This thread shows how to change the position of the legend in a ggvis object. However, if tooltips are added as well, the legend disappears.
library(ggvis)
data(mtcars)
mtcars %>%
ggvis(x = ~wt, y = ~mpg, fill = ~cyl) %>%
layer_points() %>%
add_legend(
"fill",
properties = legend_props(
legend = list(
x = scaled_value("x", 3.25),
y = scaled_value("y", 40)
)
)
) %>%
add_tooltip(function(df) df$wt)
Any idea how to prevent this?
This is a know issue, you can try adding the below at the end of your code as a workaround:
... %>% set_options(duration = 0)
Related
In the following example how can i add a title to the legend in plot_ly for R ?
mtcars %>% plot_ly(x = ~disp, y = ~mpg, color = ~factor(cyl), size = ~wt) %>% add_markers(
hoverinfo = "text",
text = ~paste("Displacement = ", disp, "\nMiles Per Gallon = ", mpg) ) %>% layout(title ="Custom Hover Text")
thanks
This functionality has since been included within the layout function in the legend option. There's a sub-option called title within which you can supply a list that includes the text.
mtcars %>%
plot_ly(x = ~disp, y = ~mpg, color = ~factor(cyl), size = ~wt) %>%
add_markers(hoverinfo = "text",
text = ~paste("Displacement = ", disp, "\nMiles Per Gallon = ", mpg) ) %>%
layout(title = "Custom Hover Text",
legend = list(title = list(text = "<b>Cylinders</b>"))) # TITLE HERE
The only way I know is to use an annotation and add it to the plot. Like this:
legendtitle <- list(yref='paper',xref="paper",y=1.05,x=1.1, text="Cylinders",showarrow=F)
mtcars %>% plot_ly(x = ~disp, y = ~mpg, color = ~factor(cyl), size = ~wt) %>%
add_markers( hoverinfo = "text",
text = ~paste("Displacement=",disp, "\nMiles Per Gallon = ", mpg)) %>%
layout(title ="Custom Hover Text", annotations=legendtitle )
Yielding:
It is a bit tricky to place the legend title though, not sure if this placement would always work.
Another way would be to use ggplot and ggplotly of course, and let ggplot figure it out.
This is my code. Just a simple historgram. But what I wanted to do is to customize the hover text so that when I hover, it will display all species included in that histogram bar. Can you help me?
iris %>%
plot_ly(x=~Sepal.Length, color=~Sepal.Width, text=~Species) %>%
add_histogram()
Here's the output. But when I hover it seems the text is only displaying the first species in the table.
plotly_hist
I'm not sure whether this is possible. Probably you are demanding too much from plotly. After trying some options I think there are two ways to go if you want the different Species to show up in the tooltip:
First option is to use a stacked histogram using hovermode = "unified" like so:
library(plotly)
fig <- plot_ly()
fig <- fig %>% add_trace(data = filter(iris, Species == "setosa"),
x = ~Sepal.Length,
color = ~Species,
text = ~Species,
type='histogram',
bingroup=1, showlegend = FALSE)
fig <- fig %>% add_trace(data = filter(iris, Species == "versicolor"),
x = ~Sepal.Length,
color = ~Species,
text = ~Species,
type='histogram',
bingroup=1, showlegend = FALSE)
fig <- fig %>% add_trace(data = filter(iris, Species == "virginica"),
x = ~Sepal.Length,
color = ~Species,
text = ~Species,
type='histogram',
bingroup=1, showlegend = FALSE)
fig <- fig %>% layout(
hovermode="unified",
barmode="stack",
bargap=0.1)
fig
The second option would be to make the computations yourself, i.e. binning and summarising and to make a bar chart of the counts.
