XY Heatmap

library(tidyverse)    # untuk manupulasi, merapikan, & visualisasi data
library(gapminder)    # untuk mengakses gapminder dataset

xy_heatmap_df <- gapminder %>%
  mutate(year = as.factor(year)) %>%
  group_by(continent, year) %>%
  summarize(MedlifeExp = round(median(lifeExp), 0))

## `summarise()` has grouped output by 'continent'. You can override using the `.groups` argument.

xy_heatmap <- xy_heatmap_df %>%
  ggplot(aes(x = year,
             y = continent,
             fill = MedlifeExp)) +
  geom_tile(color = '#FFFFFF') +
  geom_text(aes(label = MedlifeExp),
            size = 4,
            color = '#FFFFFF') +
  scale_fill_gradient(name = 'Median Life Expectancy',
                      low = '#8a9db1',
                      high = '#094568') +
  theme_minimal() +
  theme(
    axis.title = element_blank(),
    axis.text = element_blank(),
    axis.line = element_blank(),
    panel.grid.major = element_blank(),
    panel.grid.minor = element_blank(),
    strip.text = element_blank(),
    panel.background = element_rect(fill = '#FFFFFF',
                                    color = NA),
    plot.background = element_rect(fill = '#FFFFFF',
                                   color = '#FFFFFF'),
    legend.position = 'none'
  )