Concept Taxonomy

[b4D8]

Hi,

I'd like to offer my contribution to the R track by providing a few concepts. I didn't see any reference to a roadmap related to this matter. Is there a concept taxonomy being worked on by anyone?

Here's a first draft of one I've been working on:

slug	name	blurb	prerequisite	covers	priority
objects	R Objects	Objects are R fundamental entities		general intro, the assignment operator and naming things	1
atomic-vectors	Atomic Vectors	All Values are Vectors	objects	length(), scalar and empty vectors, positional subsetting with [i], c(), seq()	2
logical-type	Logical Data Type	Using Booleans with Logical Vectors	atomic-vectors	logical constants (TRUE, FALSE), comparison operators and basic logical operators (&, I, !), create with logical(), coerce with as.(), check with is.()	3
numeric-mode	Numeric Data Type	Using Integers and Floats with Numeric Vectors	logical-type	integer and double types, L suffix, 32 bits constraint, numeric constants (pi, Inf), arithmetic operators, recycling, ":"	4
character-type	Character Data Type	Using Strings with Character Vectors	numeric-mode	basic string manipulation, nchar(), maybe strsplit(), character constants (letters, LETTERS etc.)	5
missing-value	Missing Value	Dealing with Missing Values	character-type	NA (maybe NaN), NULL, is.na(), is.null(), the na.rm argument	6
names-attribute	Attributes and Names	Naming things is hard	missing-value	attributes(), attr(), names(), subsetting with ["name"]	8
functions	Functions	Let’s do stuff and automate it	names-attribute	arguments, named arguments, formals, body, return keyword, "…"	7
class-attribute	Classes	R has one of the most flexible class system	functions	class(), unclass(), generic functions (S3) and method dispatch, special double dispatch for grouped generic functions	14
conditions	Conditions	Control your code execution with if statements	names-attribute	If, else, lazy evaluation with && and ||, xor(), precedence, identical(), all(), any()	9
iterations	Iterations	Repetitive code execution with loops	conditions	for, in, seq_along(), while, repeat, next, break	10
exceptions	Exceptions	Handling errors and recovering	functions	stop(), stopifnot(), warning(), try()	15
factors	Factors	Integer representation or characters	missing-value	ordered and unordered factors, levels attribute, stringsAsFactors argument, maybe cut()	19
dim-attribute	Dimensions	Dimensions of an Object	names-attribute	array, matrix, subsetting with [i, j, k], dimnames attribute	20
switch	Switch	Select One of a List of Alternatives	missing-value	on character or numeric expressions	18
lists	Lists	Lists are Recursive Vectors	atomic-vectors	subsetting with [[ and $	11
tabular-data	Tabular Data	Lists superpowers	lists, class-attribute	data.frame, row.names attribute, cbind(), rbind(), subsetting with [row, col]	12
selection	Subsetting	Chirurgical operations	tabular-data	Summary of [, [[, $ , sort(), order(), which() and %in% for subsetting	13
apply-functions	Apply Functions Family	Apply functions are here to help you vectorize your code	functions, iterations, lists	lapply, sapply, vapply etc.	16
regex-functions	Regex Functions Family	Pattern Matching and Replacement	functions	grep(), grepl(), regexpr(), gregexpr(), regexec(), gregexec(), sub(), gsub() maybe stringr::	17
raw-type	Raw Data Type	Store raw bytes	character-type	strtoi(), charToRaw() - there’s actual use case in exercises so it might deserve higher priority but seems somewhat advanced	22
environments	Environments	Lexical and Dynamic Scoping	functions	current, global, closure, <<-, namespace	21

Additional concepts that could also be introduced:

• pipes (base R and magrittr)
• maps (purrr)

I don't really know at what point I would be a good idea to introduce recursion (functions, lists, iterations...).

Of course this is all work in progress and need much more thoughts, but I'd like to have your feedback before I look further into this (on the concepts themselves - definition, scope and order, as well as the method as I'm new to Exercism)

Major references:

• R Intro
• Advanced R

[jonmcalder]

Hi there

I haven't been through this in detail but it looks like a really solid start. As far as I know no-one has started working on a concept taxonomy for R yet - so your contribution is most welcome. Have you considered signing up as a mentor? https://exercism.org/mentoring

Should you wish to become a mentor, that should get you an invite to the Slack channel where you can then also be in touch with other track mentors and maintainers which could help a lot in facilitating further contributions to the R track. No pressure of course, just a suggestion.

[b4D8]

Hi, I just enrolled slack, thanks for the input. I look forward to introduce myself, get to know the inner workings of the team and see how I can be useful to the R track.

[jonmcalder]

Awesome!