{"product_id":"r-for-data-science-cookbook","title":"R for Data Science Cookbook","description":"\u003cp\u003eThis 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.\u003c\/p\u003e\u003cp style=\"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);\"\u003eThe 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.\u003c\/p\u003e\u003cp style=\"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);\"\u003eIn 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.\u003c\/p\u003e\u003cp\u003eBy 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.\u003c\/p\u003e\u003ch2 style=\"margin-bottom: 20px; font-weight: 300; font-family: Ubuntu, sans-serif; font-size: 2em; line-height: 36.4px; color: rgb(73, 73, 73); background-color: rgb(243, 247, 248);\"\u003eWhat You Will Learn\u003c\/h2\u003e\u003cdiv class=\"book-info-will-learn-text\" style=\"color: rgb(73, 73, 73); font-family: Ubuntu, sans-serif; background-color: rgb(243, 247, 248);\"\u003e\u003cul\u003e\n\u003cli\u003eGet to know the functional characteristics of R language\u003c\/li\u003e\n\u003cli\u003eExtract, transform, and load data from heterogeneous sources\u003c\/li\u003e\n\u003cli\u003eUnderstand how easily R can confront probability and statistics problems\u003c\/li\u003e\n\u003cli\u003eGet simple R instructions to quickly organize and manipulate large datasets\u003c\/li\u003e\n\u003cli\u003eCreate professional data visualizations and interactive reports\u003c\/li\u003e\n\u003cli\u003ePredict user purchase behavior by adopting a classification approach\u003c\/li\u003e\n\u003cli\u003eImplement data mining techniques to discover items that are frequently purchased together\u003c\/li\u003e\n\u003cli\u003eGroup similar text documents by using various clustering methods\u003c\/li\u003e\n\u003c\/ul\u003e\u003c\/div\u003e\u003ch2 style=\"margin-bottom: 20px; font-weight: 300; font-family: Ubuntu, sans-serif; font-size: 2em; line-height: 36.4px; color: rgb(73, 73, 73); background-color: rgb(243, 247, 248);\"\u003eAuthors\u003c\/h2\u003e\u003cdiv class=\"book-info-bottom-author-text\" style=\"color: rgb(73, 73, 73); font-family: Ubuntu, sans-serif; background-color: rgb(243, 247, 248);\"\u003e\u003cdiv itemprop=\"author\" itemscope=\"\" itemtype=\"http:\/\/schema.org\/Person\"\u003e\u003cdiv class=\"book-info-bottom-author-title\"\u003e\u003ch3 itemprop=\"name\" style=\"margin-bottom: 10px; font-weight: normal; font-family: Ubuntu, sans-serif; font-size: 1.3em;\"\u003eYu-Wei, Chiu (David Chiu)\u003c\/h3\u003e\u003c\/div\u003e\u003c\/div\u003e\u003c\/div\u003e\u003cp\u003eYu-Wei, Chiu (David Chiu) is the founder of LargitData Company. He has previously worked for Trend Micro as a software engineer, with the responsibility of building up big data platforms for business intelligence and customer relationship management systems. In addition to being a startup entrepreneur and data scientist, he specializes in using Spark and Hadoop to process big data and apply data mining techniques to data analysis. Yu-Wei is also a professional lecturer, and has delivered talks on Python, R, Hadoop, and tech talks at a variety of conferences.\u003cbr\u003e\u003c\/p\u003e\u003cp class=\"MsoNormal\" style=\"margin-bottom: 13.2pt; line-height: 24.05pt; background-image: initial; background-color: rgb(243, 247, 248);\"\u003eTable of Contents\u003co:p\u003e\u003c\/o:p\u003e\u003c\/p\u003e\u003cp class=\"MsoNormal\" style=\"margin-bottom: 0.0001pt; line-height: normal; background-image: initial; background-color: rgb(243, 247, 248);\"\u003e1:FUNCTIONS IN R\u003co:p\u003e\u003c\/o:p\u003e\u003c\/p\u003e\u003cp class=\"MsoNormal\" style=\"margin-bottom: 0.0001pt; line-height: normal; background-image: initial; background-color: rgb(243, 247, 248);\"\u003e2:DATA EXTRACTING, TRANSFORMING, AND LOADING\u003co:p\u003e\u003c\/o:p\u003e\u003c\/p\u003e\u003cp class=\"MsoNormal\" style=\"margin-bottom: 0.0001pt; line-height: normal; background-image: initial; background-color: rgb(243, 247, 248);\"\u003e3:DATA PREPROCESSING AND PREPARATION\u003co:p\u003e\u003c\/o:p\u003e\u003c\/p\u003e\u003cp class=\"MsoNormal\" style=\"margin-bottom: 0.0001pt; line-height: normal; background-image: initial; background-color: rgb(243, 247, 248);\"\u003e4:DATA MANIPULATION\u003co:p\u003e\u003c\/o:p\u003e\u003c\/p\u003e\u003cp class=\"MsoNormal\" style=\"margin-bottom: 0.0001pt; line-height: normal; background-image: initial; background-color: rgb(243, 247, 248);\"\u003e5:VISUALIZING DATA WITH GGPLOT2\u003co:p\u003e\u003c\/o:p\u003e\u003c\/p\u003e\u003cp class=\"MsoNormal\" style=\"margin-bottom: 0.0001pt; line-height: normal; background-image: initial; background-color: rgb(243, 247, 248);\"\u003e6:MAKING INTERACTIVE REPORTS\u003co:p\u003e\u003c\/o:p\u003e\u003c\/p\u003e\u003cp class=\"MsoNormal\" style=\"margin-bottom: 0.0001pt; line-height: normal; background-image: initial; background-color: rgb(243, 247, 248);\"\u003e7:SIMULATION FROM PROBABILITY DISTRIBUTIONS\u003co:p\u003e\u003c\/o:p\u003e\u003c\/p\u003e\u003cp class=\"MsoNormal\" style=\"margin-bottom: 0.0001pt; line-height: normal; background-image: initial; background-color: rgb(243, 247, 248);\"\u003e8:STATISTICAL INFERENCE IN R\u003co:p\u003e\u003c\/o:p\u003e\u003c\/p\u003e\u003cp class=\"MsoNormal\" style=\"margin-bottom: 0.0001pt; line-height: normal; background-image: initial; background-color: rgb(243, 247, 248);\"\u003e9:RULE AND PATTERN MINING WITH R\u003co:p\u003e\u003c\/o:p\u003e\u003c\/p\u003e\u003cp class=\"MsoNormal\" style=\"margin-bottom: 0.0001pt; line-height: normal; background-image: initial; background-color: rgb(243, 247, 248);\"\u003e10:TIME SERIES MINING WITH R\u003co:p\u003e\u003c\/o:p\u003e\u003c\/p\u003e\u003cp class=\"MsoNormal\" style=\"margin-bottom: 0.0001pt; line-height: normal; background-image: initial; background-color: rgb(243, 247, 248);\"\u003e11:SUPERVISED MACHINE LEARNING\u003co:p\u003e\u003c\/o:p\u003e\u003c\/p\u003e\u003cp\u003e12:UNSUPERVISED MACHINE LEARNING\u003cbr\u003e\u003c\/p\u003e","brand":"Packt Publishing","offers":[{"title":"Default Title","offer_id":50506022682694,"sku":"9781784390815","price":2959.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0754\/2797\/1142\/files\/0815OS_4007_R_Cookbook_New.jpg?v=1790317812","url":"https:\/\/cb-india.com\/products\/r-for-data-science-cookbook","provider":"Computer Bookshop (India) Pvt Ltd","version":"1.0","type":"link"}