Question

I’m trying to understand how to have more than one series on a plot, using the following data.

Year <- c('1950', '1960', '1970', '1980')
Bus <- c(10,20,30,40)
Bus.sd <- c(1.1, 2.2, 3.3, 4.4)
Car <- c(20, 20, 40, 40)
Car.sd <- c(1.1, 2.2, 3.3, 4.4)

sample_data = data.frame(Year, Bus, Bus.sd, Car, Car.sd)

qplot(Year, Bus, data=sample_data, geom="pointrange", 
ymin = Bus - Bus.sd/2, ymax = Bus + Bus.sd/2)

For example, using the above data, how do I show both sample_data$Bus and sample_data$Car on the same plot in different colors?

What I tried doing was:

p <- qplot(...)

then

p <- p + qplot(...) 

where I replicated the previous line, but this gave me an error.

I don’t fully understand how AES works. I have studied the ggplot2 examples, but have difficulty understanding the relevant examples here. Or, if it is possible to make a stacked bar (geom_bar) using this data, I think that would also represent it appropriately.

Answer 1

I Hope this helps

gplot2 works best with data in long format, like so:

  Year score  sd variable
1 1950    10 1.1      bus
2 1960    20 2.2      bus
3 1970    30 3.3      bus
4 1980    40 4.4      bus
5 1950    20 1.1      car
6 1960    20 2.2      car
7 1970    40 3.3      car
8 1980    40 4.4      car

This will get the data into R:

data <- structure(list(Year = structure(c(1L, 2L, 3L, 4L, 1L, 2L, 3L, 
4L), class = "factor", .Label = c("1950", "1960", "1970", "1980"
)), score = c(10, 20, 30, 40, 20, 20, 40, 40), sd = c(1.1, 2.2, 
3.3, 4.4, 1.1, 2.2, 3.3, 4.4), variable = c("bus", "bus", "bus", 
"bus", "car", "car", "car", "car")), .Names = c("Year", "score", 
"sd", "variable"), row.names = c(NA, -8L), class = "data.frame")

And this will make the plot, with dodge an all. You properbly need the dodge, because your data is overlapping. You can control the amount of dodging with the “W” value.

ggplot(data, aes(x=Year, y=score,col=variable))+
geom_point(position=position_dodge(w=0.2))+
geom_pointrange(aes(ymin=score-sd, ymax=score+sd,group=Year),position=position_dodge(w=0.2))