iris %>%
mutate(Sepal.Length.Cut = cut(Sepal.Length, breaks = seq(4, 8, .5), right = FALSE)) %>%
group_by(Sepal.Length.Cut, Species) %>%
summarise(n = n(), Sepal.Width = sum(Sepal.Width)) %>%
tidyr::unite("text", Species, n, sep = ": ", remove = FALSE) %>%
summarise(n = sum(n), Sepal.Width = sum(Sepal.Width) / n, text = paste(unique(text), collapse = "\n")) %>%
plot_ly(x = ~Sepal.Length.Cut, y = ~n, text = ~text) %>%
add_bars(marker = list(colorscale = "Rainbow"), hovertemplate = "%{y}<br>%{text}")
Edit A third option would be to use ggplotly(). This way it is an easy task to add annotations displayling the total numbers per bin. This way we can make use of the stats layers in ggplot2 which will do all the computations. To the best of my knowledge that couldn't be done that easily using "pure" plotly.
library(plotly)
ggplot(iris, aes(Sepal.Length, fill = Species)) +
stat_bin(breaks = seq(4, 8, .5), closed = "left") +
stat_bin(breaks = seq(4, 8, .5), closed = "left", geom = "text", mapping = aes(Sepal.Length, label = ..count..), inherit.aes = FALSE, vjust = -.5) +
theme_light()
ggplotly()
I want to achieve the same result as this ggplot code with plotly:
mtcars %>% add_rownames('car') %>%
ggplot(aes(x = mpg,
y = disp,
color = as.factor(gear),
shape = as.factor(cyl))) +
geom_point()
which results in:
My plotly code is:
library(dplyr)
mtcars %>% add_rownames('car') %>%
plot_ly(x = ~mpg,
y = ~disp,
text = ~car,
color = ~as.factor(gear),
symbol = ~as.factor(cyl),
mode = 'markers')
which enumerates all possible combinations of colors and shapes in the legend.
Is there a way to have a similar legend to the ggplot?
UPDATE: To overcome some of the issues mentioned for my previous solution (see below) and to increase the usability of the legend, one can simply add the column name to the legend description and then assign the legendgroups to each category.
mtcars %>% rownames_to_column('car') %>%
plot_ly() %>%
#Plot symbols for cyl
add_trace(type = "scatter",
x = ~mpg,
y = ~disp,
text = ~car,
symbol = ~paste0(cyl," cyl."),
mode = 'markers',
marker = list(color = "grey", size = 15)) %>%
#Overlay color for gears
add_trace(type = "scatter",
x = ~mpg,
y = ~disp,
text = ~car,
color = ~paste0(gear, " gears"),
mode = 'markers')
This is the previous solution, which is visually closer to the ggplot2 equivalent:
Based on the answer of dww in this thread, we can manually create the groups for cylinders and gears. Subsequently, with the answer of Artem Sokolov this thread, we can add the legend titles as annotations.
mtcars %>% rownames_to_column('car') %>%
plot_ly() %>%
#Plot symbols for cyl
add_trace(type = "scatter",
x = ~mpg,
y = ~disp,
text = ~car,
symbol = ~as.factor(cyl),
mode = 'markers',
legendgroup="cyl",
marker = list(color = "grey", size = 15)) %>%
#Overlay color for gears
add_trace(type = "scatter",
x = ~mpg,
y = ~disp,
text = ~car,
color = ~as.factor(gear),
mode = 'markers',
legendgroup="gear") %>%
#Add Legend Titles (manual)
add_annotations( text="Cylinders:", xref="paper", yref="paper",
x=1.02, xanchor="left",
y=0.9, yanchor="bottom", # Same y as legend below
legendtitle=TRUE, showarrow=FALSE ) %>%
add_annotations( text="Gears:", xref="paper", yref="paper",
x=1.02, xanchor="left",
y=0.7, yanchor="bottom", # Y depends on the height of the plot
legendtitle=TRUE, showarrow=FALSE ) %>%
#Increase distance between groups in Legend
layout(legend=list(tracegroupgap =30, y=0.9, yanchor="top"))
Unsolved issues:
Groups have to be created manually
Groups are just overlayed (color over shape). This means that only the whole group can be dis-/activated in the legend (e.g., it is not possible to only show only the entries with 4 cylinders)
The position of the second legend title (annotation) depends on the height of the plot!
