Data Wrangling with R: Load, explore, transform and visualize data for modeling with tidyverse libraries

Take your data wrangling skills to the next level by gaining a deep understanding of tidyverse libraries and effectively prepare your data for impressive analysis

Key Features

- Explore state-of-the-art libraries for data wrangling in R and learn to prepare your data for analysis
- Find out how to work with different data types such as strings, numbers, date, and time
- Build your first model and visualize data with ease through advanced plot types and with ggplot2

Book Description

In this information era, where large volumes of data are being generated every day, companies want to get a better grip on it to perform more efficiently than before. This is where skillful data analysts and data scientists come into play, wrangling and exploring data to generate valuable business insights. In order to do that, you'll need plenty of tools that enable you to extract the most useful knowledge from data.

Data Wrangling with R will help you to gain a deep understanding of ways to wrangle and prepare datasets for exploration, analysis, and modeling. This data book enables you to get your data ready for more optimized analyses, develop your first data model, and perform effective data visualization.

The book begins by teaching you how to load and explore datasets. Then, you'll get to grips with the modern concepts and tools of data wrangling. As data wrangling and visualization are intrinsically connected, you'll go over best practices to plot data and extract insights from it. The chapters are designed in a way to help you learn all about modeling, as you will go through the construction of a data science project from end to end, and become familiar with the built-in RStudio, including an application built with Shiny dashboards.

By the end of this book, you'll have learned how to create your first data model and build an application with Shiny in R.

What you will learn

- Discover how to load datasets and explore data in R
- Work with different types of variables in datasets
- Create basic and advanced visualizations
- Find out how to build your first data model
- Create graphics using ggplot2 in a step-by-step way in Microsoft Power BI
- Get familiarized with building an application in R with Shiny

Who this book is for

If you are a professional data analyst, data scientist, or beginner who wants to learn more about data wrangling, this book is for you. Familiarity with the basic concepts of R programming or any other object-oriented programming language will help you to grasp the concepts taught in this book. Data analysts looking to improve their data manipulation and visualization skills will also benefit immensely from this book.

提升您的資料整理技能，深入了解tidyverse函式庫，有效地準備資料以進行令人印象深刻的分析。

主要特點：
- 探索R語言中用於資料整理的最新函式庫，並學習如何準備資料進行分析。
- 了解如何處理不同類型的資料，例如字串、數字、日期和時間。
- 透過高級繪圖類型和ggplot2輕鬆建立模型並視覺化資料。

書籍描述：
在這個資訊時代，每天都有大量的資料產生，公司希望能更好地掌握資料，以比以前更高效地運作。這就是熟練的資料分析師和資料科學家發揮作用的地方，他們整理和探索資料以生成有價值的業務洞察。為了做到這一點，您需要許多工具，使您能夠從資料中提取最有用的知識。

《使用R進行資料整理》將幫助您深入了解整理和準備資料集以進行探索、分析和建模的方法。這本資料書籍使您能夠準備好進行更優化的分析，開發您的第一個資料模型並進行有效的資料視覺化。

本書首先教您如何載入和探索資料集。然後，您將熟悉資料整理的現代概念和工具。由於資料整理和視覺化密切相關，您將學習最佳實踐來繪製資料並從中提取洞察。各章節的設計方式旨在幫助您全面了解建模，您將從頭到尾完成一個資料科學專案的構建，並熟悉內置的RStudio，包括使用Shiny儀表板構建的應用程式。

通過閱讀本書，您將學會如何創建您的第一個資料模型並在R中使用Shiny構建應用程式。

您將學到什麼：
- 發現如何在R中載入資料集並探索資料。
- 處理資料集中不同類型的變數。
- 創建基本和高級視覺化。
- 了解如何建立您的第一個資料模型。
- 在Microsoft Power BI中逐步使用ggplot2創建圖形。
- 熟悉使用Shiny在R中構建應用程式。

本書適合對象：
如果您是專業的資料分析師、資料科學家或初學者，並且想更多地了解資料整理，這本書適合您。熟悉R編程或其他面向對象的編程語言的基本概念將有助於您理解本書所教授的概念。希望提升資料操作和視覺化技能的資料分析師也將從本書中受益匪淺。

1. Fundamentals of Data Wrangling
2. Load & Explore Datasets
3. Basic Data Visualization
4. Working with Strings
5. Working with Numbers
6. Working with Date and Time objects
7. Transformations with Base R
8. Transformations with tidyverse libraries
9. Exploratory Data Analysis
10. Introduction to ggplot2
11. Enhanced Visualizations with ggplot2
12. Other Data Visualization Options
13. Build Your First Model
14. Build an Application with Shiny in R

1. 資料整理基礎
2. 載入與探索資料集
3. 基本資料視覺化
4. 處理字串
5. 處理數字
6. 處理日期和時間物件
7. 使用基本 R 進行轉換
8. 使用 tidyverse 函式庫進行轉換
9. 探索性資料分析
10. ggplot2 入門
11. 使用 ggplot2 進行進階視覺化
12. 其他資料視覺化選項
13. 建立第一個模型
14. 在 R 中使用 Shiny 建立應用程式