Abedin - Data manipulation with R: perform group-wise data manipulation and deal with large datasets using R efficiently and effectively

A. Dhandapani is currently working as a professor of Statistics and Computer Applications at the National Academy of Agricultural Research Management (NAARM), Hyderabad, India. He holds a Master's and a Ph.D. degree in Agricultural Statistics from the Indian Agricultural Research Institute, New Delhi, specializing in sampling techniques. He joined the Agricultural Research Service of the Indian Council of Agricultural Research in the discipline of Agricultural Statistics in 1996 and was posted as a scientist at New Delhi. He has worked in the area of pest surveillance, pest forewarning models, and developed several information systems (both web-and desktop-based) in the area of plant protection. He has also developed a web-based application for the generation of Hadamard Matrices. Currently, he is teaching business management students of Business Statistics, Business Analytics, Marketing Research, Management Information System, and Enterprise Resource Planning for Agribusiness. Besides this, he trains agricultural scientists in data analysis using SAS. He is also involved in creating information systems for the collection and analysis of data collected from large-scale coordinated trials in agriculture.

Colman McMahon is a PhD fellow in the Dynamics Lab, University College, Dublin. His research is on policy network analysis and data visualization of the EU's proposed General Data Protection Regulation. This project is a part of the Simulation Science program run under the auspices of the Complex Adaptive Systems Laboratory (CASL). In addition to research, he has lectured on data visualization and knowledge management for M.Sc Computer Science courses. Prior to his full immersion into academia, he has worked in visual effects for film and television in Los Angeles and was an independent technology consultant.

Vignesh Prajapati is a Big Data scientist at Pingax. He loves to play with open source technologies like R, Hadoop, MongoDB, and Java. He has been working on data analytics with machine learning, R, Hadoop, RHadoop, and MongoDB. He has expertise in algorithm development for Data ETL and generating recommendations, prediction, and behavioral targeting over e-commerce historical Google Analytics, and other datasets. He has also written several articles on R, Hadoop, and machine learning fields for producing intelligent Big Data applications. He can be contacted at <.

Vignesh has worked on another book with Packt Publishing. He has written Big Data Analytics with R and Hadoop (https://www.packtpub.com/big-data-analytics-with-r-and-hadoop/book).

Firstly, I would like to thank my teachers, who introduced me to this wonderful open source technology during my undergraduate years. Then I would like to express my gratitude to my family, friends, colleagues, and well wishers, who always motivated me to contribute to this technology. Last but not least, I would like to express my deepest gratitude to Packt Publishing and its team, who gave me the opportunity to write this book. Finally, I am grateful to all of the reviewers for their time and constructive suggestions.

This book, Data Manipulation with R , is aimed at giving intermediate to advanced level users of R (who have knowledge about datasets) an opportunity to use state-of-the-art approaches in data manipulation. This book will discuss the types of data that can be handled using R and different types of operations for those data types. Upon reading this book, readers will be able to efficiently manage and check the validity of their datasets with the effective use of R programming, including specialized packages for data management. Readers will come to know about the split-apply-combine strategy, which is the state-of-the-art approach in data management. This book ends with an introduction to how R can be utilized with different database software.