I'm fairly new to ggplot2, and I'm trying to create a contour plot of data that has missing values. Because there's missing values I can't have the contours by themselves, so I'm combining a tiles background with a contour. The problem is the labels are the same colour as the background.
Suppose I have data like so:
DF1 <- data.frame(x=rep(1:3,3),y=rep(1:3,each=3),z=c(1,2,3,2,3,4,3,NA,NA))
I can make a plot like this:
require(ggplot2); require(directlabels)
plotDF <- ggplot(DF1,aes(x,y,z=z)) + geom_tile(aes(fill=z)) + stat_contour(aes(x,y,z=z,colour= ..level..),colour="white")
direct.label(plotDF)
This gives me a plot similar to what I want but I'd like to be able to change the colours of the labels to be black. Any ideas?
I spotted a similar post and thought this would be easy, something along the lines of direct.label(p, list("last.points", colour = "black"). I could not make it work, unfortunately; I believe, this is not directly supproted.
I then decided to use black magic and managed to do the trick by manually overriding the colour scale:
direct.label(plotDF +
scale_colour_gradient(low="black", high="black"))
Related
I have a question about facet_wrap() in ggplot2.
I am trying to make a graph that looks like this. I attach an example image 1.enter image description here
In image 1 it can be seen that there are two maps and each one has its legend and color scale. I would like to be able to do this with ggplot and the facet_wrap() function.
My problem is that because the data in the dataframe is very different, they have a lot of amplitude for each map, when plotting the scale it does not allow me to visualize it the way I want.
enter image description here
ggplot(dataframe,mapping=aes(x=lon,x=lat))+
geom_contour_fill((aes(z=hgt,fill=stat(level)))+
geom_contour(aes(z=hgt),color="black",size=0.2)+
scale_fill_distiller(palette = "YlOrBr",direction = 1,super=ScaleDiscretised)+
mi_mapa+
coord_quickmap(xlim = range(dataframe$lon),ylim=range(dataframe$lat),expand = FALSE)+
facet_wrap(~nombre_nivel,scales="free", ncol =2) +
labs(x="Longitud",y="Latitud",fill="altura",title = "campos")
my dataframe has a shape like this. Where the facets are determined by the level variable. In this case the dataframe has another variable which is temp instead of hgt, but it's just another name.
enter image description here
Thanks
I think I've faced the alike problem building the two parts of the single map with two different scales. I found the package grid useful.
library(grid)
grid.newpage()
print(myggplot, vp = specifiedviewport)
In my case I built the first p <- ggplot() than adjusted p2 <- p + ...
with printing the two ggplots (p and p2) in two viewports. You can newly construct p2 with individual scale and print it in the grid. You can find useful information
here.
I try to generate a plot on which every point stands for an event. Color, Size and faced_grid are used to give additional information available in a visual way. The graph is working in ggplot2 but it is often important to know the exact numbers so an interactive version is needed which enables to hover over the point and get the info. I tried to convert the plot into an interactive version with the function ggplotly from the plotly-package. The problem then is, that the legend not only display the different states of the used attributes, it contains every existent combination. In addition, it did not display info from geom_rect.
I found related/similar questions but they used the function plot_ly and not ggploty or did not provide an answer.
Following, the same problem illustrated with the mtcars dataset:
library(plotly)
g = ggplot(mtcars,aes(x=mpg,y=disp,color = as.factor(cyl),size =as.factor(gear))) +
geom_point() +
geom_text(label = c(rep("A",nrow(mtcars)-5),rep("B",5)),color = "black",size=4) +
geom_rect(data=data.frame(name="zone",Start=20,End = 30,ymin = -Inf,ymax = Inf),aes(xmin=Start, xmax=End, ymin=ymin, ymax=ymax,fill=name),inherit.aes = FALSE,alpha=0.3)+
facet_grid(vs~am)
g
This is the result and how it should look like: ggplot Graph
Now using ggplotly
ggplotly(g)
This is the result: ggploty Graph
(1) The legend is now a combination of the different attributes used for Color and Size
(2) geom_rect is in the legend but didn’t get displayed in the graph
Does anyone knows how to get the same graph in ggplotly like in ggplot2? I am grateful for every hint. Thanks
Dave
I do not know how to fix the combination of legends when you use ggplotly. But, I can fix the second problem, if you do not use the Inf and -Inf, the geom_rect will work:
ggplotly(ggplot(mtcars,aes(x=mpg,y=disp, = as.factor(cyl),size =as.factor(gear))) +
geom_rect(aes( xmin=20,
xmax=30,
ymin=0,
ymax=max(mtcars$disp),
fill="Name"),
inherit.aes = FALSE, alpha=0.3) +
geom_point() +
geom_text(label = c(rep("A",nrow(mtcars)-5),rep("B",5)), = "black",size=4) +
facet_grid(vs~am))
However, the legends are bad.
