R for Data Science: Import, Tidy, Transform, Visualize, and Model Data, 2/e (Paperback)
暫譯: R 語言與資料科學:匯入、整理、轉換、視覺化與建模資料,第二版 (平裝本)
Wickham, Hadley, Çetinkaya-Rundel, Mine, Grolemund, Garrett
- 出版商: O'Reilly
- 出版日期: 2023-07-18
- 定價: $2,800
- 售價: 9.0 折 $2,520
- 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、知識和理解。這本實用的書籍將幫助有志於成為數據科學家的讀者學習如何使用 R 和 RStudio 進行數據科學,並介紹 tidyverse——一組設計為協同工作的 R 套件,旨在使數據科學變得快速、流暢且有趣。即使您沒有編程經驗,這個更新版也能讓您迅速進入數據科學的領域。
您將學習如何導入、轉換和可視化數據,並傳達結果。您還將全面了解數據科學循環及管理細節所需的基本工具。這本書針對最新的 tidyverse 功能和最佳實踐進行了更新,新增章節展示如何從電子表格、數據庫和網站獲取數據。練習題將幫助您在學習過程中實踐所學。
您將了解如何:
- **可視化:** 創建圖表以進行數據探索和結果傳達
- **轉換:** 發現變量類型及其操作工具
- **導入:** 將數據導入 R 並以便於分析的形式呈現
- **編程:** 學習 R 工具以更清晰和輕鬆地解決數據問題
- **傳達:** 使用 Quarto 整合文本、代碼和結果