Reshaping data is a common and tedious task in real-life data manipulation and analysis. A dataset might come with different levels of grouping, and we need to implement a reorientation to perform certain types of analysis. The layout of datasets could be long or wide. In a long layout, multiple rows represent a single subject's record, whereas, in a wide layout, a single row represents a single subject's record. Statistical analysis sometimes requires wide data and sometimes long data. In such cases, we need to be able to fluently and fluidly reshape the data to meet the requirements of statistical analysis. Data reshaping is just a rearrangement of the form of the data—it does not change the content of the dataset. In this chapter, we will show you different layouts of the same dataset and see how they can be transferred from one layout to another. This chapter mainly highlights the melt and cast paradigms of reshaping datasets, melt and cast is implemented...