Is this path about R's data structures, like vectors and data frames?
Not mainly. R's own data types are atomic vectors, lists (which nest), matrices, data frames and factors; they are what most guides to data structures in R cover, and Coddy's R course teaches them. This path is the computer science meaning: stacks, queues, linked lists, hash tables, heaps, tries, trees and graphs, built in R and then used for sorting, recursion and graph algorithms.
Is R good for data structures and algorithms?
It works, with some friction. R is built for vectorized statistics, not for structures made of linked nodes, so a linked list or a tree takes more thought than in Python, and coding interviews are rarely held in R. For an analyst, that friction is the value: knowing that growing a vector in a loop is quadratic, or that an environment is a hash map, is what makes R code scale to real data.
How do you make a hash map in R?
With an environment: h <- new.env(), then h[[key]] <- value to store and h[[key]] to read, which gives NULL for a missing key. Environments are hashed, keyed by strings, and have reference semantics, so a function that changes one changes it for the caller too, unlike a vector or a list. A named list looks like a dictionary but behaves like a value: change it inside a function and the caller's copy is untouched.
Does deep recursion fail in R?
It can. By default options(expressions = 5000) caps how deeply evaluation may nest, and a deep recursion, such as a depth-first search down a long chain, stops with an evaluation nested too deeply error. Raising the option buys some room; the reliable fix is an explicit stack in a loop, the structure you build in step one.
Which courses on this path are not taught in R?
Three: dynamic programming and the Python interview series, taught in Python, and bit manipulation, taught in C++. They are listed after the steps, each with a link that opens it in its own language. Dynamic programming translates directly, a memo table in R being a preallocated vector, and C++'s &, |, ^ and << become the functions bitwAnd, bitwOr, bitwXor and bitwShiftL.
Do I need to know R before starting this path?
Vectors, lists, functions, loops and indexing from 1, at least. If those are new, Coddy's R course takes you there first, free, and this path picks up where it ends.
