A problem occurs when i add a colour(gradient) into the aesthetics of geom_line. It seems that the dots are no longer connected by a line but instead transformed into squares, which messes up the plot. Does anyone have an idea how to solve this problem or if this is how R or ggplot handles colour(gradients). This problem doesn't occur, when i remove the colours from the aes().
Thanks in advance!
Simple code:
df <- data.frame(c(1,3,4,2,5,8),c(1,2,3,4,5,6))
colnames(df) <- c("x","y")
ggplot()+
theme_classic()+
geom_line(data=df,aes(x=x,y=y,colour=y),size=2)
ggplot()+
theme_classic()+
geom_line(data=df,aes(x=x,y=y),size=2)
Adjusting the lineend parameter should do it, which has a default of "square". The reason the uncolored version looks okay is that in those cases the segments are treated as continuations of the same series, so they are governed then by the linejoin parameter, which has a default of "round."
ggplot()+
theme_classic()+
geom_line(data=df,aes(x=x,y=y,colour=y),size=2, lineend = "round")
PS - if you want the color to vary within each segment, you might look at alternatives like ggforce::geom_link2, which uses interpolation to allow smooth transitions. However, it's parameterized differently, to be like geom_path, which plots data in order of appearance rather than in order of the x value, like geom_line.
Related
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)
So I'm trying to change the line type on ellipses generated from stat_ellipse in ggplot2 (see here https://raw.github.com/low-decarie/FAAV/master/r/stat-ellipse.R). I can manually set the colors easily enough, but I'd like to give it a vector of linetypes that would change the linetype of the ellipse. I've tried setting the linetypes in the stat_ellipse() function, and separately also with the +scale_linetype_manual but only a single value for line type seems to work in the stat_ellipse function, and the scale_linetype_manual doesn't do anything. Any advice is appreciated!
Basic code and example image is
ggplot(data.df,aes(x = PC1,y =PC2, color = mapping$Description))+
geom_point(size=5,aes(shape=factor(mapping$Status)))+
stat_ellipse(aes(x = PC1,y=PC2,fill=factor(mapping$Description)),
geom="polygon",level=0.8,alpha=0.2)+
scale_fill_manual(values=c("red","red","green","blue","blue"))
The mapping$... are just factors. PC1 and PC2 are just vectors with the principle components and data.df is just a data frame with all of those things in it.
The line type can be changed by first specifying the line type as a factor in the aes of the stat_ellipse, followed scale_linetype_manual as user aosmith pointed out in the comments.
ggplot(data.df,aes(x = PC1,y =PC2, color = mapping$Description))+
geom_point(size=5,aes(shape=factor(mapping$Status)))+
stat_ellipse(aes(x = PC1,y=PC2,lty=factor(mapping$Status),fill=factor(mapping$Description)),
geom="polygon",level=0.8,alpha=0.2)+
scale_fill_manual(values=c("red","red","green","blue","blue"))+
scale_linetype_manual(values=c(1,2,1,2,1))
I am trying to set the labels on a categorical axis within a faceted plot using the ggplot2 package (1.0.1) in R (3.1.1) with scales="free". If I plot without manually setting the axis tick labels they appear correctly (first plot), but when I try to set the labels (second plot) only the first n labels are used on both facets (not in sequence as with the original labels).
Here is a reproducible code snippet exemplifying the problem:
foo <- data.frame(yVal=factor(letters[1:8]), xVal=factor(rep(1:4,2)), fillVal=rnorm(8), facetVar=rep(1:2,each=4))
## axis labels are correct
p <- ggplot(foo) + geom_tile(aes(x=xVal, y=yVal, fill=fillVal)) + facet_grid(facetVar ~ ., scales='free')
print(p)
## axis labels are not set correctly
p <- p + scale_y_discrete(labels=c('a','a','b','b','c','d','d','d'))
print(p)
I note that I cannot set the labels correctly within the data.frame as they are not unique. Also I am aware that I can accomplish this with arrange.grid, but this requires "manually" aligning the plots if there are different length labels etc. Additionally, I would like to have the facet labels included in the plot which is not an available option with the arrange.grid solution. Also I haven't tried viewports yet. Maybe that is the solution, but I was hoping for more of the faceted look to this plot and that seems to be more similar to grid.arrange.
