Big Mac Index (Tidy Tuesday 2020-12-22)

###################################################################################################
# Big Mac Index - Change in price of the McDonald's Big Mac burger from 2000 to 2020
# Created by: reddit.com/user/brianhaas19

# Link to data
# https://github.com/rfordatascience/tidytuesday/blob/master/data/2020/2020-12-22

# Setup
library(tidyverse)
library(scales)
library(patchwork)
theme_set(theme_bw())

# Load data
big_mac <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-12-22/big-mac.csv')
df <- big_mac # generic name

# Clean data
### Filter for countries with mostly complete data:
complete_data <- df %>%
  count(name) %>%
  filter(n >= 19) %>% # this leaves 42 countries
  .$name

df <- df %>%
  filter(name %in% complete_data)

# Visualize
# Suggested parameters for R notebook: fig.height=12, fig.width=9

### Colors
colors <- c("bun" = "#F7C064",
            "burger" = "#7A4E3D",
            "lettuce" = "#A0C03A",
            "sauce" = "#F5DE92",
            "cheese" = "#F9E239",
            "sesame" = "#F9F3D9",
            "red" = "#DF4458")
# Ref: https://images.app.goo.gl/3iAvxZfQ9r75CCVz6

### Plot
p1 <- df %>%
  mutate(name2 = name) %>% # use a duplicate column to allow 'highlighting' within each facet
  ggplot(aes(date, dollar_price)) +
  geom_line(data = df,
            aes(group = name),
            color = colors["sauce"],
            alpha = 0.7) +
  geom_line(color = colors["burger"]) +
  facet_wrap(~name2, nrow = 7) +
  labs(x = "Date", y = "Price in USD",
       title = expression(paste(bold("Big Mac Index"), " - Change in price of the McDonald's Big Mac burger from 2000 to 2020")),
       subtitle = "The price in USD is calculated by converting from local currency to US dollars using the appropriate exchange rate.",
       caption = expression(paste("Created by: ", italic("reddit.com/user/brianhaas19"), "\tData source: ", italic("https://github.com/rfordatascience/tidytuesday/blob/master/data/2020/2020-12-22")))) +
  scale_x_continuous(breaks = seq(min(df$date), max(df$date), length.out = 5),
                     labels = date_format("'%y")) +
  scale_y_continuous(breaks = seq(2.5, 7.5, 2.5), labels = dollar) +
  theme(plot.title = element_text(color = colors["burger"]),
        plot.subtitle = element_text(color = colors["burger"]),
        plot.caption = element_text(color = colors["burger"], hjust = 0),
        plot.background = element_rect(fill = colors["bun"]),
        panel.background = element_rect(fill = colors["bun"]),
        panel.grid.major = element_line(color = colors["lettuce"], size = 0.25, linetype = "dashed"),
        panel.grid.minor = element_blank(),
        axis.title = element_text(color = colors["burger"]),
        axis.text = element_text(color = colors["burger"]),
        strip.background = element_rect(fill = colors["red"]),
        strip.text = element_text(color = colors["cheese"]))
p1

### Uncomment to save to disk:
# ggsave(plot = p1,
#        filename = str_c(getwd(), "/big_mac_index.png"),
#        height = 12, width = 9)
###################################################################################################