Statistical data cleaning with applications in R - Jonge, Edwin de, 1972-; Loo, Mark van der, 1976- ([Hoboken, NJ] : John Wiley & Sons Ltd, 2018)
A comprehensive guide to automated statistical data cleaning The production of clean data is a complex and time-consuming process that requires both technical know-how and statistical expertise. Statistical Data Cleaning brings together a wide range of techniques for cleaning textual, numeric or categorical data. This book examines technical data cleaning methods relating to data representation and data structure. A prominent role is given to statistical data validation, data cleaning based on predefined restrictions, and data cleaning strategy. Key features: -Focuses on the automation of data cleaning methods, including both theory and applications written in R. -Enables the reader to design data cleaning processes for either one-off analytical purposes or for setting up production systems that clean data on a regular basis. -Explores statistical techniques for solving issues such as incompleteness, contradictions and outliers, integration of data cleaning components and quality monitoring. -Supported by an accompanying website featuring data and R code. This book enables data scientists and statistical analysts working with data to deepen their understanding of data cleaning as well as to upgrade their practical data cleaning skills. It can also be used as material for a course in data cleaning and analyses.
10.11.1 Formal Description -- 10.11.2 Application to Imputed Data -- 10.11.3 Adjusting Imputed Values with the rspa Package -- Chapter 11 Example: A Small Data-Cleaning System -- 11.1 Setup -- 11.1.1 Deterministic Methods -- 11.1.2 Error Localization -- 11.1.3 Imputation -- 11.1.4 Adjusting Imputed Data -- 11.2 Monitoring Changes in Data -- 11.2.1 Data Diff (Daff) -- 11.2.2 Summarizing Cell Changes -- 11.2.3 Summarizing Changes in Conformance to Validation Rules -- 11.2.4 Track Changes in Data Automatically with lumberjack -- 11.3 Integration and Automation -- 11.3.1 Using RScript -- 11.3.2 The docopt Package -- 11.3.3 Automated Data Cleaning -- References -- Index -- EULA.
Includes bibliographical references and index.
Online resource; title from digital title page (viewed on June 13, 2018).
Keywords: Statistics -- Data processing; R (Computer program language); MATHEMATICS -- Applied; MATHEMATICS -- Probability & Statistics -- General; R (Computer program language); Statistics -- Data processing; Electronic books