Data Wrangling with R

eBook Details:

• Paperback: 384 pages
• Publisher: WOW! eBook (February 23, 2023)
• Language: English
• ISBN-10: 1803235403
• ISBN-13: 978-1803235400

eBook Description:

Data Wrangling with R: Take your data wrangling skills to the next level by gaining a deep understanding of tidyverse libraries and effectively prepare your data for impressive analysis

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.

• Discover how to load datasets and explore data in R
• Work with different types of variables in datasets
• Create basic and advanced visualizations
• Find out how to build your first data model
• Create graphics using ggplot2 in a step-by-step way in Microsoft Power BI
• Get familiarized with building an application in R with Shiny

By the end of this Data Wrangling with R book, you’ll have learned how to create your first data model and build an application with Shiny in R.