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

Summary

In this chapter, numbers were on display. The R language is great for dealing with numbers, since the software was created as a statistical tool. As we know, statistics is all about numbers, so we were able to see that many of the functions used during this chapter are from the Base R, eliminating the need to install or load any library to work with so many useful functions.

We started the chapter by learning about structures with numbers, such as vectors, matrices, and data frames. That knowledge prepared us for the next section, where we studied many operations to deal with numbers in vectors and data frames, and we learned a good resource for that is the apply family of functions.

We also went over how descriptive statistics are important to help us gain an understanding of data and its distribution, because that can drive our efforts of data wrangling before modeling.

Finally, we saw the correlation test and how to interpret its result.