Reputation: 1361
I have the following dataset:
Data <- data.frame(
week = c(1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4),
variable = c("nuclear", "nuclear", "nuclear", "nuclear", "atomic", "atomic", "atomic", "atomic", "unemployment", "unemployment", "unemployment", "unemployment"),
value = c(2, 3, 1, 4, 5, 1, 2, 3, 3, 2, 5, 1)
)
I need a black-white-graph. So I use the following code:
ggplot(Data, aes(week, value, group=variable)) + xlab("Year") + ylab("Frequency of searches") +
geom_line(aes(linetype=variable))+ # Line type depends on cond
geom_point(aes(shape=variable))+ # Shape depends on cond
scale_shape_manual(values=c(0,1,2)) + # Change shapes
scale_linetype_manual(values=c("solid", "dotted", "dotdash"))+
theme(legend.position="top", legend.title=element_blank(), panel.background = element_rect(fill = "#FFFFFF", colour="#000000"))+
stat_smooth(method="loess"))
That works for fine for this small dataset. But when it's bigger, it's difficult to distinguish the lines and points from each other. It all looks very similar. Is there a way to plot only every second or tenth data point?
Upvotes: 2
Views: 7322
Reputation: 42679
Here's a way to take the even rows, relying on recycling of the index vector:
Data[c(FALSE,TRUE),]
And every 10th:
Data[c(rep(FALSE, 9), TRUE),]
Upvotes: 1
Reputation: 54247
Subset Data
using seq()
:
Data[seq(1, nrow(Data), 4), ] # every 4th row
Data[seq(1, nrow(Data), 2), ] # every 2nd row
# ...
Upvotes: 7
Reputation: 1878
You can override the data for geom_point
with a subset:
geom_point(aes(shape=variable), data=subset(Data, week %% 2 == 1))
Upvotes: 7