplot2 in depth for skill refinement
- Essential for serious learners of data visualization
- High-quality publication by a reputable publisher
Nevýhody
- Some readers may find the content dense at times
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CZK 1338
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Služby a výhody
- Compatibility with knitr and RStudio
- Produce publication-quality plots with automatic legends
- Superimpose multiple layers from different data sources
- Add customizable smoothers using powerful modeling capabilities of R
- Save plots for later modification or reuse
- Create custom themes for multiple plots
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