Historical Phone Usage

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# Historical Phone Usage - Landline and Mobile Phone Subscriptions in Europe from 1990 to 2017
# Created by: reddit.com/user/brianhaas19

# Link to data
# https://github.com/rfordatascience/tidytuesday/tree/master/data/2020/2020-11-10

# Setup
library(tidyverse)
library(tidytuesdayR)
library(gganimate)
theme_set(theme_bw())

# Load data:
tt <- tt_load("2020-11-10")
mobile <- tt$mobile
landline <- tt$landline

# Combine and clean data
subs <- rbind(
  mutate(mobile, type = "mobile") %>% rename(subs = mobile_subs),
  mutate(landline, type = "landline") %>% rename(subs = landline_subs)
) %>%
  rename(country = entity)

# Shorten the name of Bosnia and Herzegovina:
subs$country[subs$country == "Bosnia and Herzegovina"] <- "Bosnia and Herz."

# List of European countries:
europe <- subs %>%
  filter(continent == "Europe", year <= 2017) %>% # data is mostly missing for year > 2017
  group_by(country) %>%
  mutate(has_data = !is.na(subs)) %>%
  filter(has_data) %>%
  count(has_data) %>%
  filter(!(country %in% c("Liechtenstein", "Gibraltar", "San Marino"))) # missing some data

# Visualize

## Colors:
orange <- "#F5793A"
blue <- "#0F2080"
# Ref: Color blind friendly palettes: https://venngage.com/blog/color-blind-friendly-palette/

## Static
### Recommended parameters for R notebook: fig.height=9, fig.width=9
p <- subs %>%
  filter(!is.na(subs)) %>%
  filter(continent == "Europe", country %in% europe$country) %>%
  ggplot(aes(year, subs, group = type, color = type)) +
  geom_line() +
  facet_wrap(~country, scales = "free_x") +
  labs(x = "Year", y = "Subscriptions (per 100 people)",
       title = expression(paste(bold("Historical Phone Usage"), " - Landline and Mobile Phone Subscriptions in Europe from 1990 to 2017")),
       subtitle = "Measured as the number of subscriptions per 100 people.",
       caption = expression(paste("Created by: ", italic("reddit.com/user/brianhaas19"), "\tData source: ", italic("https://github.com/rfordatascience/tidytuesday/tree/master/data/2020/2020-11-10")))) +
  scale_x_continuous(breaks = c(1990, 2000, 2010),
                     limits = c(1990, 2017)) +
  scale_color_manual("Type:",
                     breaks = c("landline", "mobile"),
                     labels = c("Landline", "Mobile"),
                     values = c(blue, orange)) +
  theme(legend.position = "top",
        plot.caption = element_text(hjust = 0))
p

### Uncomment this line to save to disk:
# ggsave(str_c(getwd(), "/mobile_landline_subs.png"),
#        plot = p, height = 9, width = 9)

## Animation
anim <- subs %>%
  filter(!is.na(subs)) %>%
  filter(continent == "Europe", country %in% europe$country) %>%
  ggplot(aes(year, subs, group = type, color = type)) +
  geom_line() +
  geom_point() +
  facet_wrap(~country, scales = "free_x") +
  labs(x = "Year", y = "Subscriptions (per 100 people)",
       title = expression(paste(bold("Historical Phone Usage"), " - Landline and Mobile Phone Subscriptions in Europe from 1990 to 2017")),
       subtitle = "Measured as the number of subscriptions per 100 people.",
       caption = expression(paste("Created by: ", italic("reddit.com/user/brianhaas19"), "\tData source: ", italic("https://github.com/rfordatascience/tidytuesday/tree/master/data/2020/2020-11-10")))) +
  scale_x_continuous(breaks = c(1990, 2000, 2010),
                     limits = c(1990, 2017)) +
  scale_color_manual("Type:",
                     breaks = c("landline", "mobile"),
                     labels = c("Landline", "Mobile"),
                     values = c(blue, orange)) +
  theme(legend.position = "top",
        plot.caption = element_text(hjust = 0)) +
  transition_reveal(year)

animate(anim,
        nframes = 120, end_pause = 20,
        height = 9, width = 9, units = "in", res = 150)

### Uncomment this line to save to disk:
# anim_save(str_c(getwd(), "/mobile_landline_subs.gif"), animation = anim)
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