R for Data Science: Visualize, Model, Transform, Tidy, and Import Data

简介:
本书将教您如何使用R进行数据科学: 您将学习如何将数据转换为R,将其转换为最有用的结构,对其进行转换,可视化和建模。什么是数据科学?通过本书,您将清楚地了解这一学科,以发现数据结构中的自然规律。在此过程中,您将学习如何使用通用的R编程语言进行数据分析。
每当你测量同一事物两次时,你会得到两个结果 -- 只要你测量得足够精确。这种现象带来了不确定性和机会。RStudio的主教练Garrett Grolemund向您展示了数据科学如何帮助您应对不确定性并抓住机遇。您将了解:
数据争论-如何操纵数据集以揭示新信息数据可视化-如何创建图形和其他可视化探索性数据分析-如何在测量中找到关系的证据建模-如何从数据中获得见解和预测推理-如何避免被无法提供万无一失的结果的数据分析所愚弄
通过本书的课程,您还将了解统计世界观,这是一种看待世界的方式,可以在面对不确定性时理解世界,并在面对复杂性时保持简单性。
英文简介:
This book will teach you how to do data science with R: You'll learn how to get your data into R, get it into the most useful structure, transform it, visualize it and model it.
What exactly is data science? With this book, you'll gain a clear understanding of this discipline for discovering natural laws in the structure of data. Along the way, you’ll learn how to use the versatile R programming language for data analysis.
Whenever you measure the same thing twice, you get two results—as 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. You'll learn about:
Data Wrangling - how to manipulate datasets to reveal new informationData Visualization - how to create graphs and other visualizationsExploratory Data Analysis - how to find evidence of relationships in your measurementsModelling - how to derive insights and predictions from your dataInference - how to avoid being fooled by data analyses that cannot provide foolproof results
Through the course of the book, you'll 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.
- 书名
- R for Data Science: Visualize, Model, Transform, Tidy, and Import Data
- 译名
- 数据科学:可视化、建模、转换、整理和导入数据
- 语言
- 英语
- 年份
- 2017
- 页数
- 520页
- 大小
- 33.00 MB
- 标签
- 数据科学
- 下载
R for Data Science: Visualize, Model, Transform, Tidy, and Import Data.pdf
- 密码
- 65536
最后更新:2025-04-12 23:58:04