http://www.spiegel.de/wissenschaft/natur/bild-1119424-1067142.html

http://www.spiegel.de/wissenschaft/natur/bild-1119539-1067290.html

Today's goal: building a final plot

1. Axis transformation

2. Labeling

3. Annotation & other geometric shapes

4. Animation & Interactivity

5. Saving

library(gapminder); library(dplyr); library(ggplot2)
gapminder %>% 
  head(3)

## # A tibble: 3 × 6
##       country continent  year lifeExp      pop gdpPercap
##        <fctr>    <fctr> <int>   <dbl>    <int>     <dbl>
## 1 Afghanistan      Asia  1952  28.801  8425333  779.4453
## 2 Afghanistan      Asia  1957  30.332  9240934  820.8530
## 3 Afghanistan      Asia  1962  31.997 10267083  853.1007

Ultimate goal: How does life expectency vary based on gdp per capita?

p <- ggplot(gapminder, aes(gdpPercap, lifeExp)) +
  geom_point() 
p

p <- ggplot(gapminder, aes(gdpPercap, lifeExp, 
                size = pop, color = continent)) +
  geom_point() 
p

p <- ggplot(gapminder, aes(gdpPercap, lifeExp, 
                 size = pop, color = continent)) +
  geom_point() +
  scale_x_log10() 
p

gapminder1 <- gapminder %>%
   mutate(gdp.log10 = log(gdpPercap, 10))
set.seed(5)
gapminder1 %>% arrange(gdpPercap) %>% sample_n(2)

## # A tibble: 2 × 7
##   country continent  year lifeExp       pop gdpPercap gdp.log10
##    <fctr>    <fctr> <int>   <dbl>     <int>     <dbl>     <dbl>
## 1   India      Asia  1987  58.553 788000000  976.5127  2.989678
## 2 Jamaica  Americas  1997  72.262   2531311 7121.9247  3.852597

gapminder2 <- gapminder1 %>%
     filter(year == 2007, continent == "Asia")
p <- ggplot(gapminder2, aes(gdpPercap, lifeExp)) +
  geom_point(aes(size = pop)) +
  scale_x_log10() 
p

p + geom_text(aes(label = country))

library(ggrepel)
p + geom_text_repel(aes(label = country))

p + geom_label_repel(aes(label = country))

p1 <- p + geom_label_repel(data = filter(gapminder2, 
          lifeExp < 50 | lifeExp >80| pop > 10^9),
          aes(label = country), 
    box.padding = unit(0.35, "lines"),
    point.padding = unit(0.5, "lines"),
    segment.color = 'red')

p1

p1 + geom_text(aes(x = 2000, y = 50), label = "Low GDP, life exp.", 
               colour = "red") + 
  geom_text(aes(x = 20000, y = 70), label = "High GDP, life exp.", 
            colour = "red")

1. Segments
2. Arrows
3. Pictures
4. What else?

Steps to animation (Mac.. PC?)

1. Install macports at macports.org
2. Command line: sudo port install ImageMagick
3. Install gganimate package

library(gganimate)
library(gapminder)
library(ggplot2)
theme_set(theme_bw())

p <- ggplot(gapminder, aes(gdpPercap, lifeExp, size = pop, 
                           color = continent, frame = year)) +
  geom_point() +
  scale_x_log10()

#gg_animate(p)

library(plotly)
dsamp <- sample_n(diamonds, 1000)
ggplot(dsamp, aes(carat, price, colour=clarity)) + 
  geom_point()

Shootouts in the NHL

#ggsave(p1, file = "gapminder.pdf", width = 6, height = 5)
#ggsave(p1, file = "gapminder.png", width = 6, height = 5)