I'm trying to make a scatter plot with R plotly, where the points are colored according to a gradient, and on top of that I'd like to text annotate several points, where I'd like the color of the text annotation to follow the same color gradient.
Here's a toy data:
set.seed(1)
df <- data.frame(x=rnorm(100),y=-1*log10(runif(100,0,1)),id=paste0("id",1:100),stringsAsFactors = F)
Here's the colored scatter plot:
library(plotly)
library(dplyr)
scatter.plot <- plot_ly(type='scatter',mode='markers',x=~df$x,y=~df$y,color=~df$y,colors=c("blue","red"),showlegend=FALSE) %>%
layout(xaxis=list(title="Effect Size",zeroline=F),yaxis=list(title="Significance",zeroline=F))
which gives:
Then, I'm trying to add the text annotation.
First, I'm creating the annotation data:
ann.df <- df[sample(100,5,replace = F),]
Then I'm trying this to add the annotation text:
scatter.plot <- scatter.plot %>% layout(annotations = list(x=ann.df$x,y=ann.df$y,text=ann.df$id,xref="x",yref="y",showarrow=T,arrowhead=5,arrowcolor=ann.df$y,ax=20,ay=-40,colors=c("blue","red"),font=list(size=15,color=ann.df$y,colors=c("blue","red"))))
The text is added but not color coded:
Any idea how to get the text colored according df$y with the c("blue","red") gradient ?
I am not sure how to achieve this using plotly. Maybe someone will have a better idea but in the meantime, it might be easier by simply using ggplotly to get what you want.
You could try this:
a <- ggplot(data = df, aes(x = x, y = y, color = y, label1 = x, label2 = y)) +
geom_point() +
theme_bw() +
scale_color_continuous(low = "blue", high = "red")
b <- a +
geom_text(data = ann.df, aes(x=x, y=y, label = id, color = y), hjust = 0, nudge_x = 0.05)
ggplotly(b, tooltip = c("label", "label1", "label2"))
Related
I would like to make a PCA score plot using ggplot2, and then convert the plot into interactive plot using plotly.
What I want to do is to add a frame (not ellipse using stat_ellipse, I know it worked).
My problem is that when I try to use sample name as tooltip in ggplotly, the frame will disappear. I don't know how to fix it.
Below is my code
library(ggplot2)
library(plotly)
library(dplyr)
## Demo data
dat <- iris[1:4]
Group <- iris$Species
## Calculate PCA
df_pca <- prcomp(dat, center = T, scale. = FALSE)
df_pcs <- data.frame(df_pca$x, Group = Group)
percentage <-round(df_pca$sdev^2 / sum(df_pca$sdev^2) * 100, 2)
percentage <-paste(colnames(df_pcs),"(", paste(as.character(percentage), "%", ")", sep = ""))
## Visualization
Sample_Name <- rownames(df_pcs)
p <- ggplot(df_pcs, aes(x = PC1, y = PC2, color = Group, label = Sample_Name)) +
xlab(percentage[1]) +
ylab(percentage[2]) +
geom_point(size = 3)
ggplotly(p, tooltip = "label")
Until here it works! You can see that sample names can be properly shown in the ggplotly plot.
Next I tried to add a frame
## add frame
hull_group <- df_pcs %>%
dplyr::mutate(Sample_Name = Sample_Name) %>%
dplyr::group_by(Group) %>%
dplyr::slice(chull(PC1, PC2))
p2 <- p +
ggplot2::geom_polygon(data = hull_group, aes(fill = Group), alpha = 0.1)
You can see that the static plot still worked! The frame is properly added.
However, when I tried to convert it to plotly interactive plot. The frame disappeared.
ggplotly(p2, tooltip = "label")
Thanks a lot for your help.
It works if you move the data and mapping from the ggplot() call to the geom_point() call:
p2 <- ggplot() +
geom_point(data = df_pcs, mapping = aes(x = PC1, y = PC2, color = Group, label = Sample_Name), size = 3) +
ggplot2::geom_polygon(data = hull_group, aes(x = PC1, y = PC2, fill = Group, group = Group), alpha = 0.2)
ggplotly(p2, tooltip = "label")
You might want to change the order of the geom_point and geom_polygon to make sure that the points are on top of the polygon (this also affects the tooltip location).
very new to this so apologies if there's an obvious answer. I'm trying to add a legend to a scatter-line graph with 2 y variables; i'm aware this can be done using colour, however I ideally want to keep this black and white, and define the variables in the legend by linetype/point instead. Is there any way to do this?