It seems to me as though this is a bug, but I am open to an explanation as to how this might be a "feature". I also hope that there might be a simple solution to this problem that I have not thought of yet!
The easiest method would be to create another column in your data set with the right conversion. This would also be easier to audit and manipulate. If you insist on changing manually:
You cannot simply set the labels directly, as it recycles (I think) the label vector for each facet. Instead, you need to set up a conversion using corresponding breaks and labels:
p <- p + scale_y_discrete(labels = c('1','2','3','4','5','6','7','8'), breaks=c('a','b','c','d','e','f','g','h'))
print(p)
Any y axis value of a will now be replaced with 1, b with 2 and so on. You can play around with the label values to see what I mean. Just make sure that every factor value you have is also represented in the breaks argument.
I think I may actually have a solution to this. My problem was that my labels were not correct because as someone above has said - it seems like the label vector is recycled through. This line of code gave me incorrect labels.
ggplot(dat, aes(x, y))+geom_col()+facet_grid(d ~ t, switch = "y", scales = "free_x")+ylab(NULL)+ylim(0,10)+geom_text(aes(label = x))
However when the geom_text was moved prior to the facet_grid, the below code gave me correct labels.
ggplot(dat, aes(x, y))+geom_col()+geom_text(aes(label = x))+facet_grid(d ~ t, switch = "y", scales = "free_x")+ylab(NULL)+ylim(0,10)
There's a good chance I may have misunderstood the problem above, but I certainly solved my problem so hopefully this is helpful to someone!
I am creating a map (choropleth) as described on the ggplot2 wiki. Everything works like a charm, except that I am running into an issue mapping a continuous value to the polygon fill color via the scale_fill_brewer() function.
This question describes the problem I'm having. As in the answer, my workaround has been to pre-cut my data into bins using the gtools quantcut() function:
UPDATE: This first example is actually the right way to do this
require(gtools) # needed for quantcut()
...
fill_factor <- quantcut(fill_continuous, q=seq(0,1,by=0.25))
ggplot(mydata) +
aes(long,lat,group=group,fill=fill_factor) +
geom_polygon() +
scale_fill_brewer(name="mybins", palette="PuOr")
This works, however, I feel like I should be able to skip the step of pre-cutting my data and do something like this with the breaks option:
ggplot(mydata) +
aes(long,lat,group=group,fill=fill_continuous) +
geom_polygon() +
scale_fill_brewer(names="mybins", palette="PuOr", breaks=quantile(fill_continuous))
But this doesn't work. Instead I get an error something like:
Continuous variable (composite score) supplied to discrete scale_brewer.
Have I misunderstood the purpose of the "breaks" option? Or is breaks broken?
A major issue with pre-cutting continuous data is that there are three pieces of information used at different points in the code:
The Brewer palette -- determines the maximum number of colors available
The number of break points (or the bin width) -- has to be specified with the data
The actual data to be plotted -- influences the choice of the Brewer palette (sequential/diverging)
A true vicious circle. This can be broken by providing a function that accepts the data and the palette, automatically derives the number of break points and returns an object that can be added to the ggplot object. Something along the following lines:
fill_brewer <- function(fill, palette) {
require(RColorBrewer)
n <- brewer.pal.info$maxcolors[palette == rownames(brewer.pal.info)]
discrete.fill <- call("quantcut", match.call()$fill, q=seq(0, 1, length.out=n))
list(
do.call(aes, list(fill=discrete.fill)),
scale_fill_brewer(palette=palette)
)
}
Use it like this:
ggplot(mydata) + aes(long,lat,group=group) + geom_polygon() +
fill_brewer(fill=fill_continuous, palette="PuOr")
As Hadley explains, the breaks option moves the ticks, but does not make the data continuous. Therefore pre-cutting the data as per the first example in the question is the right way to use the scale_fill_brewer command.