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I've looked around a fair bit but I am stumped on this one. I cannot find a way to plot a line that is unassociated with a scatterplot. Here is some of my data and code to clarify the problem. I have data of the following form
> head(allData)
AnnounceDate MarketProbability DealStatus binary BrierScore
1 2000-04-10 0.3333333 Complete 1 0.2340565
2 2000-06-14 0.2142857 Complete 1 0.3618200
3 2000-06-26 0.6846154 Complete 1 0.3690167
4 2000-06-16 0.1875000 Complete 1 0.4364041
5 2000-10-05 0.9555556 Complete 1 0.3078432
6 2000-10-19 0.8500000 Complete 1 0.2670799
I would like to create a scatter plot of the MarketProbabilities vs. the AnnounceDate, and identify whether a DealStatus is Completed or Terminated using colour.
(ggplot(data=allData, aes(x=AnnounceDate, y=MarketProbability, colour=DealStatus))
+ geom_point() + scale_colour_hue(h = c(180,0)))
I would also like to overlay a rolling Brier score, I have tried
(ggplot(data=allData, aes(x=AnnounceDate, y=MarketProbability, colour=DealStatus))
+ geom_point() + scale_colour_hue(h=c(180,0))
+ geom_line(aes(x=AnnounceDate, y=BrierScore)))
I am confused why two coloured lines are plotted? How do I dissociate the line with the previous plotted data?
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A scatter plot can be created using the function plot(x, y). The function lm() will be used to fit linear models between y and x. A regression line will be added on the plot using the function abline(), which takes the output of lm() as an argument. You can also add a smoothing line using the function loess().
To overlay a line plot in the R language, we use the lines() function. The lines() function is a generic function that overlays a line plot by taking coordinates from a data frame and joining the corresponding points with line segments.
One of the easiest methods to add a regression line to a scatter plot with ggplot2 is to use geom_smooth(), by adding it as additional later to the scatter plot. To make a linear regression line, we specify the method to use to be “lm”.
%>% is a pipe operator reexported from the magrittr package. Start by reading the vignette. Adding things to a ggplot changes the object that gets created. The print method of ggplot draws an appropriate plot depending upon the contents of the variable.
As @MattBagg has pointed out, this issue is fixed by moving the aes() for colour out of the main ggplot() call and into the geom_point() call.
library(ggplot2)
allData = read.table(header=TRUE,
colClasses=c("Date", "numeric", "character", "numeric", "numeric"),
text="AnnounceDate MarketProbability DealStatus binary BrierScore
2000-04-10 0.3333333 Complete 1 0.2340565
2000-06-14 0.2142857 Complete 1 0.3618200
2000-06-26 0.6846154 Complete 1 0.3690167
2000-06-16 0.1875000 Complete 1 0.4364041
2000-10-05 0.9555556 Complete 1 0.3078432
2000-10-19 0.8500000 Complete 1 0.2670799")
p1 = ggplot(data=allData, aes(x=AnnounceDate)) +
geom_point(aes(y=MarketProbability, colour=DealStatus)) +
scale_colour_hue(h = c(180,0)) +
geom_line(aes(y=BrierScore))
ggsave(filename="plot_1.png", plot=p1, height=2.5, width=5)
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