Code
library(tidyverse)
library(praise)library(tidyverse)
library(praise)This week’s dataset explores baby names in the UK.
There are three datasets which cover baby names across England and Wales from the Office for National Statistics, Northern Ireland from the Northern Ireland Statistics and Research Agency, and Scotland from National Records of Scotland.
Dearest gentle reader… we can report that Daphne, Eloise and Penelope have all increased in popularity this year, with the name of each Bridgerton character reaching joint 172nd, 91st, and 71st place respectively, up from 476th, 124th, and 81st in 2024.
Thank you to Nicola Rennie for curating this week’s dataset.
england_wales_names <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/main/data/2026/2026-06-16/england_wales_names.csv')
ni_names <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/main/data/2026/2026-06-16/ni_names.csv')
scotland_names <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/main/data/2026/2026-06-16/scotland_names.csv')all_names <- rbind(
cbind(england_wales_names, country = "England & Wales"),
cbind(ni_names, country = "Northern Ireland"),
cbind(scotland_names, country = "Scotland")
)all_names |>
filter(Name %in% c("Frida", "Frances", "Nathalie", "Johanna", "Simon")) |>
ggplot(aes(x = Year, y = Number, color = Name, shape = Sex)) +
geom_line() +
geom_point() +
facet_grid(~country) +
scale_y_log10(labels = scales::label_number()) +
theme_minimal() +
labs(x = "", y = "", title = "Number of babies with a given name")praise()[1] "You are well-made!"