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Data Visualization and Exploration with R A Practical Guide to Using R RStudio and Tidyverse for Data

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Today, data science is an indispensable tool for any organization, allowing for the analysis and optimization of decisions and strategy. R has become the preferred software for data science, thanks to its open source nature, simplicity, applicability to data analysis, and the abundance of libraries for any type of algorithm.This book will allow the student to learn, in detail, the fundamentals of the R language and additionally master some of the most efficient libraries for data visualization in chart, graph, and map formats. 238 Pages · 2018 · 20.77 MB · English

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Description

Discover best practices for data analysis and software development in R and start on the path to becoming a fully-fledged data scientist. This book teaches you techniques for both data manipulation and visualization and shows you the best way for developing new software packages for R.
Data Science in R details how data science is a combination of statistics, computational science, and machine learning. You ll see how to efficiently structure and mine data to extract useful patterns and build mathematical models. This requires computational methods and programming, and R is an ideal programming language for this.
This book is based on a number of lecture notes for classes the author has taught on data science and statistical programming using the R programming language. Modern data analysis requires computational skills and usually a minimum of programming.
What You Will Learn
Perform data science and analytics using statistics and the R programming language

Visualize and explore data, including working with large data sets found in big data

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