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Data Wrangling with R

Data Wrangling with R

By : Gustavo R Santos, Gustavo Santos
4.9 (7)
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Data Wrangling with R

Data Wrangling with R

4.9 (7)
By: Gustavo R Santos, Gustavo 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)
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1
Part 1: Load and Explore Data
5
Part 2: Data Wrangling
12
Part 3: Data Visualization
16
Part 4: Modeling

Basic Data Visualization

Perhaps I am too bold for saying this, but I don’t think there is a point in wrangling or analyzing data if you are not going to visualize it. As previously mentioned, the human brain is so much better at understanding images than numbers or words. Furthermore, in the era of huge amounts of data, presenting tables would not be the most interesting way to identify or even just visualize patterns.

Data visualization means presenting information in a visual format, such as a graphic, a map, or another visual way of encoding data, such as an infographic, for instance, which is a combination of graphics, text, and other elements that help you to tell a story and transmit a message.

In this chapter, we are going to see basic data visualization using the native plotting capabilities of RStudio. We will start with plots of a single variable, which are the best way to visualize distributions. Included in this group are histograms, boxplots, and density...

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