R Programming Fundamentals: Deal with data using various modeling techniques

R Programming Fundamentals: Deal with data using various modeling techniques

Author
Kaelen Medeiros
Publisher
Packt Publishing
Language
English
Page
206
ISBN
9781789612998,1789612993
File Type
pdf
File Size
8.7 MiB

Study data analysis and visualization to successfully analyze data with R Key Features Get to grips with data cleaning methods Explore statistical concepts and programming in R, including best practices Build a data science project with real-world examples Book Description
R Programming Fundamentals, focused on R and the R ecosystem, introduces you to the tools for working with data. To start with, you'll understand you how to set up R and RStudio, followed by exploring R packages, functions, data structures, control flow, and loops.
Once you have grasped the basics, you'll move on to studying data visualization and graphics. You'll learn how to build statistical and advanced plots using the powerful ggplot2 library. In addition to this, you'll discover data management concepts such as factoring, pivoting, aggregating, merging, and dealing with missing values.
By the end of this book, you'll have completed an entire data science project of your own for your portfolio or blog. What you will learn Use basic programming concepts of R such as loading packages, arithmetic functions, data structures, and flow control Import data to R from various formats such as CSV, Excel, and SQL Clean data by handling missing values and standardizing fields Perform univariate and bivariate analysis using ggplot2 Create statistical summary and advanced plots such as histograms, scatter plots, box plots, and interaction plots Apply data management techniques, such as factoring, pivoting, aggregating, merging, and dealing with missing values, on the example datasets Who this book is for
R Programming Fundamentals is for you if you are an analyst who wants to grow in the field of data science and explore the latest tools. Table of Contents Introducing R Data Visualization and Graphics Data Management

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