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Hands-On Exploratory Data Analysis with R

You're reading from  Hands-On Exploratory Data Analysis with R

Product type Book
Published in May 2019
Publisher Packt
ISBN-13 9781789804379
Pages 266 pages
Edition 1st Edition
Languages
Authors (2):
Radhika Datar Radhika Datar
Profile icon Radhika Datar
Harish Garg Harish Garg
Profile icon Harish Garg
View More author details
Toc

Table of Contents (17) Chapters close

Preface 1. Section 1: Setting Up Data Analysis Environment
2. Setting Up Our Data Analysis Environment 3. Importing Diverse Datasets 4. Examining, Cleaning, and Filtering 5. Visualizing Data Graphically with ggplot2 6. Creating Aesthetically Pleasing Reports with knitr and R Markdown 7. Section 2: Univariate, Time Series, and Multivariate Data
8. Univariate and Control Datasets 9. Time Series Datasets 10. Multivariate Datasets 11. Section 3: Multifactor, Optimization, and Regression Data Problems
12. Multi-Factor Datasets 13. Handling Optimization and Regression Data Problems 14. Section 4: Conclusions
15. Next Steps 16. Other Books You May Enjoy

Introducing and reading the dataset

In this chapter, we will focus on the dataset that consists of the responses of a gas with the help of a multi-sensor device. The dataset includes an hourly response average, which is being recorded along with gas concentrations and proportions. This dataset is referred to as an Air Quality Dataset.

You can download the file from the following link:

https://github.com/PacktPublishing/Hands-On-Exploratory-Data-Analysis-with-R/tree/master/ch07.

For more information, you can refer to the link specified as follows:
https://archive.ics.uci.edu/ml/machine-learning-databases/00360/.

In this section, we will be focusing on reading the attributes of the dataset and converting the .csv or .xls file to a data frame or dataset in the R workspace (with workspace, we are referring to the R environment where various data manipulations can be performed). As...

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