Approximately 80% of the data analyst’s time is often spent on data manipulation – which is the process of getting data from various sources, cleaning and transforming it for analysis and visualisation purposes. In fact, the usefulness of data depends on the analyst’s ability to manipulate it. This course introduces participants to facilities available in R to turn messy and unrefined raw data into clear and actionable bits of information. It builds on top of the introduction to R course. It is therefore important that you have taken that course or you have good grasp of the basics of R already. We shall look at some of the most common data manipulation procedures like reading, recoding, subsetting, selecting, merging and saving data.
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