Interactive and Dynamic Animation

In this R Notebook we will try out some interactive visualizations and some dynamic visualizations that are possible using R.

library(pacman)
p_load(tidyverse, purrr, gapminder, plotly, trelliscopejs, echarts4r, echarts4r.assets, gganimate)

Using the gapminder dataset.

gapminder

Plot by continent.

gapm <- gapminder %>% group_by(continent, country) %>%
  ggplot(aes(x = gdpPercap, y = lifeExp, 
             size = pop, colour = country )) +
  geom_point() +
  scale_x_log10() + 
  facet_wrap(~continent) +
  theme(legend.position = "none")
gapm

ggplotly(gapm)

`group_by_()` is deprecated as of dplyr 0.7.0.
Please use `group_by()` instead.
See vignette('programming') for more help
This warning is displayed once every 8 hours.
Call `lifecycle::last_warnings()` to see where this warning was generated.

Using facet_trelliscope can be used to create an interactive collection of plots. Can you image making a million plots?

gapminder %>% ggplot(aes(x = log10(gdpPercap), y = lifeExp, 
                         color = country, size = pop)) +  
  geom_point() + 
  theme_bw() +
  theme(legend.position = "none") +
  facet_trelliscope(~ continent, 
                    nrow = 2, ncol = 3)

using data from the first layer

gapm_trel <- gapminder %>% 
  ggplot(aes(x = log10(gdpPercap), y = lifeExp,
             color = country, size = pop)) +
  geom_point() +
  theme_bw() +
  theme(legend.position = "none") +
  facet_trelliscope(~ country + continent, 
                    nrow = 2, ncol = 3) 

gapm_trel

using data from the first layer

Try echarts.

titles <- map(unique(gapminder$year), function(x){
  list(
    text = "Gapminder",
    subtext = x,
    left = "center"
  )
})

gapminder %>% 
  group_by(year) %>% 
  e_charts(gdpPercap, timeline = TRUE) %>% 
  e_scatter(lifeExp, pop, country) %>% 
  e_y_axis(min = 20, max = 85) %>% 
  e_x_axis(type = "log", min = 100, max = 100000) %>% 
  e_timeline_serie(title = titles) %>% 
  e_tooltip() %>% 
  e_timeline_opts(
    show = TRUE,
    orient = "vertical",
    symbol = "none",
    right = 0,
    top = 20,
    bottom = 20,
    height = NULL,
    width = 45,
    inverse = TRUE,
    playInterval = 1000,
    autoPlay  = TRUE,
    controlStyle = list(
      showNextBtn = FALSE,
      showPrevBtn = FALSE
    ),
    label = list(
      fontSize = 8
    )
  ) %>% 
  e_theme("dark")

gapminder %>% ggplot(aes(x = gdpPercap, y = lifeExp, 
                         size = pop, colour = country)) +
  geom_point(alpha = 0.7, show.legend = FALSE) +
  scale_colour_manual(values = country_colors) +
  scale_size(range = c(2, 12)) +
  scale_x_log10() +
  facet_wrap(~ continent)

Try gganimate.

gapminder %>% ggplot(aes(x = gdpPercap, y = lifeExp, 
                         size = pop, colour = country)) +
  geom_point(alpha = 0.7, show.legend = FALSE) +
  scale_colour_manual(values = country_colors) +
  scale_size(range = c(2, 12)) +
  scale_x_log10() +
  facet_wrap(~ continent) +
  # Here comes the gganimate specific bits
  labs(title = 'Year: {frame_time}', 
       x = 'GDP per capita', y = 'life expectancy') +
  transition_time(year) +
  ease_aes('cubic-in-out')

goo <- gapminder %>% ggplot(aes(x = gdpPercap, y = lifeExp, 
                         size = pop, colour = country)) +
  geom_point(alpha = 0.7, show.legend = FALSE) +
  scale_colour_manual(values = country_colors) +
  scale_size(range = c(2, 12)) +
  scale_x_log10() +
  facet_wrap(~continent) +
  # Here comes the gganimate specific bits
  labs(title = 'Year: {frame_time}', 
       x = 'GDP per capita', y = 'life expectancy') +
  transition_time(year) +
  ease_aes('cubic-in-out')

anim_save("goo.gif", goo)

Try echarts.

airports <- read.csv(
  paste0("https://raw.githubusercontent.com/plotly/datasets/",
         "master/2011_february_us_airport_traffic.csv")
)

airports %>% 
  e_charts(long) %>% 
  e_globe(
    environment = ea_asset("starfield"),
    base_texture = ea_asset("world"), 
    globeOuterRadius = 100
  ) %>% 
  e_scatter_3d(lat, cnt, coord_system = "globe", blendMode = 'lighter') %>% 
  e_visual_map(inRange = list(symbolSize = c(1, 10)))

# download
flights <- jsonlite::fromJSON("https://raw.githubusercontent.com/apache/incubator-echarts/master/test/data/flight.json")



# airports
airports <- as.data.frame(flights$airports)
names(airports) <- flights$airportsFields

airports <- airports %>% 
  select(name, longitude, latitude) %>% 
  tibble::rownames_to_column("ID") %>% 
  mutate(ID = as.integer(paste0(ID)))

# routes
routes <- as.data.frame(flights$routes)
names(routes) <- c("ID", "from", "to")

# airlines
airlines <- as.data.frame(flights$airlines) %>% 
  tibble::rownames_to_column("ID") %>% 
  mutate(ID = as.integer(paste(ID))) %>% 
  select(ID, airline = V1, country = V2) %>%
  filter(country == "United States")

# bind
data <- routes %>% 
  inner_join(airports, by = c("from" = "ID")) %>% 
  inner_join(airports, by = c("to" = "ID"), suffix = c(".start", ".end")) %>%
  inner_join(airlines, by = "ID") %>% 
  select(airline, longitude.start, latitude.start, longitude.end, latitude.end) 

# initialise plot  
data %>%
  group_by(airline) %>% 
  e_charts() %>% 
  e_globe(
    base_texture = ea_asset("world dark"),
    environment = ea_asset("starfield"),
    displacementScale = 0.1,
    displacementQuality = "high",
    shading = "realistic",
    realisticMaterial = list(
      roughness = .2,
      metalness = 0
    ),
    postEffect = list(
      enable = TRUE,
      depthOfField = list(
        enable = FALSE
      )
    ),
    temporalSuperSampling = list(
      enable = TRUE
    ),
    light = list(
      ambient = list(
        intensity = 1
      ),
      main = list(
        intensity = .1,
        shadow = FALSE
      )
    ),
    viewControl = list(autoRotate = FALSE)
  ) %>% 
  e_legend(
    selectedMode = "single", 
    left = "left",
    textStyle = list(color = "#fff"),
    orient = "vertical"
  ) %>% 
  e_lines_3d(
    longitude.start, latitude.start, longitude.end, latitude.end, 
    coord_system = "globe", 
    effect = list(
      show = TRUE,
      trailWidth = 2,
      trailLength = 0.15,
      trailOpacity = 1,
      trailColor = 'rgb(30, 30, 60)'
    ),
    lineStyle = list(opacity = 0.1, widh = 0.5, color = 'rgb(50, 50, 150)')
  )

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