I'm using plotly in r to generate a number of subplots. A toy example is shown below.
library(shiny)
library(dplyr)
library(plotly)
## Toy Example
ui <- fluidPage(
h3("Diamonds"),
plotlyOutput("plot", height = 600)
)
server <- function(input, output, session) {
# reduce down the dataset to make the example simpler
dat <- diamonds %>%
filter(clarity %in% c("I1", "IF")) %>%
mutate(clarity = factor(clarity, levels = c("I1", "IF")))
output$plot <- renderPlotly({
# Generates the chart for a single clarity
byClarity <- function(df){
Clarity <- df$clarity[1];
plot_ly(df, x = ~carat, y = ~price, color = ~cut, name = ~clarity) %>%
add_trace(
type="bar"
## Also tried adding this with no success
# legendgroup = ~cut
) %>%
layout(
barmode = "stack"
)
}
dat %>%
split(.$clarity) %>%
lapply(byClarity) %>%
subplot(nrows = NROW(.), shareX = TRUE, which_layout = "merge")
})
}
shinyApp(ui, server)
I would like to make the legends such that clicking on a 'Cut' on the legend will show/hide that 'Cut' from both charts instead of just the chart associated with that legend.
I looked at legendgroup but can't figure out how to associate it with cut instead of clarity (clarity is the grouping I'm using to make the subplots).
I also need the solution to work with raw plot_ly and not ggplotly as there are other plot_ly functionalities I need that aren't available in ggplotly.
Any help would be appreciated. I am using plotly_4.5.2, dplyr_0.5.0, and shiny_0.14.
Ok, here is a solution using ggplot2:
library(ggplot2)
library(dplyr)
library(plotly)
dat <- diamonds %>%
filter(clarity %in% c("I1", "IF")) %>%
mutate(clarity = factor(clarity, levels = c("I1", "IF")))
# Function for nice labels
k_label <- function(x) {
c(0, paste0((x)/1000,"K")[-1])
}
# ggplot
p <- ggplot(dat,aes(x=carat, y=price, fill=cut)) +
geom_bar(stat="identity") +
facet_wrap(~clarity,nrow=2, scales = "free_y") +
scale_y_continuous(labels = k_label) +
theme_minimal() + ylab("") + xlab("") +
theme(legend.title=element_blank(),
panel.grid.major.x=element_blank())
# a plotly
ggplotly(p)
Try adding legendgroup = ~cut to both traces and setting showlegend = F for one of them. Then in layout set showlegend = T
Like this:
plot_ly(df, x = ~carat, y = ~price, color = ~cut, name = ~clarity, legendgroup = ~cut, showlegend = T) %>%
add_trace( type="bar", legendgroup = ~cut, showlegend = F) %>%
layout(
barmode = "stack",showlegend = T
)
I want to group data on two variables and distinguish them in a ggvis plot via 'stroke' and 'strokeDash'. If I want to add legends to a ggvis plot, I can do so for the 'stroke' property:
library(ggvis)
mtcars %>%
ggvis(~wt, ~mpg, stroke = ~factor(cyl), strokeDash = ~factor(vs)) %>%
layer_lines() %>%
add_legend('stroke', title = 'Number of cylinders')
However, if try to add a legend for 'strokeDash', the plot does not get rendered:
mtcars %>%
ggvis(~wt, ~mpg, stroke = ~factor(cyl), strokeDash = ~factor(vs)) %>%
layer_lines() %>%
add_legend('stroke', title = 'Number of cylinders') %>%
add_legend('strokeDash', title = 'V/S')
Same applies, if I try it with 'strokeWidth' instead of 'strokeDash':
# works
mtcars %>%
ggvis(~wt, ~mpg, stroke = ~factor(cyl), strokeWidth = ~factor(vs)) %>%
layer_lines() %>%
scale_nominal('strokeWidth', range = c(1,5)) %>%
add_legend('stroke', title = 'Number of cylinders')
# does not work
mtcars %>%
ggvis(~wt, ~mpg, stroke = ~factor(cyl), strokeWidth = ~factor(vs)) %>%
layer_lines() %>%
scale_nominal('strokeWidth', range = c(1,5)) %>%
add_legend('stroke', title = 'Number of cylinders')%>%
add_legend('strokeWidth', title = 'V/S')
Does anyone know, why for 'stroke' it works and for the others it does not? Any solutions?
Thanks,
Fabian