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

Downloading open data

Before conducting any data analysis, an essential step is to collect high-quality, meaningful data. One important data source is open data, which is selected, organized, and freely available to the public. Most open data is published online in either text format or as APIs. Here, we introduce how to download the text format of an open data file with the download.file function.

Getting ready

In this recipe, you need to prepare your environment with R installed and a computer that can access the Internet.

How to do it…

Please perform the following steps to download open data from the Internet:

  1. First, visit the link to view the historical price of the S&P 500 in Yahoo Finance:

    Figure 1: Historical price of S&P 500

  2. Scroll down to the bottom of the page, right-click and copy the link in Download to Spreadsheet (the link should appear similar to