rename.R

# Load libraries
library(tidyverse)

# Original names
df <- tibble(Q1=c(1), Q2=c(1), Q3=c(1), Q4=c(1), Q5=c(1), Q6=c(1), Q7=c(1), Q25_1=c(1), Q25_2=c(1), Q25_3=c(1), Q25_4=c(1), Q25_5=c(1), Q25_6=c(1), Q25_7=c(1), Q25_8=c(1), Q25_9=c(1), Q25_10=c(1), Q25_11=c(1), Q25_12=c(1), Q25_13=c(1), Q25_14=c(1), Q25_15=c(1), Q25_16=c(1), Q26_1=c(1), Q26_2=c(1), Q26_3=c(1), Q26_4=c(1), Q26_5=c(1), Q26_6=c(1), Q26_7=c(1))
df %>% glimpse()

# Option A) Using select and rename_with
df %>%
  select(
    English = Q1,
    Familiar_CSD = Q2,
    Familiar_CSD_2 = Q3,
    Age = Q4,
    Gender = Q5,
    Race = Q6,
    Ethnicity = Q7,
    starts_with("Q25_"),
    starts_with("Q26_")
  ) %>%
  rename_with(~ str_replace(., "^Q25_(\\d+)",  "LC\\1_dys")) %>%
  rename_with(~ str_replace(., "^Q26_(\\d+)",  "S\\1_dys")) %>%
  glimpse()

# Option B) Using character vector and set_names
nicer <- c(
  "English",
  "Familiar_CSD",
  "Familiar_CSD_2",
  "Age",
  "Gender",
  "Race",
  "Ethnicity",
  c(paste0("LC",1:16,"_dys")),
  c(paste0("S",1:7,"_dys"))
)
df %>%
  set_names(nicer) %>%
  glimpse()