ggplot2 : geom_line()

time series

geom_line() is suitable for time series

> economics
# A tibble: 574 x 6
   date         pce    pop psavert uempmed unemploy
   <date>     <dbl>  <dbl>   <dbl>   <dbl>    <dbl>
 1 1967-07-01  507. 198712    12.6     4.5     2944
 2 1967-08-01  510. 198911    12.6     4.7     2945
 3 1967-09-01  516. 199113    11.9     4.6     2958
 4 1967-10-01  512. 199311    12.9     4.9     3143
 5 1967-11-01  517. 199498    12.8     4.7     3066
 6 1967-12-01  525. 199657    11.8     4.8     3018
 7 1968-01-01  531. 199808    11.7     5.1     2878
 8 1968-02-01  534. 199920    12.3     4.5     3001
 9 1968-03-01  544. 200056    11.7     4.1     2877
10 1968-04-01  544  200208    12.3     4.6     2709
# ... with 564 more rows

> economics_long
# A tibble: 2,870 x 4
   date       variable value  value01
   <date>     <chr>    <dbl>    <dbl>
 1 1967-07-01 pce       507. 0       
 2 1967-08-01 pce       510. 0.000265
 3 1967-09-01 pce       516. 0.000762
 4 1967-10-01 pce       512. 0.000471
 5 1967-11-01 pce       517. 0.000916
 6 1967-12-01 pce       525. 0.00157 
 7 1968-01-01 pce       531. 0.00207 
 8 1968-02-01 pce       534. 0.00230 
 9 1968-03-01 pce       544. 0.00322 
10 1968-04-01 pce       544  0.00319 
# ... with 2,860 more rows

ggplot(economics, aes(date, unemploy)) + geom_line()
ggplot(economics_long, aes(date, value01, colour = variable)) +
  geom_line()

geom_step()

geom_step() is useful when you want to highlight exactly when the y value changes

recent <- economics[economics$date > as.Date("2013-01-01"), ]
ggplot(recent, aes(date, unemploy)) + geom_line()
ggplot(recent, aes(date, unemploy)) + geom_step()

geom_path()

geom_path lets you explore how two variables are related over time, e.g. unemployment and personal savings rate

m <- ggplot(economics, aes(unemploy/pop, psavert))
m + geom_path()
m + geom_path(aes(colour = as.numeric(date)))

Changing parameters ----------------------------------------------

ggplot(economics, aes(date, unemploy)) +
  geom_line(colour = "red")

Control line join parameters

df <- data.frame(x = 1:3, y = c(4, 1, 9))
base <- ggplot(df, aes(x, y))
base + geom_path(size = 10)
base + geom_path(size = 10, lineend = "round")
base + geom_path(size = 10, linejoin = "mitre", lineend = "butt")

Break line

You can use NAs to break the line.

df <- data.frame(x = 1:5, y = c(1, 2, NA, 4, 5))
ggplot(df, aes(x, y)) + geom_point() + geom_line()

Setting line type vs colour/size

Line type needs to be applied to a line as a whole, so it can
not be used with colour or size that vary across a line

x <- seq(0.01, .99, length.out = 100)
df <- data.frame(
  x = rep(x, 2),
  y = c(qlogis(x), 2 * qlogis(x)),
  group = rep(c("a","b"),
              each = 100)
)
p <- ggplot(df, aes(x=x, y=y, group=group))
# These work
p + geom_line(linetype = 2)
p + geom_line(aes(colour = group), linetype = 2)
p + geom_line(aes(colour = x))
# But this doesn't
should_stop(p + geom_line(aes(colour = x), linetype=2))