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  • 1
    Online Resource
    Online Resource
    R für Data Science : Daten importieren, bereinigen, umformen, modellieren und visualisieren (2018)
    Heidelberg : O'Reilly
    Details
    ISBN: 9783960101536 , 3960101538
    Language: German
    Pages: 1 online resource (1 volume) , illustrations
    Edition: 1. Auflage.
    Keywords: Data mining ; Computer programs ; Information visualization ; Computer programs ; R (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Lernen Sie, wie Sie mit R Ihre Rohdaten in Erkenntnisse und Wissen umwandeln. Dieses Buch führt Sie ein in R, RStudio und tidyverse - eine Sammlung von R-Paketen, die ineinandergreifen, um Data Science schnell, flüssig und komfortabel zu machen. R für Data Science ist geeignet für Leser ohne vorherige Programmierkenntnisse und zielt darauf ab, dass Sie Techniken der Data Science so schnell wie möglich in der Praxis umsetzen können.Die Autoren Hadley Wickham und Garrett Grolemund zeigen, wie Sie Daten importieren, aufbereiten, untersuchen und modellieren und wie Sie die Ergebnisse kommunizieren können. So bekommen Sie einen vollständigen Überblick über den Data-Science-Zyklus und die Tools, die für die Detailarbeit erforderlich sind.
    Note: Includes index. - Description based on online resource; title from title page (viewed January 12, 2018)
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 2
    Online Resource
    Online Resource
    Reproducible research and reports with R Markdown : how to streamline your reporting workflow in R (2016)
    [Place of publication not identified] : O'Reilly
    Details
    Language: English
    Pages: 1 online resource (1 streaming video file (2 hr., 9 min., 28 sec.)) , digital, sound, color
    Keywords: R (Computer program language) ; Electronic videos ; local
    Abstract: "R Markdown does three main things pretty close to magic. First, it lets you make a completely reproducible, parameter-set and automatable R report. Second, it lets you export that report into a multitude of formats (HTML, Word, .js slide show, interactive web app, etc.). Third, it does the first two things really fast. Wishing for a way to document your code so it still makes sense to you or somebody else six months down the road? Presto! R Markdown does that. Hoping for a button you could click to reproduce your entire analysis with a new data set or parameter? Shazaam! R Markdown does that. Sick of having to copy and paste your results? Poof! R Markdown takes the pain away. If you're an analyst, scientist, actuary, statistician, or a programmer familiar with R, you should add this package to your bag of tricks."--Resource description page.
    Note: Title from title screen (viewed May 18, 2016)
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 3
    Online Resource
    Online Resource
    Introduction to Shiny : learn how to build interactive web apps with R, Shiny, and reactive programming (2016)
    [Place of publication not identified] : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 streaming video file (3 hr., 13 min., 36 sec.)) , digital, sound, color
    Keywords: R (Computer program language) ; Information visualization ; Application software ; Electronic videos ; local
    Abstract: "Data scientists who work with R look to Shiny as the web framework of choice for moving analytical power into the hands of their bosses, clients, and the public at large. The reason? Shiny apps let the non-coders of the world control the visualization of complex data sets so they can explore, analyze and model on their own. Taught by RStudio master instructor Garrett Grolemund, this video details how Shiny combines the computational power of R and the interactivity of the web to produce highly interactive reports and visualizations. Part one offers a detailed description of Shiny and how to use it build an app. Part two covers reactive programming and why it differs from functional programming, the paradigm that guides most of R. Part three outlines the Shiny UI and the toolsets it offers to customize the appearance of a Shiny app. This video is optimized for the intermediate level R coder."--Resource description page.
    Note: Title from title screen (viewed May 5, 2016)
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 4
    Online Resource
    Online Resource
    R for data science : import, tidy, transform, visualize, and model data (2016)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: First edition.
    Keywords: R (Computer program language) ; Data mining ; Information visualization ; Electronic books ; Electronic books ; local
    Abstract: Learn how to use R to turn raw data into insight, knowledge, and understanding. 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, R for Data Science is designed to get you doing data science as quickly as possible.
