I am new to ggplot so bear with me. I am charting out growth projections for 35 small-area geographies which is an unhealthy amount for one plot even with use of the fantastic directlabels
library. However I need all the series for initial screening.
The challenge is to make it readable. I found a fix by @Ben Bolker for using large numbers of distinct colors but am having trouble varying the linetype. The 35 series don't need to be unique, but I would like to use the 12 different types to make individual series easier to read.
My plan was to create a random list with 35 elements of the 12 possible types and pass that as the linetype argument, but I am having trouble getting it to work, with the error:
Error: Aesthetics must either be length one, or the same length as the dataProblems:lty
I have 35 values in the linetype list. Of course I would like for the types, colors and all to be reflected in the legend.
The melted data looks like this; 9 years' observations for each of 35 series:
> simulation_long_index[16:24,]
year geography value
16 2018 sfr_2 101.1871
17 2019 sfr_2 101.1678
18 2020 sfr_2 101.2044
19 2012 sfr_3 100.0000
20 2013 sfr_3 100.1038
21 2014 sfr_3 100.2561
22 2015 sfr_3 100.0631
23 2016 sfr_3 100.8071
24 2017 sfr_3 101.2405
Here is my code so far:
lty <- data.frame(lty=letters[1:12][sample(1:12, 35,replace=T)])
g3<-ggplot(data=simulation_long_index,
aes(
x=as.factor(year),
y=value,
colour=geography,
group=geography,
linetype=lty$lty))+
geom_line(size=.65) +
scale_colour_manual(values=manyColors(35)) +
geom_point(size=2.5) +
opts(title="growth")+
xlab("Year") +
ylab(paste("Indexed Value (Rel. to 2012")) +
opts(axis.text.x=theme_text(angle=90, hjust=0))
print(g3)
adding
scale_linetype_manual("",values=lty$lty) +
after scale_color_manual instead of the linetype argument produces the chart, but lines are all the same. How, then, do I get the lines to vary for large series counts?
Change manually the appearance of lines The functions below can be used : scale_linetype_manual() : to change line types. scale_color_manual() : to change line colors. scale_size_manual() : to change the size of lines.
To change line width, just add argument size=2 to geom_line().
The trick with using scale_..._manual
is often to send a named vector as the value
argument. The setNames
function is good for this
First, some dummy data
## some dummy data
simulations<- expand.grid(year = 2012:2020, geography = paste0('a',1:35))
library(plyr)
library(RColorBrewer)
simulation_long_index <- ddply(simulations, .(geography), mutate,
value = (year-2012) * runif(1,-2, 2) + rnorm(9, mean = 0, sd = runif(1, 1, 3)))
## create a manyColors function
manyColors <- colorRampPalette(brewer.pal(name = 'Set3',n=11))
Next we create a vector that is a random sample from 1:12 (with replacement) and set the names the same as the geography
variable
lty <- setNames(sample(1:12,35,T), levels(simulation_long_index$geography))
This is what it looks like
lty
## a1 a2 a3 a4 a5 a6 a7 a8 a9 a10 a11 a12 a13 a14 a15 a16
## 7 5 8 11 2 10 3 2 5 4 6 6 11 8 2 2
## a17 a18 a19 a20 a21 a22 a23 a24 a25 a26 a27 a28 a29 a30 a31 a32
## 12 7 6 8 11 5 1 1 8 12 8 1 12 2 3 5
## a33 a34 a35
#7 1 3
Now you can use line_type = geography
in conjunction with scale_linetype_manual(values = lty)
ggplot(data=simulation_long_index,
aes(
x=as.factor(year),
y=value,
colour=geography,
group=geography,
linetype = geography))+
geom_line(size=.65) +
scale_colour_manual(values=manyColors(35)) +
geom_point(size=2.5) +
opts(title="growth")+
xlab("Year") +
ylab(paste("Indexed Value (Rel. to 2012")) +
opts(axis.text.x=theme_text(angle=90, hjust=0)) +
scale_linetype_manual(values = lty)
Which gives you
As an aside, do you really want to plot the years as a factor variable?
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