Introduction to R Data Analysis for Everyone
 |
Description
Book Introduction
An easy-to-learn introduction to R data analysis!
《Introduction to R Data Analysis for Everyone (2nd Edition)》 is a book for beginners who are starting data analysis with R.
You can learn the basic grammar of R and data analysis using R simultaneously by practicing various examples based on solid theoretical explanations.
In particular, this second edition adds "Practical Analysis" elements and "Data Analysis Case Projects" to help you understand how data analysis is actually implemented in the field.
By following the contents of this book, you will naturally acquire the ability to handle data.
※ This book was developed as a textbook for university lectures, so it does not provide answers to practice problems.
《Introduction to R Data Analysis for Everyone (2nd Edition)》 is a book for beginners who are starting data analysis with R.
You can learn the basic grammar of R and data analysis using R simultaneously by practicing various examples based on solid theoretical explanations.
In particular, this second edition adds "Practical Analysis" elements and "Data Analysis Case Projects" to help you understand how data analysis is actually implemented in the field.
By following the contents of this book, you will naturally acquire the ability to handle data.
※ This book was developed as a textbook for university lectures, so it does not provide answers to practice problems.
- You can preview some of the book's contents.
Preview
index
CHAPTER 01 Data Analysis and R
01 The Age of Data
02 Big Data
03 Data Analysis Process
04 Installation and Use of R and R Studio
summation
Practice problems
CHAPTER 02 Variables and Vectors
01 Basic operations of R
02 Variables
03 Understanding Vectors
04 Vector Operations
05 Lists and Factors
summation
Practice problems
CHAPTER 03 Matrices and Data Frames
01 Matrix
02 Data Frame
03 Handling Matrices and Data Frames
04 Reading/Writing File Data
summation
Practice problems
CHAPTER 04 Conditional statements, loops, and functions
01 Conditional statement
02 Loop
03 apply() function
04 User-defined functions
05 Finding the location of data that meets the conditions
summation
Practice problems
CHAPTER 05 Exploring Single-Variable Data
01 Type of data
02 Exploring single-variable categorical data
03 Exploring single-variable continuous data
Practical analysis
summation
Practice problems
CHAPTER 06 Exploring Multivariate Data
01 Scatter plot
02 Correlation Analysis
03 Line Graph
04 Data Exploration Practice
Practical analysis
summation
Practice problems
CHAPTER 07 Data Preprocessing
01 Missing values
02 Singular values
03 Data Sorting
04 Data separation and selection
05 Data Sampling and Combination
06 Data Aggregation and Merging
Practical analysis
summation
Practice problems
CHAPTER 08 Data Visualization
01 Data Visualization Techniques
02 ggplot package
3-dimensional reduction
Practical analysis
summation
Practice problems
CHAPTER 09 Maps and Data
01 Preparing to use Google Maps
02 View a map of a specific area
03 Displaying markers and text on the map
04 Displaying data on the map
Practical analysis
summation
Practice problems
CHAPTER 10: Word Cloud and Purchasing Pattern Analysis
01 Word Cloud Analysis
02 Purchase Pattern Analysis
03 Internet search term analysis
04 Public Big Data
Practical analysis
summation
Practice problems
CHAPTER 11 REGRESSION ANALYSIS
01 Simple linear regression analysis
02 Multiple linear regression analysis
03 Logistic Regression Analysis
Practical analysis
summation
Practice problems
CHAPTER 12 Clustering and Classification
01 Overview of Clustering and Classification
02 k-means clustering
03 k-nearest neighbor classification
04 k-fold cross-validation
Practical analysis
summation
Practice problems
CHAPTER 13 Data Analysis Case I
01 Prepare data for analysis
02 Data Exploration
03 Period-by-period analysis
04.
Analysis of the commercial district in Yeoksam 1-dong
summation
Practice problems
CHAPTER 14 Data Analysis Case II
01 Dataset Description
02 Data Exploration
03 Comparison before and after COVID-19
summation
Practice problems
CHAPTER 15 Data Analysis Case III
01 Dataset Description
02 Data Exploration
03 Analysis of Housing Price Formation Factors
04 Development of a housing price prediction model
summation
Practice problems
supplement.
Google Maps API key and KoNLP package
01 The Age of Data
02 Big Data
03 Data Analysis Process
04 Installation and Use of R and R Studio
summation
Practice problems
CHAPTER 02 Variables and Vectors
01 Basic operations of R
02 Variables
03 Understanding Vectors
04 Vector Operations
05 Lists and Factors
summation
Practice problems
CHAPTER 03 Matrices and Data Frames
01 Matrix
02 Data Frame
03 Handling Matrices and Data Frames
04 Reading/Writing File Data
summation
Practice problems
CHAPTER 04 Conditional statements, loops, and functions
01 Conditional statement
02 Loop
03 apply() function
04 User-defined functions
05 Finding the location of data that meets the conditions
summation
Practice problems
CHAPTER 05 Exploring Single-Variable Data
01 Type of data
02 Exploring single-variable categorical data
03 Exploring single-variable continuous data
Practical analysis
summation
Practice problems
CHAPTER 06 Exploring Multivariate Data
01 Scatter plot
02 Correlation Analysis
03 Line Graph
04 Data Exploration Practice
Practical analysis
summation
Practice problems
CHAPTER 07 Data Preprocessing
01 Missing values
02 Singular values
03 Data Sorting
04 Data separation and selection
05 Data Sampling and Combination
06 Data Aggregation and Merging
Practical analysis
summation
Practice problems
CHAPTER 08 Data Visualization
01 Data Visualization Techniques
02 ggplot package
3-dimensional reduction
Practical analysis
summation
Practice problems
CHAPTER 09 Maps and Data
01 Preparing to use Google Maps
02 View a map of a specific area
03 Displaying markers and text on the map
04 Displaying data on the map
Practical analysis
summation
Practice problems
CHAPTER 10: Word Cloud and Purchasing Pattern Analysis
01 Word Cloud Analysis
02 Purchase Pattern Analysis
03 Internet search term analysis
04 Public Big Data
Practical analysis
summation
Practice problems
CHAPTER 11 REGRESSION ANALYSIS
01 Simple linear regression analysis
02 Multiple linear regression analysis
03 Logistic Regression Analysis
Practical analysis
summation
Practice problems
CHAPTER 12 Clustering and Classification
01 Overview of Clustering and Classification
02 k-means clustering
03 k-nearest neighbor classification
04 k-fold cross-validation
Practical analysis
summation
Practice problems
CHAPTER 13 Data Analysis Case I
01 Prepare data for analysis
02 Data Exploration
03 Period-by-period analysis
04.
Analysis of the commercial district in Yeoksam 1-dong
summation
Practice problems
CHAPTER 14 Data Analysis Case II
01 Dataset Description
02 Data Exploration
03 Comparison before and after COVID-19
summation
Practice problems
CHAPTER 15 Data Analysis Case III
01 Dataset Description
02 Data Exploration
03 Analysis of Housing Price Formation Factors
04 Development of a housing price prediction model
summation
Practice problems
supplement.
Google Maps API key and KoNLP package
Detailed image
.jpg)
GOODS SPECIFICS
- Date of issue: May 5, 2023
- Page count, weight, size: 584 pages | 188*235*35mm
- ISBN13: 9791156646532
- ISBN10: 1156646537
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