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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

Working with Date and Time Objects

Computers are complex machines that can, among many other things, record date and time. The world is so attached to the measurement of time that it drives a great part of our daily lives. We work within a time interval, we are supposed to go to school for a determinate minimum number of years, and even the value of our work is calculated based on time. Likewise, the business world is also run by the wheel of time. This is evident because of the popular saying: time is money.

Dates and times are just like other types of data, holding valuable information and good business insights if you know how to handle them. During a data exploration that involves a datetime variable, questions such as What is the busiest month, day, and hour? Which days of the week have more traffic? or How much was the revenue in the past 3 months? will arise, and we must know how to deal with those objects to facilitate better analysis.

There are three main ways to work...

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