Naming stuff

1 Naming stuff

1.1 Meaning

Let variable, function and file names convey meaning.

# 1 
d <- d %>% 
  mutate(s=factor(c("M", "F"))[as.numeric(substr(id,nchar(id),nchar(id))) %% 2])

# 2 
mData <- d %>% filter(s=="M")

Look at the code and suggest better variable names

Suggested solution

# 1 
data <- data %>% 
  mutate(sex=factor(c("M", "F"))[as.numeric(substr(id,nchar(id),nchar(id))) %% 2])

# 2 
data_males_only <- data %>% filter(sex=="M")
males_only_data <- data %>% filter(sex=="M")

An even better solution

data <- data %>% 
  mutate(sex=cpr2sex(id))

Alas, the function cpr2sex does not exist in base R or Tidyverse, but we can write it ourselves:

Tip

# Requires a custom function like this -- which could be sourced from file

cpr2sex <- function(x) {
  # This function takes a string (x), presumed to be a valid Danish CPR
  # and return "F", "M" or NA depending on the last character in the string
  # If the last CPR character is an even number, it indicates female sex, and
  # an odd number indicates male sex.
  if (str_sub(x, str_length(x), str_length(x)) %in% c("0","2","4","6","8")) {
    return("F") 
  } else if (str_sub(x, str_length(x), str_length(x)) %in% c("1","3","5","7","9")) {
    return("M") 
  } 
  return(NA) # Last character in CPR is not a ciffre
}

We could hide this away in a separate file and ‘source’ it .. or even make a new package…

1.2 Compound names

• Do use under_scores
• Do not use camelCase
• Do not use kebab-case

1.3 Nouns and verbs

make_larger_by_10 <- function(x) {
  return(x+10)
}

ten_larger <- make_larger_by_10(112)

# For instance:
# selected_data <- data %>% select(..)

1.4 Names

Main points

• Names should be meaningful
• Use under_scores, not CamelCase, nor kebab-case
• Function names should be verbs
• Variable names should be nouns