ggplot(birds, aes(distance)) +geom_point(aes(y=individuals_AC)) +geom_point(aes(y=species_AC, shape=17)) +geom_line(aes(y=individuals_AC)) +geom_line(aes(y=species_AC, linetype="dashed")) + scale_shape_identity() + scale_linetype_identity() + theme_classic()
library(tidyverse)
#create some dummy data
df <- tibble(
x = runif(10),
y = runif(10),
type = rep(c("a", "b"), 5)
)
#plot it with a different shape for each type
df %>%
ggplot(aes(x, y, shape = type)) +
geom_point()
I have created the following dataframe in R. The first step is to import the necessary libraries
library(ggplot2)
library(plotly)
library(dplyr)
We create the dataframe here as follows
DF_1<-data.frame("A"= c(1:10))
DF_1$B<-c("D", "C")
DF_1$C<-DF_1$A^2
Next we create a plot as follows
p2<-ggplot(DF_1, aes(x=A, y=C, group=B, fill=B)) +
geom_line(size=.5) + geom_ribbon(data=subset(DF_1),aes(x=A,ymax=C),ymin=0,alpha=0.3) +
scale_fill_manual(name='Legend', values=c("green4", "red"), labels=c("D", "C" ))+theme_bw()
When p2 is rendered, the legend displays correctly. When I nest p2 in ggplotly, the legend changes to two dark lines.
p3<-ggplotly(p2, dynamicTicks = T)
p3= layout(p3, xaxis = list(type = "log"))
Is it possible to retain the legends of p2 in p3. I request someone to take a look
Looks like ggplotly is a more sensible than ggplot2 in how one sets the aesthetics. Simply moving the fill aes from the global setup in ggplot into geom_ribbon gives the correct legend:
library(ggplot2)
library(plotly)
library(dplyr)
DF_1<-data.frame("A"= c(1:10))
DF_1$B<-c("D", "C")
DF_1$C<-DF_1$A^2
ggplot(DF_1, aes(x = A, y = C, group=B)) +
geom_line(size=.5) +
geom_ribbon(aes(x = A, ymin = 0, ymax = C, fill = B), alpha=0.3) +
scale_fill_manual(name='Legend', values=c("green4", "red"), labels=c("D", "C" ))+theme_bw()
ggplotly(dynamicTicks = T) %>%
layout(xaxis = list(type = "log"))
I have a data frame and I would like to stack the points that have overlaps exactly on top of each other.
here is my example data:
value <- c(1.080251e-04, 1.708859e-01, 1.232473e-05, 4.519876e-03,2.914256e-01, 5.869711e-03, 2.196347e-01,4.124873e-01, 5.914052e-03, 2.305623e-03, 1.439013e-01, 5.407597e-03, 7.530298e-02, 7.746897e-03)
names = letters[1:7]
data <- data.frame(names = rep(names,), group = group, value = value, stringsAsFactors = T)
group <- c(rep("AA", 7) , rep("BB", 7))
I am using the following command:
p <- ggplot(data, aes(x = names, y = "", color = group)) +
geom_point(aes(size = -log(value)), position = "stack")
plot(p)
But the stacked circle outlines out of the grid. I want it close or exactly next to the bottom circle. do you have any idea how I can fix the issue?
Thanks,
The y-axis has no numeric value, so use the group instead. And we don't need the color legend now since the group labels are shown on the y-axis.
ggplot(data, aes(x = names, y = group, color = group)) +
geom_point(aes(size = -log(value))) +
guides(color=FALSE)
I'm converting a ggplot2 plot to plotly.
The plot consists of a tile layer (in the background) and a point layer (in the foreground).
I would like to have tooltips when hovering on the tiles.
The code below mostly gets me what I am looking for. When I hover on tiles in "points free" zones, the desired tooltip appears. However, when I hover in areas with a high density of dots, the tooltips do not appear.
I thought that playing with the layerData parameter in the ggplotly call might help, but that was not the case.
library(ggplot2)
library(dplyr)
library(plotly)
set.seed(1)
dat_points <- data.frame(x = rnorm(100), y = rnorm(100))
dat_tiles <- expand.grid(tx = -3:3, ty = -3:3)
dat_tiles$val <- rnorm(nrow(dat_tiles))
dat_tiles$label <- sample(LETTERS[1:5], nrow(dat_tiles), replace = T)
p <- ggplot() +
geom_tile(data = dat_tiles, aes(x = tx, y = ty, fill = val, text = label)) +
geom_point(data = dat_points, aes(x = x, y = y), alpha = .5)
gg <- ggplotly(p, tooltip = "text")
gg
I would like that hovering on high density areas (e.g. 0, 0) would bring up tooltips with the same promptness as in low density areas.
EDIT: added static image of the plot.
You can switch the order of you layers in p and because of how ggplotly() constructs from a ggplot object, you get an identical looking plot, but with the desired tooltip behavior!
p <- ggplot() +
geom_point(data = dat_points, aes(x = x, y = y), alpha = 1) +
geom_tile(data = dat_tiles, aes(x = tx, y = ty, fill = val, text = label))
p # this looks bad
gg <- ggplotly(p, tooltip = "text")
gg # but this looks good!