I am fairly certain I have seen a solution for this somewhere, but as I have been unable to find it, here is my problem.
I have some time series data identified by multiple variables, I would like to be able to graph and differentiate color using multiple variables in ggplot2
.
Sample data:
date <- c("2016-04-01 UTC", "2016-05-01 UTC", "2016-06-01 UTC", "2016-04-01 UTC",
"2016-05-01 UTC", "2016-06-01 UTC", "2016-04-01 UTC", "2016-05-01 UTC",
"2016-06-01 UTC", "2016-04-01 UTC")
temp <- c(80.24018, 85.88911, 104.23125, 85.13571, 91.21129, 104.88333, 97.81116,
107.40484, 121.03958, 87.91830)
id <- c("A","A","A","A","A","B","B","B","B","B")
location <- c("N","S","S","N","N","S","N","S","N","S")
df <- data.frame(date,temp,id,location)
My attempt at graphing
library(ggplot2)
ggplot(df) +
geom_line(aes(x=date,y=temp,colour=factor(location), group=interaction(location,id)))
Using this code it is only coloring by location. I would like to the lines to be colored by location and id.
Two options:
library(ggplot2)
df <- data.frame(date = c("2016-04-01 UTC", "2016-05-01 UTC", "2016-06-01 UTC", "2016-04-01 UTC", "2016-05-01 UTC", "2016-06-01 UTC", "2016-04-01 UTC", "2016-05-01 UTC", "2016-06-01 UTC", "2016-04-01 UTC"),
temp = c(80.24018, 85.88911, 104.23125, 85.13571, 91.21129, 104.88333, 97.81116, 107.40484, 121.03958, 87.91830),
id = c("A","A","A","A","A","B","B","B","B","B"),
location = c("N","S","S","N","N","S","N","S","N","S"))
df$date <- as.Date(df$date) # parse dates to get a nicer x-axis
Map id
to color and location
to linetype:
ggplot(df, aes(date, temp, color = id, linetype = location)) + geom_path()
...or plot all interactions as different colors:
ggplot(df, aes(date, temp, color = id:location)) + geom_path()
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