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Published in:
2018 | OriginalPaper | Chapter
3. Managing Data in R
Author : Ivo D. Dinov
Published in: Data Science and Predictive Analytics
Publisher: Springer International Publishing
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Abstract
In this Chapter, we will discuss strategies to
import data and export results. Also, we are going to learn the basic tricks we need to know about processing different types of data. Specifically, we will illustrate common R data structures and strategies for loading (ingesting) and saving (regurgitating) data. In addition, we will (1) present some basic statistics, e.g., for measuring central tendency (mean, median, mode) or dispersion (variance, quartiles, range); (2) explore simple plots; (3) demonstrate the uniform and normal distributions; (4) contrast numerical and categorical types of variables; (5) present strategies for handling incomplete (missing) data; and (6) show the need for cohort-rebalancing when comparing imbalanced groups of subjects, cases or units.