global_temps.R

# Load required packages
library(tidyverse)
library(gridExtra)
library(showtext)
library(grid)

# Read the global temperature data from CSV file
global_temps <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2023/2023-07-11/global_temps.csv')

# Add custom font and enable automatic text rendering
font_add_google("Lato", "my_lato")
showtext_auto()

# Perform data transformations and create the temperature plot
temp <- global_temps %>% 
  select(Year:Dec) %>% 
  rowwise() %>%
  mutate(min_value = min(c_across(Jan:Dec), na.rm = TRUE), 
         max_value = max(c_across(Jan:Dec), na.rm = TRUE),
         mean_value = mean(c_across(Jan:Dec), na.rm = TRUE)) %>% 
  select(1, min_value, max_value, mean_value) %>% 
  pivot_longer(!Year) %>% 
  filter(Year > 1986) %>% 
  ggplot() +
  geom_line(aes(x = value, y = Year, group = Year), color = "#333333") +
  geom_point(aes(x = value, y = Year, color = name), size = 3) +
  scale_color_manual(
    values = c(min_value = "#00798c", mean_value = "#e3d5d5", max_value = "#d1495b"),
    breaks = c("min_value", "mean_value", "max_value"),
    labels = c("min Temp", "mean Temp", "max Temp"),
    name = ""
  ) +
  scale_y_continuous(breaks = seq(1987, 2023, by = 5)) +
  guides(alpha = "none") +
  scale_x_continuous(
    breaks = seq(0, 1.50, 0.25),
    limits = c(-0.1, 1.50)
  ) +
  coord_cartesian(
    xlim = c(0, 1.6),
    ylim = c(1986, 2024),
    expand = FALSE,
    clip = 'off'
  ) +
  annotate(
    'segment', x = 0, xend = 1.5,
    y = 1986,
    yend = 1986,
    col = "#333333",
    size = 0.25
  ) +
  labs(
    x = "Temperature (°C)", y = "Year",
    title = "Riding the Thermal Waves: A Journey from 1987 to Today",
    subtitle = "Depicting changes in global temperatures over time: Minimum, Mean, and Maximum\nvalues from 1987 onwards"
  ) +
  theme_minimal() +
  theme(
    text = element_text(family = "my_lato", color = "#333333"),
    panel.grid.major.y = element_blank(),
    panel.grid.minor.y = element_blank(),
    panel.grid.major.x = element_blank(),
    panel.grid.minor.x = element_blank(),
    plot.title = element_text(hjust = 0.5, margin = margin(10, 0, 0, 0), size = 15),
    plot.subtitle = element_text(family = "my_lato", size = 11, color = "#333333", hjust = 0.5),
    legend.position = "bottom",
    axis.title.x = element_text(size = 13, margin = margin(10, 0, 0, 0)),
    axis.text.x = element_text(size = 12),
    axis.ticks.x = element_line(color = "#333333", size = 0.3),
    axis.ticks.length = unit(.2, "cm"),
    axis.line.x = element_blank(),
    axis.title.y = element_text(size = 13, margin = margin(0, 10, 0, 0)),
    axis.text.y = element_text(size = 12)
  )

# Display the temperature plot
temp

# Add a rectangle grob for additional styling
rect_grob <- rectGrob(
  width = 0.01,
  height = 0.08,
  gp = gpar(fill = "#d1495b", col = "transparent")
)

# Draw the rectangle grob on the plot
grid.draw(grobTree(rect_grob, vp = viewport(x = 0.1, y = 0.93)))