R Tutorial: Data Manipulation with data.table in R | Intro

Want to learn more? Take the full course at https://learn.datacamp.com/courses/data-manipulation-with-datatable-in-r at your own pace. More than a video, you'll learn hands-on coding & quickly apply skills to your daily work. --- Welcome to the new and renewed introductory course on R's data table package. I am Arun Srinivasan, a data scientist in the Finance industry. We hope that you are already familiar with data frames at this point. A data table is also a data frame but does so much more. Like data frames, they are columnar data structures and all columns must be of equal length. So why do you need data tables? A data table is a 2-D data structure, the two dimensions being rows and columns. However, most data analysis tasks require performing operations by groups. It is quite common to consider grouping as a virtual third dimension. The data table syntax is quite powerful because it provides quick access to these dimensions in the form of placeholders for operations on rows, columns, and groups. The first argument, 'i' allows for filtering of required rows by accepting an expression or simply the required row numbers. If the 'i' argument is empty, then no rows are filtered. The second argument, 'j' operates on columns. In addition to just selecting columns as in a data frame, it also allows for directly computing on the columns as you will see in the next chapters. The last argument 'by' allows you to operate on columns by groups. data table is also very fast - many operations are parallelized including filtering, ordering, grouping, file reading, writing etc. Check out this link for up-to-date benchmarks on data table's performance against other common packages. Finally, data table has many additional powerful features including rolling, overlapping and non-equi joins, updating tables by reference, fast reshaping, parallel file reading/writing, primary key based joins, automatic creation of secondary keys for faster filtering and joins etc. We will n