ggplot2: Elegant Graphics for Data Analysis (Use R!)
| Autor | Hadley Wickham |
| 8850481900 | |
| Idioma | Germany - English |
| Terminal correspondiente | Android|iPhone|iPad|PC |
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Create Elegant Data Visualisations Using the Grammar of Graphics A system for 'declaratively' creating graphics, based on "The Grammar of Graphics". You provide the data, tell 'ggplot2' how to map variables to aesthetics, what graphical primitives to use, and it takes care of the details.
About Quick-R. R is an elegant and comprehensive statistical and graphical programming language. Unfortunately, it can also have a steep learning curve.I created this website for both current R users, and experienced users of other statistical packages (, SAS, SPSS, Stata) who would like to transition to R.
Some basic knowledge of R is necessary (, 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.
He is the author of the R packages survminer (for analyzing and drawing survival curves), ggcorrplot (for drawing correlation matrix using ggplot2) and factoextra (to easily extract and visualize the results of multivariate analysis such PCA, CA, MCA and clustering).
You will need some basic knowledge of R ( you should be able to get your data into R), but ggplot2 is a mini-language specifically tailored for producing graphics, and you'll learn everything you need in the book.
Medway, R. L., & Fulton, J. (2012). When more gets you less: a meta-analysis of the effect of concurrent web options on mail survey response rates. Public Opinion Quarterly, 76(4), 733–746. CrossRef Google Scholar
Auch die "Layered Grammar of Graphics" (Wickham 2010) und das R-Package ggplot2 basieren darauf. Die theoretischen und mathematischen Grundlagen sind bei der praktischen Arbeit mit den ggplot2-Funktionen immer im Hintergrund dabei, es reicht aber ein strak vereinfachtes, prinzipielles Verständnis, um sie erfolgreich anwenden zu können.
Zusammenfassung. R ist eine freie und kostenlose Umgebung zur computergestützten statistischen Datenverarbeitung (Ihaka & Gentleman, 1996; R Core Team, 2014): R integriert eine Vielzahl von Möglichkeiten, um Daten organisieren, transformieren, auswerten und visualisieren zu kö bezeichnet R sowohl das Programm selbst als auch die Sprache, in der die Auswertungsbefehle geschrieben ...
Zusammenfassung. Dieses Kapitel stellt eine Anwendung von Topic-Modell-Verfahren auf semantische Indikatoren im Rahmen einer quantitativen Umfrage vor, die in Bezug auf Akteure der Nanomedizin in Europa erhoben wurde.
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