|aR for data science :|bimport, tidy, transform, visualize, and model data /|cHadley Wickham & Garrett Grolemund.
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|aBeijing :|bO'Reilly,|cc2017.
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|aBeijing :|bO'Reilly,|c[2017]
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|axxv, 492 pages :|billustrations (some color) ;|c23 cm
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|atext|2rdacontent
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|aunmediated|2rdamedia
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|avolume|2rdacarrier
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|aIncludes index.
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|aPart I. Explore. Data visualization with ggplot2 -- Workflow: basics -- Data transformation with dplyr -- Workflow: scripts -- Exploratory data analysis -- Workflow: projects -- Part II. Wrangle. Tibbles with tibble -- Data import with readr --Tidy data with tidyr -- Relational data with dplyr -- Strings with stringr -- Factors with forcats -- Dates and times with lubridate -- Part III. Program. Pipes with magrittr -- Functions -- Vectors -- Iteration with purrr -- Part IV. Model. Model basics with modelr -- Model building -- Many models with purrr and broom -- Part V. Communicate. R Markdown -- Graphics for communication with ggplot2 -- R Markdown formats -- R Markdown workflow.
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|a"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"--Page 4 of cover.
內容簡介top R for Data Science 簡介 What exactly is data science? With this book, youl gain a clear understanding of this discipline for discovering natural laws in the structure of data. Along the way, youl learn how to use the versatile R programming language for data analysis.Whenever you measure the same thing twice, you get two resultss long as you measure precisely enough. This phenomenon creates uncertainty and opportunity. Author Garrett Grolemund, Master Instructor at RStudio, shows you how data science can help you work with the uncertainty and capture the opportunities. Youl learn about:Data Wranglingow to manipulate datasets to reveal new informationData Visualizationow to create graphs and other visualizationsExploratory Data Analysisow to find evidence of relationships in your measurementsModellingow to derive insights and predictions from your dataInferenceow to avoid being fooled by data analyses that cannot provide foolproof resultsThrough the course of the book, youl also learn about the statistical worldview, a way of seeing the world that permits understanding in the face of uncertainty, and simplicity in the face of complexity.