    Note: Includes index. - Description based on online resource; title from title page (Safari, viewed January 10, 2017)
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 5
    Online Resource
    Online Resource
    R for data science : import, tidy, transform, visualize, and model data (2023)
    Sebastopol, CA : O'Reilly Media, Inc.
    Details
    Language: English
    Pages: 1 online resource (576 pages) , illustrations
    Edition: 2nd edition.
    DDC: 006.3/12
    Keywords: Data mining Computer programs ; Information visualization Computer programs ; R (Computer program language) ; Big data ; Databases
    Abstract: Use R to turn data into insight, knowledge, and understanding. With this practical book, aspiring data scientists will learn how to do data science with R and RStudio, along with the tidyverse—a collection of R packages designed to work together to make data science fast, fluent, and fun. Even if you have no programming experience, this updated edition will have you doing data science quickly. You'll learn how to import, transform, and visualize your data and communicate the results. And you'll get a complete, big-picture understanding of the data science cycle and the basic tools you need to manage the details. Updated for the latest tidyverse features and best practices, new chapters show you how to get data from spreadsheets, databases, and websites. Exercises help you practice what you've learned along the way.
    Note: Includes bibliographical references and index
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 6
    Online Resource
    Online Resource
    Easy, reproducible report with R (2015)
    [Place of publication not identified] : O'Reilly Media
    Details
    ISBN: 9781491954867
    Language: English
    Pages: 1 online resource (1 streaming video file (43 min., 36 sec.)) , digital, sound, color
    Keywords: R (Computer program language) ; Electronic videos ; local
    Abstract: "The R Markdown package makes it very easy to generate reports straight from your R code. With R Markdown, you combine code and text into a single .Rmd file. You use this document to generate polished reports automatically in a variety of formats (html, pdf, MS Word, and slideshows). The .Rmd file retains all of your code for reproducibility, but lets you set how the code and its results will appear in the final report. Best of all, R Markdown reports are parameterizable. This webcast will cover applying the same report to multiple data sets."--Resource description page.
    Note: Title from title screen (viewed January 28, 2016)
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 7
    Online Resource
    Online Resource
    Introduction to data science with R : manipulating, visualizing, and modeling data with the R language (2014)
    [Place of publication not identified] : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 streaming video file (8 hr., 36 min., 39 sec.)) , digital, sound, color.
    Keywords: R (Computer program language) ; Information visualization ; Statistical decision ; Electronic videos ; local
    Abstract: "Learn practical skills for visualizing, transforming, and modeling data in R. This comprehensive video course shows you how to explore and understand data, as well as how to build linear and non-linear models in the R language and environment. It's ideal whether you're a non-programmer with no data science experience, or a data scientist switching to R from other software such as SAS or Excel."--Resource description page.
    Note: Title from title screen (viewed December 11, 2014)
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 8
    Online Resource
    Online Resource
    Expert data wrangling with R : streamline your work with tidyr, dplyr, and ggvis (2015)
    [Place of publication not identified] : O'Reilly Media
    Details
    ISBN: 9781491917046
    Language: English
    Pages: 1 online resource (1 streaming video file (3 hr., 50 min., 49 sec.)) , digital, sound, color.
    Keywords: R (Computer program language) ; Big data ; Data mining ; Electronic videos ; local
    Abstract: "Analysts often spend 50-80% of their time preparing and transforming data sets before they begin more formal analysis work. This video tutorial shows you how to streamline your code-and your thinking-by introducing a set of principles and R packages that make this work much faster and easier. Garrett Grolemund, Data Scientist and Master Instructor at RStudio, demonstrates how R and its packages help you tackle three main issues. Data Manipulation. Data sets contain more information than they display. By transforming your data, you can reveal a wealth of descriptive statistics, group level observations, and hidden variables. R's dplyr package provides optimized functions to help you transform data, as well as a pipe syntax that makes R code more concise and intuitive. Data Tidying. Data sets come in many formats, but R prefers just one. R runs quickly and intuitively when your data is stored in the tidy format, a layout that allows vectorized programming. R's tidyr package reshapes the layout of your data sets, making them tidy while preserving the relationships they contain. Data Visualization. The structure of data visualizations parallels the structure of data sets. Once your data is tidy, visualizations become straightforward: each observation in your dataset becomes a mark on a graph, each variable becomes a visual property of the marks. The result is a grammar of graphics that lets you create thousands of graphs. R's ggvis package implements the grammar, providing a system of data visualization for R."--Resource description page.
