I have a time series with multiple days of data. In between each day there's one period with no data points. How can I omit these periods when plotting the time series using ggplot2?
An artificial example shown as below, how can I get rid of the two periods where there's no data?
code:
Time = Sys.time()+(seq(1,100)*60+c(rep(1,100)*3600*24, rep(2, 100)*3600*24, rep(3, 100)*3600*24))
Value = rnorm(length(Time))
g <- ggplot()
g <- g + geom_line (aes(x=Time, y=Value))
g
First, create a grouping variable. Here, two groups are different if the time difference is larger than 1 minute:
Group <- c(0, cumsum(diff(Time) > 1))
Now three distinct panels could be created using facet_grid and the argument scales = "free_x":
library(ggplot2)
g <- ggplot(data.frame(Time, Value, Group)) +
geom_line (aes(x=Time, y=Value)) +
facet_grid(~ Group, scales = "free_x")
The problem is that how does ggplot2 know you have missing values? I see two options:
NA valuesAdd an additional variable representing a "group". For example,
dd = data.frame(Time, Value)
##type contains three distinct values
dd$type = factor(cumsum(c(0, as.numeric(diff(dd$Time) - 1))))
##Plot, but use the group aesthetic
ggplot(dd, aes(x=Time, y=Value)) +
geom_line (aes(group=type))
gives
csgillespie mentioned padding by NA, but a simpler method is to add one NA after each block:
Value[seq(1,length(Value)-1,by=100)]=NA
where the -1 avoids a warning.
