In jvcasillas/ds4ling: Datasets and Functions developed for SPAN658: Data Science for Linguists

Comments

In R, anything that comes after a hashtag (or pound, #) is considered a comment. Comments are important because they help you to remember what you did, why you did it, etc. You should think of adding comments as a way for you to leave little notes to future you and others that will help you/them to understand your workflow. Here is a trivial example with some simple math a few comments.

#############################
# Always comment your code! #
#############################

# This is a comment
2 + 2

It is good practice to also use comments to separate important sections of your script. In the example below, I separate important setup code from the descriptive statistics, with explanations of what I am doing before each function call.

# Setup ------------------------------------------------------------------

# Load packages
library(tidyverse)
library(lingStuff)

# Load data
important_data <- read_csv("./data/my_data.csv")

# Check structure
skimr::skim(important_data)



# Descriptives -----------------------------------------------------------

# Get summary stats
summary(important_data)

# Calculate means and SD
important_data %>% 
  group_by(., var1) %>% 
  summarise(., var2_mean = mean(var2), var2_sd = sd(var2))

You will always be thankful when you receive well commented code!

jvcasillas/ds4ling documentation built on March 4, 2025, 11:18 p.m.