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).
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 have got a data frame with several 1000 rows in the form of
group = c("gr1","gr1","gr1","gr1","gr1","gr1","gr1","gr1","gr1","gr1","gr2","gr2","gr2","gr2","gr2","gr2","gr2","gr2","gr2","gr2","gr3","gr3","gr3","gr3","gr3","gr3","gr3","gr3","gr3","gr3")
pos = c(1,2,3,4,5,6,7,8,9,10,1,2,3,4,5,6,7,8,9,10,1,2,3,4,5,6,7,8,9,10)
color = c(2,2,2,2,3,3,2,2,3,2,1,2,2,2,1,1,1,1,1,1,2,2,2,2,2,2,1,1,2,2)
df = data.frame(group, pos, color)
and would like to make a kind of heatmap in which one axes has a continuous scale (position). The color column is categorical. However due to the large amount of data points I want to use binning, i.e. use it as a continuous variable.
This is more or less how the plot should look like:
I can't think of a way to create such a plot using ggplot2/R. I have tried several geometries, e.g. geom_point()
ggplot(data=df, aes(x=strain, y=pos, color=color)) +
geom_point() +
scale_colour_gradientn(colors=c("yellow", "black", "orange"))
Thanks for your help in advance.
Does this help you?
library(ggplot2)
group = c("gr1","gr1","gr1","gr1","gr1","gr1","gr1","gr1","gr1","gr1","gr2","gr2","gr2","gr2","gr2","gr2","gr2","gr2","gr2","gr2","gr3","gr3","gr3","gr3","gr3","gr3","gr3","gr3","gr3","gr3")
pos = c(1,2,3,4,5,6,7,8,9,10,1,2,3,4,5,6,7,8,9,10,1,2,3,4,5,6,7,8,9,10)
color = c(2,2,2,2,3,3,2,2,3,2,1,2,2,2,1,1,1,1,1,1,2,2,2,2,2,2,1,1,2,2)
df = data.frame(group, pos, color)
ggplot(data = df, aes(x = group, y = pos)) + geom_tile(aes(fill = color))
Looks like this
Improved version with 3 color gradient if you like
library(scales)
ggplot(data = df, aes(x = group, y = pos)) + geom_tile(aes(fill = color))+ scale_fill_gradientn(colours=c("orange","black","yellow"),values=rescale(c(1, 2, 3)),guide="colorbar")
I have two dataframes dataA and dataB, both of which contain a time and a value column. Time columns are closely related, but non-identical. Now, I generate two plots with ggplot, e.g.:
plotA <- ggplot(dataA) + geom_line(aes(x = time, y = value))
plotB <- ggplot(dataB) + geom_line(aes(x = time, y = value))
How can I use grid.arrange or a similar function to display the two plots vertically and so that x-axis labels and grid lines align?
You could use facets to align the plots.
Firstly, both data sets need to be combined:
dataAB <- rbind(dataA[c("time", "value")], dataB[c("time", "value")])
A new column indicates the original data set:
dataAB$ind <- c(rep("A", nrow(dataA)), rep("B", nrow(dataB)))
Plot:
library(ggplot2)
ggplot(dataAB) +
geom_line(aes(x = time, y = value)) +
facet_wrap( ~ ind, ncol = 1, scales = "free_y")
I have data where I look at the difference in growth between a monoculture and a mixed culture for two different species. Additionally, I made a graph to make my data clear.
I want a barplot with error bars, the whole dataset is of course bigger, but for this graph this is the data.frame with the means for the barplot.
plant species means
Mixed culture Elytrigia 0.886625
Monoculture Elytrigia 1.022667
Monoculture Festuca 0.314375
Mixed culture Festuca 0.078125
With this data I made a graph in ggplot2, where plant is on the x-axis and means on the y-axis, and I used a facet to divide the species.
This is my code:
limits <- aes(ymax = meansS$means + eS$se, ymin=meansS$means - eS$se)
dodge <- position_dodge(width=0.9)
myplot <- ggplot(data=meansS, aes(x=plant, y=means, fill=plant)) + facet_grid(. ~ species)
myplot <- myplot + geom_bar(position=dodge) + geom_errorbar(limits, position=dodge, width=0.25)
myplot <- myplot + scale_fill_manual(values=c("#6495ED","#FF7F50"))
myplot <- myplot + labs(x = "Plant treatment", y = "Shoot biomass (gr)")
myplot <- myplot + opts(title="Plant competition")
myplot <- myplot + opts(legend.position = "none")
myplot <- myplot + opts(panel.grid.minor=theme_blank(), panel.grid.major=theme_blank())
So far it is fine. However, I want to add two different horizontal lines in the two facets. For that, I used this code:
hline.data <- data.frame(z = c(0.511,0.157), species = c("Elytrigia","Festuca"))
myplot <- myplot + geom_hline(aes(yintercept = z), hline.data)
However if I do that, I get a plot were there are two extra facets, where the two horizontal lines are plotted. Instead, I want the horizontal lines to be plotted in the facets with the bars, not to make two new facets. Anyone a idea how to solve this.
I think it makes it clearer if I put the graph I create now:
Make sure that the variable species is identical in both datasets. If it a factor in one on them, then it must be a factor in the other too
library(ggplot2)
dummy1 <- expand.grid(X = factor(c("A", "B")), Y = rnorm(10))
dummy1$D <- rnorm(nrow(dummy1))
dummy2 <- data.frame(X = c("A", "B"), Z = c(1, 0))
ggplot(dummy1, aes(x = D, y = Y)) + geom_point() + facet_grid(~X) +
geom_hline(data = dummy2, aes(yintercept = Z))
dummy2$X <- factor(dummy2$X)
ggplot(dummy1, aes(x = D, y = Y)) + geom_point() + facet_grid(~X) +
geom_hline(data = dummy2, aes(yintercept = Z))