    Note: Title from resource description page (viewed March 27, 2015)
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 9
    Online Resource
    Online Resource
    Język R (2017)
    [Erscheinungsort nicht ermittelbar] : Helion | Boston, MA : Safari
    Details
    Language: English , Polish
    Pages: 1 online resource (432 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Analiza danych jest stosunkowo młodą, interdyscyplinarną dziedziną, której celem jest wydobycie i wykorzystanie wiedzy ukrytej w surowych danych pozyskanych z różnych źródeł. Można w ten sposób zrozumieć istotę zjawisk, przewidzieć wystąpienie zdarzeń czy pozyskać informacje niedostępne w inny sposób. W wielu przypadkach wnioski wyciągnięte z analizy danych okazują się bezcenne, co doceniają profesjonaliści z licznych branż. Przygotowanie danych, przeanalizowanie ich i odpowiednie przedstawienie płynącej z nich wiedzy bywa sporym wyzwaniem, jednak dzięki takim narzędziom jak język R i związane z nim pakiety zadanie to staje się znacząco prostsze. Niniejsza książka jest przystępnie napisanym przewodnikiem po języku R i narzędziach służących do analizy danych. Zawarto tu wyczerpujące wprowadzenie do języka R, programu RStudio i tidyverse. Zaprezentowano zestaw pakietów R, które znacznie poprawiają komfort pracy podczas analizy danych. Wyjaśniono znaczenie poszczególnych etapów analizy danych: ich importowania, oczyszczania, przekształcania, modelowania, wizualizowania, a także skutecznego komunikowania wiedzy płynącej z danych. Mimo że książka dotyczy narzędzi programistycznych, skorzystają z niej nie tylko programiści. Doceni ją każdy, kto chce zyskać solidne podstawy przygotowania i analizy danych. Najważniejsze zagadnienia: przekształcanie zbiorów danych techniki analizy danych w języku R eksplorowanie danych, formułowanie i testowanie hipotez integracja opisów, kodu i wyników badań w języku R Markdown graficzna prezentacja danych z wykorzystaniem ggplot2 R - wszystko, czego potrzebujesz w profesjonalnej analizie danych! Hadley Wickham pracuje w RStudio. Jest również członkiem fundacji R Foundation. Tworzy ciekawe narzędzia do analizy danych. Jest również naukowcem, autorem książek i wykładowcą. Angażuje się w promowanie języka R jako narzędzia do analizy danych. Garrett Grolemund jest statystykiem, nauczycielem i programistą R. Napisał powszechnie znany pakiet lubridate. Grolemund jest popularnym instruktorem języka R i analizy danych - w tym zakresie pomagał takim firmom, jak Google, eBay, Roche i inne.
    Note: Online resource; Title from title page (viewed December 1, 2017) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
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    Online Resource
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  • 10
    Online Resource
    Online Resource
    R para Data Science (2018)
    [Erscheinungsort nicht ermittelbar] : Alta Books | Boston, MA : Safari
    Details
    Language: English , Portuguese
    Pages: 1 online resource (528 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Aprenda a usar R para transformar dados brutos em in­sight, conhecimento e compreensão. Este livro apresenta você ao R, RStudio e ao tidyverse, uma coleção de pacotes R elaborados para trabalhar juntos com o objetivo de dei­xar a ciência de dados rápida, fluente e divertida. Adequa­do para leitores sem experiência prévia em programação, R para Data Science foi projetado para que você comece a fazer ciência de dados o mais rápido possível. Os autores Hadley Wickham e Garret Grolemund te guiam através dos passos de importar, fazer data wrangle, explorar e modelar seus dados e comunicar os resultados. Você obterá uma compreensão completa do quadro geral do ciclo de ciência de dados, junto das ferramentas bási­cas que você precisa para administrar os detalhes.
    Note: Online resource; Title from title page (viewed March 30, 2018) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
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