In this chapter, you learned to import and read data from different sources such as CSV, TXT, XLSX, and relational data sources and the different data types available in R such as numeric, integer, character, and logical data types. We covered the basic data preprocessing techniques used to handle outliers, missing data, and inconsistencies in order to facilitate analysis.

You learned to perform different arithmetic operations that can be performed on the data using R, such as addition, subtraction, multiplication, division, exponentiation, and modulus, and also learned the string operations that can be performed on the data using R, such as subsetting a string, replacing a string, changing the case, and splitting the string into characters, which helps in data manipulation. Finally, you learned about the different control structures in R, such as if, else, for, while, repeat, break, next, and return, which facilitate a recursive or logical execution. We also covered bringing data to a usable format for analysis and building a model. In the next chapter, we will see how to perform exploratory data analysis using R. It will include a few statistical techniques and also variable analyses, such as univariate, bivariate, and multivariate analyses.