Download R for Data Science, by Hadley Wickham Garrett Grolemund

Download R for Data Science, by Hadley Wickham Garrett Grolemund

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R for Data Science, by Hadley Wickham Garrett Grolemund

Download R for Data Science, by Hadley Wickham Garrett Grolemund

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Über den Autor und weitere Mitwirkende

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.

Produktinformation

Taschenbuch: 494 Seiten

Verlag: O'Reilly UK Ltd. (31. Januar 2017)

Sprache: Englisch

ISBN-10: 1491910399

ISBN-13: 978-1491910399

Größe und/oder Gewicht:

15,2 x 2,7 x 22,9 cm

Durchschnittliche Kundenbewertung:

4.4 von 5 Sternen

9 Kundenrezensionen

Amazon Bestseller-Rang:

Nr. 1.952 in Fremdsprachige Bücher (Siehe Top 100 in Fremdsprachige Bücher)

Hadley Wickham zeigt einmal mehr, dass er einer der führenden R-Köpfe ist. Alle Aspekte der Datenanalyse werden angesprochen oder besser gesagt alle Schritte. Vom Einlesen, über Aufbereiten, Visualisieren, Modellieren und Berichten. Das Modellieren wird allerdings nur kurz abgehandelt. Kein Vergleich zu Klassikern wie Hastie o.ä.Sein "tidyverse"-Ansatz wird konsequent durchgezogen. Elegant und mächtig. Einfach geschrieben. Kaum Mathe - die theoretischen Hintergründe der Datenanalyse sind nicht Gegenstand des Buches.

Eines der Standardwerke, die man als R-Professional gelesen und durchgearbeitet haben sollte. Schwerpunkt ist die Arbeit als Data-Scientist mit R und dem Tidyverse-Package und den vielen darin enthaltenen Packages wie dyplr, readr, modelr, lubridate etc.Das Buch ist vom Autor auch online verfügbar gemacht worden, leider darf ich hier keinen Link posten, also googlen! Dort findet sich immer die aktuelle Version, aus der heraus die Printversion erstellt wird. Aber zum Arbeiten ist das gedruckte Werk natürlich besser zu gebrauchen.

The book is intended for a reader, that is not experienced in data science. As an experienced data scientist, that just needed to learn R syntax better, the book was unnecessarily verbose for me and sometimes it was really painful to read many pages explaining obvious. Nevertheless it was a well spend time, because:- There is usually more than one way to do given task in R. The book describes packages/commands that are generally considered to be the best/standard procedures.- The book describes best practices (coding style etc.) that are really beneficial.- The print quality is very high (nice paper, colorful graphs and even frequent code snippets are printed with colorful syntax highlighting).

A very nice book on the subject,the think i loved is that the writer makes clear that not all things can be covered on one book and also provides external resources on some of the need to know subjects.It is well writen and as a person who had no expirience on the subject (i do now!)I would suggest the book to anyone who wants to take look on R for Data Science.

I have done several online R courses before I decided to purchase this book. The book, being written by the celebrity of the R community, is really inspirational. It was a good summary for some of the courses that I did online. I am halfway through reading the book. In simple language, the author nicely guided me in learning R. Interested in learning R? I definitely recommend you buying this book.

Die klare Sprache und vor allem die klare Denkweise, die dem Buch und der vorgestellten tidyverse-Bibliothek zugrunde liegen, machen es zu einer spannenden und erfrischenden Lektüre. Selbst als langjähriger R-Nutzer habe ich vieles dazugelernt und bin nun in der Lage, sehr viel schlankeren und übersichtlicheren R-Code zu schreiben.

Several types of analyses are well explained in the book and are visualized in a nice graph.In addition more information was given than initially thought.I would definitely recommend this book.

It explains R programming in easy and simplest way for the beginners. For intermediate users it is not a best suggestion.

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