I would suggest using subplot to create the same thing in Plotly, and I think this link Ben mentioned will help you create each subplot. One thing to mention is that I had trouble Illustrating different size in legend in plotly, while the size of the marker will be different, there will not be a legend for the size scale. Maybe a scale will be a better option.
Is there a reason why ggplot might mess with the geom_point shape in the legend?
In the actual plot everything looks with the shapes correctly plotted as circles, but in the legend it shows them as weird boxes / squares, i.e. it is showing this:
But it should show this:
Could it be because I have an ifelse in my geom_point ? This is what I have here for this part:
geom_point(aes( y=y, colour=ifelse( (ty>308)&(Time < chron(times=c('08:30:30.0'))), ifelse(side=='left', 'red', 'blue'),'gray')), na.rm = T)
This issue is actually because geom_point and geom_line are both plotted and the points are varying according to the size parameter. ggplot is trying to show a point on a line which looks good when it is small and clear but becomes strange and box-like as the size varies.
To make it clearer, turning off the legend for either the line or the points will keep just one.
For example:
geom_line(aes(y=foo , colour='green'), show.legend = F)
I have a dataset:
a<-c(1,2,3,4,5,6,7,8,9,10)
b<-c(2,2,2,2,4,5,6,8,4,1)
c<-c("red","red","red","blue","blue","blue","orange","orange","orange","orange")
data<-data.frame(a=a,b=b,c=c)
I now want to plot the data on a graph with each group having a different colour:
plot(a[c=="red"],b[c=="red"],col="red",xlim=c(min(a),max(a)),ylim=c(min(b),max(b)))
points(a[c=="blue"],b[c=="blue"],col="blue")
points(a[c=="orange"],b[c=="orange"],col="orange")
This works fine - however, say if I have 30 groups, the task of writing the code becomes tedious. I am wondering if there is a better way of writing the code such that R will automatically plot the graph and give different colours to different groups?
Also, I wonder if there is a quick way to display a legend in the graph.
Thank you for all your help.
Try this:
with(data,plot(a,b,col=c))
The col argument in plot() stands for color. This can contain a vector of the colors you want.
Additionally, you don't have to make a column just to define the color if the color-group relationship is not that important. For example, you could make column c a more meaningful column like this:
a<-c(1,2,3,4,5,6,7,8,9,10)
b<-c(2,2,2,2,4,5,6,8,4,1)
c<-c(rep('Group1',3),rep('Group2',3),rep('Group3',4))
data<-data.frame(a=a,b=b,c=c)
Then to plot, use:
with(data,plot(a,b,col=c))
To add a legend:
legend('topleft',legend = levels(data[,'c']),col=1:nlevels(data[,'c']),pch=1)
Try ggplot2
library(ggplot2)
ggplot(data=data, aes(x=a, y=b, colour=c)) + geom_point()
I'm relatively new to ggplot2, and I'm having trouble adding appropriate labels to my contours. I would love to be able to add the labels without the directlabels package, but I haven't found a way to, so if you know of a way to customize labels without directlabels, I would love to here it.
Using the classic volcano example, I can add labels to the default contour plot using the directlabels packet in the following way:
library(plyr)
library(ggplot2)
library(directlabels)
library(reshape)
volcano<-melt(volcano)
v<-ggplot(volcano, aes(x,y,z=z))
e<-v + stat_contour(aes(colour=..level..))
direct.label(e)
In the above example, the labels are added appropriately, but things become more complicated if I try to specify my own break points for the contours:
e<-v + stat_contour(aes(breaks=c(160, 170, 180), colour=..level..))
direct.label(e)
Now, the contours are specified by the breaks I have provided, but labels still appear for all of the default contours. How do I only plot only labels for the graphed contours?
A related issue, how would I plot labels for contour levels not included in the default? Say a break of 165:
e<-v + stat_contour(aes(breaks=c(165), colour=..level..))
direct.label(e)
Thanks for any help!
The current development version (directlabels_2013.6.15 with ggplot2_0.9.3.1) should fix your problem (as the author of the directlabels package explained to me). You can install it with:
install.packages("directlabels", repos="http://r-forge.r-project.org")
And then:
library(plyr)
library(ggplot2)
library(directlabels)
library(reshape)
volcano<-melt(volcano)
v<-ggplot(volcano, aes(X1,X2,z=value))
e<-v + stat_contour(aes(colour=..level..), breaks=c(165))
direct.label(e)
I noted several other limitations with simple workarounds:
the first ggplot call must contain the z aesthetic
this works only with the stat_contour (and not with the geom_contour)
the colour aesthetic must be defined in the stat_contour call and set to ..level..
Finally, if you want to control the label and contour line colours (black labels and blue contour lines for instance), you can achieved this as follow:
e<-v + stat_contour(aes(colour=..level..), colour = "blue", breaks=c(165))
e<-e + scale_colour_continuous(low = "#FF0000", high = "#FF0000")
direct.label(e)