Book Image

Data Wrangling with R

By : Gustavo R Santos
Book Image

Data Wrangling with R

By: Gustavo R Santos

Overview of this book

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.
Table of Contents (21 chapters)
1
Part 1: Load and Explore Data
5
Part 2: Data Wrangling
12
Part 3: Data Visualization
16
Part 4: Modeling

Map plots

We live in the information era. Enormous amounts of data are created each day, from all parts of the world. Part of that data has location information attached to it (latitude and longitude), enabling the data scientists that have access to it to create visualizations using maps. Anaysis of store sales by city, state taxes collection, tourism destinations, and internet access by country are only a few examples of a large spectrum of possibilities. That is enough reason to learn how to use ggplot2 to create plots using maps.

A side note before we jump into the action is that map plots are a vast domain as well, being part of the spatial data analysis domain, which is out of the scope of this book. Here, the intention is to show the capabilities of ggplot2. To learn in more depth about map plotting, there is some material available in the Further reading section.

To plot a map, the geometry used is geom_map(). But before we can plot anything, ggplot2 requires us to load...