R for Data Science: Import, Tidy, Transform, Visualize, and Model Data
Kurzinformation
inkl. MwSt. Versandinformationen
Artikel zZt. nicht lieferbar
Artikel zZt. nicht lieferbar
Beschreibung
"R for Data Science: Import, Tidy, Transform, Visualize, and Model Data" von Garrett Grolemund ist ein umfassendes Handbuch für angehende und erfahrene Datenwissenschaftler zur effektiven Nutzung der R-Programmiersprache für Datenanalyse. Das Buch führt die Leser durch die Schlüsselkonzepte und Fähigkeiten, die benötigt werden, um aus Rohdaten aussagekräftige Erkenntnisse zu gewinnen. Es beginnt mit der Erläuterung der Grundlagen des Imports und Aufräumens von Daten in R und geht dann auf fortgeschrittene Themen wie Datentransformation, Visualisierung und Modellierung ein. Mit vielen praktischen Beispielen zeigt das Buch den gesamten Prozess der Datenanalyse - vom Laden und Reinigen von Daten bis hin zur Implementierung von Modellen und Kommunikationsergebnissen.
Produktdetails
So garantieren wir Dir zu jeder Zeit Premiumqualität.
Über den Autor
Hadley Wickham is an Assistant Professor and the Dobelman FamilyJunior Chair in Statistics at Rice University. He is an active memberof the R community, has written and contributed to over 30 R packages, and won the John Chambers Award for Statistical Computing for his work developing tools for data reshaping and visualization. His research focuses on how to make data analysis better, faster and easier, with a particular emphasis on the use of visualization to better understand data and models.Garrett Grolemund is a statistician, teacher and R developer who currently works for RStudio. He sees data analysis as a largely untapped fountain of value for both industry and science. Garrett received his Ph.D at Rice University in Hadley Wickham's lab, where his research traced the origins of data analysis as a cognitive process and identified how attentional and epistemological concerns guide every data analysis.Garrett is passionate about helping people avoid the frustration and unnecessary learning he went through while mastering data analysis. Even before he finished his dissertation, he started teaching corporate training in R and data analysis for Revolutions Analytics. He's taught at Google, eBay, Axciom and many other companies, and is currently developing a training curriculum for RStudio that will make useful know-how even more accessible. Outside of teaching, Garrett spends time doing clinical trials research, legal research, and financial analysis. He also develops R software, he's co-authored the lubridate R package--which provides methods to parse, manipulate, and do arithmetic with date-times--and wrote the ggsubplot package, which extends the ggplot2 package.