Overview

PREPARATION

At this point we will turn our attention to implementing the specifics outlined in our research blueprint. This section will group the components which concern the acquisition, curation, and transformation of data into a dataset which is prepared to be submitted to analysis. In each of these three chapters I will outline some of the main characteristics to consider in each of these research steps and provide authentic examples of working with R to implement these steps. In Chapter 5 this includes downloads, working with APIs, and webscraping. In Chapter 6 we turn to organize data into rectangular, or ‘tidy’, format. Depending on the data or dataset acquired for the research project, the steps necessary to shape our data into a base dataset will vary, as we will see. In Chapter 7 we will work to manipulate curated datasets to create datasets which are aligned with the research aim and research question. This often includes normalizing values, recoding variables, and generating new variables as well as and sourcing and merging information from other datasets with the dataset to be submitted for analysis.