Book Image

R for Data Science Cookbook (n)

By : Yu-Wei, Chiu (David Chiu)
Book Image

R for Data Science Cookbook (n)

By: Yu-Wei, Chiu (David Chiu)

Overview of this book

This cookbook offers a range of data analysis samples in simple and straightforward R code, providing step-by-step resources and time-saving methods to help you solve data problems efficiently. The first section deals with how to create R functions to avoid the unnecessary duplication of code. You will learn how to prepare, process, and perform sophisticated ETL for heterogeneous data sources with R packages. An example of data manipulation is provided, illustrating how to use the “dplyr” and “data.table” packages to efficiently process larger data structures. We also focus on “ggplot2” and show you how to create advanced figures for data exploration. In addition, you will learn how to build an interactive report using the “ggvis” package. Later chapters offer insight into time series analysis on financial data, while there is detailed information on the hot topic of machine learning, including data classification, regression, clustering, association rule mining, and dimension reduction. By the end of this book, you will understand how to resolve issues and will be able to comfortably offer solutions to problems encountered while performing data analysis.
Table of Contents (19 chapters)
R for Data Science Cookbook
About the Author
About the Reviewer


The first example of time series analysis in human history occurred in ancient Egypt. The ancient Egyptians recorded the inundation (rise) and relinquishment (fall) of the Nile river every day, noting when fertile silt and moisture occurred. Based on these records, they found that the inundation period began when the sun rose at the same time as the Sirius star system became visible. By being able to predict the inundation period, the ancient Egyptians were able to make sophisticated agricultural decisions, greatly improving the yield of their farming activities.

As demonstrated by the ancient Egyptian inundation period example, time series analysis is a method that can extract patterns or meaningful statistics from data with temporal information. It allows us to forecast future values based on observed results. One can apply time series analysis to any data that has temporal information. For example, an economist can perform time series analysis to predict the GDP growth rate...