R for Data Science Cookbook

R for Data Science CookbookThis cookbook offers a range of data analysis samples in simple and straightforward R code, providing step step resources and time saving methods to help you solve data problems efficiently."margin top: 0. 6em; margin bottom: 1. 2em; padding: 0px; color: rgb(73, 73, 73); font family: Ubuntu, sans serif; background color: rgb(243, 247, 248);"The first section deals with how to create R functions to avoid the unnecessary duplication of code. You will

This cookbook offers a range of data analysis samples in simple and straightforward R code, providing step--step resources and time-saving methods to help you solve data problems efficiently."margin-top: 0.6em; margin-bottom: 1.2em; padding: 0px; color: rgb(73, 73, 73); font-family: Ubuntu, sans-serif; background-color: rgb(243, 247, 248);"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."margin-top: 0.6em; margin-bottom: 1.2em; padding: 0px; color: rgb(73, 73, 73); font-family: Ubuntu, sans-serif; background-color: rgb(243, 247, 248);"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. 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.