TidyTuesday Week 42: UK Historical

The UK Met Office is the United Kingdom’s national weather and climate service, providing forecasts, severe weather warnings, and climate science expertise. It helps people, businesses, and governments make informed decisions to stay safe and plan for the future. It was first established in 1854, making it one of the oldest weather services in the world.

TidyTuesday
Data Visualization
R Programming
2025
Author

Peter Gray

Published

October 20, 2025

Chart Graph of Average Rainfall and Sunshine

Chart Graph of Average Min and Max Temp

1. R code

Show code
if (!require(tidyverse)) {
  install.packages("tidyverse")
  library(tidyverse)
}
if (!require(patchwork)) {
  install.packages("patchwork")
  library(patchwork)
}
if (!require(ggrepel)) {
  install.packages("ggrepel")
  library(ggrepel)
}
# Read data
historic_station_met <- readr::read_csv(
  'https://raw.githubusercontent.com/rfordatascience/tidytuesday/main/data/2025/2025-10-21/historic_station_met.csv'
)
station_meta <- readr::read_csv(
  'https://raw.githubusercontent.com/rfordatascience/tidytuesday/main/data/2025/2025-10-21/station_meta.csv'
)


welsh_stations <- c("aberporth", "cardiff", "cwmystwyth", "valley")

welsh_data <- historic_station_met |>
  filter(station %in% welsh_stations)

welsh_data_2024 <- welsh_data %>%
  mutate(month = month.name[as.integer(month)]) %>%
  filter(year == 2024) |>
  mutate(month = factor(month, levels = month.name))


mean_sunshine <- welsh_data_2024 |>
  group_by(month) |>
  summarise(mean_sunshine = mean(sun, na.rm = T)) |>
  mutate(angle = (as.numeric(month) - 0.5) / 12 * 360)

mean_rain <- welsh_data_2024 |>
  group_by(month) |>
  summarise(mean_rain = mean(rain, na.rm = T)) |>
  mutate(angle = (as.numeric(month) - 0.5) / 12 * 360)

mean_max_temp <- welsh_data_2024 |>
  group_by(month) |>
  summarise(mean_max_temp = mean(tmax, na.rm = T))

mean_min_temp <- welsh_data_2024 |>
  group_by(month) |>
  summarise(mean_min_temp = mean(tmin, na.rm = T))


##### Graphs

max_r <- max(mean_sunshine$mean_sunshine) + 5

sunshine <- ggplot(
  mean_sunshine,
  aes(x = month, y = mean_sunshine, fill = mean_sunshine)
) +
  geom_bar(stat = "identity", width = 1, color = "gold") +
  geom_label_repel(
    aes(
      label = paste0(round(mean_sunshine, 1), " hrs"),
      y = mean_sunshine + 30
    ),
    size = 3.5,
    color = "black"
  ) +
  coord_polar(start = 0) + # makes it circular
  annotate("point", x = 0, y = 0, size = 15, color = "gold") + # sun core
  scale_fill_gradient(low = "yellow", high = "orange") +
  theme_minimal() +
  theme(
    axis.text.y = element_blank(),
    axis.ticks = element_blank(),
    axis.title = element_blank(),
    panel.grid = element_blank(),
    legend.position = "bottom",
    axis.text.x = element_text(size = 12, face = "bold"),
    title = element_text(size = 12, face = "bold")
  ) +
  labs(
    fill = "Mean Sunshine (hrs)",
    title = "Average Monthly Hours of Sunshine in Wales in 2024"
  )




#######################=== Rain

rain <- ggplot(mean_rain, aes(x = month, y = mean_rain, fill = mean_rain)) +
  geom_bar(stat = "identity", width = 1, color = "lightgrey") +
  geom_label_repel(
    aes(
      label = paste0(round(mean_rain, 1), " mm"),
      y = mean_rain + 30
    ),
    size = 5,
    color = "white"
  ) +
  coord_polar(start = 0) + # makes it circular
  # annotate("point", x = 0, y = 0, size = 15, color = "#2E5984") +  # sun core
  scale_fill_gradient(low = "#BCD2E8", high = "#1C6CCC") +
  theme_minimal() +
  theme(
    axis.text.y = element_blank(),
    axis.ticks = element_blank(),
    axis.title = element_blank(),
    panel.grid = element_blank(),
    legend.position = "bottom",
    axis.text.x = element_text(size = 12, face = "bold"),
    title = element_text(size = 12, face = "bold")
  ) +
  labs(
    fill = "Average Monthly Rainfall (mm)",
    title = "Average Monthly Rainfall in Wales in 2024"
  )



######## = Average Max Temperature

maxtemp <- ggplot(
  mean_max_temp,
  aes(x = month, y = mean_max_temp, fill = mean_max_temp)
) +
  geom_bar(stat = "identity", width = 1, color = "lightgrey") +
  geom_label_repel(
    aes(
      label = paste0(round(mean_max_temp, 1), " °C"),
      y = mean_max_temp + 5
    ),
    size = 5,
    color = "black"
  ) +
  coord_polar(start = 0) + # makes it circular
  # annotate("point", x = 0, y = 0, size = 15, color = "#2E5984") +  # sun core
  scale_fill_gradient(low = "#c4d7ff", high = "#ff3800") +
  theme_minimal() +
  theme(
    axis.text.y = element_blank(),
    axis.ticks = element_blank(),
    axis.title = element_blank(),
    panel.grid = element_blank(),
    legend.position = "bottom",
    axis.text.x = element_text(size = 12, face = "bold"),
    title = element_text(size = 12, face = "bold")
  ) +
  labs(
    fill = "Average Maximum Temperature (°C)",
    title = "Average Maximum Monthly Temperature in Wales in 2024"
  )



######## = Average min Temperature

mintemp <- ggplot(
  mean_min_temp,
  aes(x = month, y = mean_min_temp, fill = mean_min_temp)
) +
  geom_bar(stat = "identity", width = 1, color = "lightgrey") +
  geom_label_repel(
    aes(
      label = paste0(round(mean_min_temp, 1), " °C"),
      y = mean_min_temp + 5
    ),
    size = 5,
    color = "black"
  ) +
  coord_polar(start = 0) + # makes it circular
  # annotate("point", x = 0, y = 0, size = 15, color = "#2E5984") +  # sun core
  scale_fill_gradient(low = "#c4d7ff", high = "#eeea04ff") +
  theme_minimal() +
  theme(
    axis.text.y = element_blank(),
    axis.ticks = element_blank(),
    axis.title = element_blank(),
    panel.grid = element_blank(),
    legend.position = "bottom",
    axis.text.x = element_text(size = 12, face = "bold"),
    title = element_text(size = 12, face = "bold")
  ) +
  labs(
    fill = "Average Minimum Temperature (°C)",
    title = "Average Minimum Monthly Temperature in Wales in 2024"
  )



plots <- (sunshine + rain) 



plots2 <- (mintemp + maxtemp)
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