Classes ‘data.table’ and 'data.frame'

Both `data.table` and `data.frame` are data structures in R used for working with tabular data. However, there are some differences between them.

`data.frame` is a built-in data structure in R, which stores data in a rectangular format where each column can have a different data type. It is a commonly used data structure, but it can become slow when working with large datasets.

`data.table` is an extension of the `data.frame` structure, designed to overcome the limitations of `data.frame` in terms of speed and memory efficiency. It is built on top of `data.frame` and provides faster and more efficient operations for working with large datasets.

Some of the key differences between `data.table` and `data.frame` are:

- Syntax: `data.table` syntax is similar to `data.frame`, but with additional syntax for advanced and efficient operations.

- Speed: `data.table` is faster than `data.frame` for most operations, especially for large datasets.

- Memory efficiency: `data.table` uses less memory than `data.frame` for certain operations, such as grouping and aggregation.

- In-place modification: `data.table` allows for in-place modification of data, which can be faster and more memory-efficient than creating new objects.

Overall, `data.table` can be a more efficient and powerful option for working with large datasets, but it may require some additional learning and syntax to use effectively.