R for Data Science: Import, Tidy, Transform, Visualize, and Model Data, 2/e (Paperback)
Wickham, Hadley, Çetinkaya-Rundel, Mine, Grolemund, Garrett
- 出版商: O'Reilly
- 出版日期: 2023-07-18
- 定價: $2,780
- 售價: 9.0 折 $2,502
- 語言: 英文
- 頁數: 576
- 裝訂: Quality Paper - also called trade paper
- ISBN: 1492097403
- ISBN-13: 9781492097402
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相關分類:
R 語言、Data Science
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相關翻譯:
R 資料科學, 2/e (R for Data Science: Import, Tidy, Transform, Visualize, and Model Data, 2/e) (繁中版)
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相關主題
商品描述
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 tidyverseâ 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.
You'll understand how to:
- Visualize: Create plots for data exploration and communication of results
- Transform: Discover variable types and the tools to work with them
- Import: Get data into R and in a form convenient for analysis
- Program: Learn R tools for solving data problems with greater clarity and ease
- Communicate: Integrate prose, code, and results with Quarto
商品描述(中文翻譯)
使用 R 將數據轉化為洞察力、知識和理解。這本實用書籍將教導有志成為數據科學家的人如何使用 R 和 RStudio 進行數據科學,以及 tidyverse - 一系列 R 套件的使用,這些套件旨在協同工作,使數據科學變得快速、流暢和有趣。即使您沒有編程經驗,這本更新的版本也能讓您快速進入數據科學領域。
您將學習如何導入、轉換和可視化數據,並傳達結果。您將全面了解數據科學循環和管理細節所需的基本工具。根據最新的 tidyverse 功能和最佳實踐進行更新,新的章節將向您展示如何從電子表格、數據庫和網站獲取數據。練習將幫助您在學習過程中進行實踐。
您將了解如何:
- 可視化:創建用於數據探索和結果傳達的圖表
- 轉換:發現變量類型和處理它們的工具
- 導入:將數據導入 R 並以便於分析的形式呈現
- 編程:學習使用 R 工具更清晰、更輕鬆地解決數據問題
- 交流:使用 Quarto 整合散文、代碼和結果