Tokyo's historical summer temperature (heatmap) - original from Toyo Keizai Online

tokyo_summer_temperature_heatmap.r

library(ggplot2)
library(dplyr)
library(tidyr)
library(purrr)
library(jsonlite)
library(lubridate)
library(magrittr)
library(scales)
library(stringr)
library(extrafont)
# loadfonts()

# download the provided .json data from the original Toyo Keizai Online link (https://toyokeizai.net/sp/visual/tko/temperature/)
# then read it into R with the jsonlite package.
tokyo_his_temp <- jsonlite::read_json("data/temperature.json", simplifyVector = TRUE)

# mold it into a dataframe...
tokyo_weather_df <- tokyo_his_temp %>% 
  set_names(nm = 1876:2018) %>% 
  map(~as.data.frame(.) %>% 
        modify_if(., is.factor, as.character) %>% 
        modify_if(., is.character, as.numeric)) %>% 
  map2_df(., names(.), ~ mutate(., ID = .y)) %>% 
  rename(avg_temp = ".",
         year = ID)

# separate 2018 as data only up to 7/17    >>> i end up just not showing the 2018 data in the final viz.
tokyo_weather_df_2018 <- tokyo_weather_df %>% 
  filter(year == 2018) %>% 
  mutate(
    date = seq.Date(from = as.Date("2018-06-01"), 
                    by = "day",
                    length = 47),
    date = format(date, "%m/%d")
  ) 
  
# rest of the years, then combine back
tokyo_weather_df <- tokyo_weather_df %>% 
  filter(year != 2018) %>% 
  group_by(year) %>% 
  mutate(
    date = seq.Date(from = as.Date("1876-06-01"), 
                    by = "day",
                    length = 122),
    date = format(date, "%m/%d")
  ) %>% 
  ungroup() %>% 
  full_join(tokyo_weather_df_2018) %>% 
  mutate(year = as.numeric(year))


# used diverging 8-class palette from colorbrewer2.org
cols <- rev(c('#d53e4f','#f46d43','#fdae61','#fee08b','#e6f598','#abdda4','#66c2a5','#3288bd'))

labels <- c("10", "12", "14", "16", "18", "20", "22", "24", "26", "28", "30", "32")

breaks <- c(seq(10, 32, by = 2))

y_labs <- seq(1880, 2015, by = 10)
# plot!

tokyo_weather_df %>% 
  ggplot(aes(x = date, y = year, fill = avg_temp)) +
  geom_tile() +
  scale_fill_gradientn(
    colours = cols,
    labels = labels,
    breaks = breaks,
    limits = c(11, max(tokyo_weather_df$avg_temp))) +
  guides(fill = guide_colorbar(title = expression("Temperature " ( degree~C)),
                                reverse = FALSE,
                                title.position = "left",
                                label.position = "bottom",
                                nrow = 1)) +
  scale_y_reverse(limits = c(2017, 1876), expand = c(0, 0),
                  breaks = c(1876, seq(1880, 2015, by = 10), 2017)) +
  scale_x_discrete(breaks = c("06/01", "07/01", "08/01", "09/01", "09/30"),
                     labels = c("June 1st", "July 1st", "Aug. 1st", 
                                "Sept. 1st", "Sept. 30th")) +
  labs(title = "Summers in Tokyo are Getting Longer and Hotter (1876-2017)",
       subtitle = glue::glue("
          One Row = One Year, From June 1st to September 30th
          Average Temperature (Celsius)
          "),
       caption = "Data from Toyo Keizai News via Japan Meteorological Agency") +
  theme_minimal() +
  theme(text = element_text(family = "Roboto Condensed", size = 12),
        axis.title = element_blank(),
        panel.grid = element_blank(),
        legend.position = "bottom",
        legend.key.width = unit(3, "cm"),
        plot.margin=unit(c(1,1,1.5,1.2),"cm"))

# save it on your computer
ggsave("tokyo_summer_temp_eng.png", plot = last_plot())