2 Getting Started with R

Over the last few years, two approaches have emerged to deal with issues related to the quantitative analysis of text: R and Python. While Python is a general-purpose language (useful for everything from websites to games to databases), R was always designed with statistics in mind. As a result, R is better suited to deep statistical analysis and a wide range of data visualisation. As a result, while Python is a good choice when dealing with issues related to machine learning and large-scale applications, R is better suited to statistical learning and data exploration. Since we are mainly interested in the latter here, we built this book around R (and all the packages it offers). If you are more interested in large-scale analysis using Python, be sure to take a look at its spaCy and NLTK libraries.