This chapter covers both the practical details and the broader philosophy of (1) reading data into R and (2) doing exploratory data analysis, in particular graphical analysis. To get the most out of the chapter you should already have some basic knowledge of R’s syntax and commands (see the R supplement of the previous chapter).
This R script was used to explore patterns within the data. Comments are used to briefly describe th...
As more and more historical records are digitized, having a way to quickly analyze large volumes of ...
R (R Development Core Team, 2011) is a very powerful tool to analyze data, that is gaining in pop...
Hands-on guide to the R system for data analysis for scientists, students and practising statisticia...
Hands-On Exploratory Data Analysis with R puts the complete process of exploratory data analysis int...
Hands-on guide to the R system for data analysis for scientists, students and practising statisticia...
Exploratory data analysis is one of the first steps in statistical data analysis. It includes the...
This textbook offers an easy-to-follow, practical guide to modern data analysis using the programmin...
This chapter serves as an introduction to the other chapters in Part II. Its main objectives are to ...
This chapter reviews the basics of the R statistical environment. The topics discussed here include ...
This contemporary presentation of statistical methods features extensive use of graphical displays f...
International audienceR is one of the most widely used computer languages for data analysis. The aim...
Everyone is a data analyst. The purpose of this book is to inspire and enable anyone who reads it to...
This guide for practicing statisticians, data scientists, and R users and programmers will teach the...
This tutorial explores how scholars can organize 'tidy' data, understand R packages to manipulate da...
This R script was used to explore patterns within the data. Comments are used to briefly describe th...
As more and more historical records are digitized, having a way to quickly analyze large volumes of ...
R (R Development Core Team, 2011) is a very powerful tool to analyze data, that is gaining in pop...
Hands-on guide to the R system for data analysis for scientists, students and practising statisticia...
Hands-On Exploratory Data Analysis with R puts the complete process of exploratory data analysis int...
Hands-on guide to the R system for data analysis for scientists, students and practising statisticia...
Exploratory data analysis is one of the first steps in statistical data analysis. It includes the...
This textbook offers an easy-to-follow, practical guide to modern data analysis using the programmin...
This chapter serves as an introduction to the other chapters in Part II. Its main objectives are to ...
This chapter reviews the basics of the R statistical environment. The topics discussed here include ...
This contemporary presentation of statistical methods features extensive use of graphical displays f...
International audienceR is one of the most widely used computer languages for data analysis. The aim...
Everyone is a data analyst. The purpose of this book is to inspire and enable anyone who reads it to...
This guide for practicing statisticians, data scientists, and R users and programmers will teach the...
This tutorial explores how scholars can organize 'tidy' data, understand R packages to manipulate da...
This R script was used to explore patterns within the data. Comments are used to briefly describe th...
As more and more historical records are digitized, having a way to quickly analyze large volumes of ...
R (R Development Core Team, 2011) is a very powerful tool to analyze data, that is gaining in pop...