I am trying to plot two plotly
plots together in R
using plotly::subplot
. The problem is subplot doesn't show the titles
of both the plots
. Other answers to similar questions recommend either using facet_wrap
or plot_ly
, but I am looking for a solution that works with ggplotly
.
How can this be fixed?
Sample data with code:
library(tidyverse)
library(plotly)
# Sample Data
Group_1_2020 = data.frame(Code = c("A", "B", "C"),
Count_2020 = c(1,2,3))
Group_2_2020 = data.frame(Code = c("D", "E", "F"),
Count_2020 = c(4,5,6))
Group_1_2021 = data.frame(Code = c("A", "B", "C"),
Count_2021 = c(4, 8, 6))
Group_2_2021 = data.frame(Code = c("D", "E", "F"),
Count_2021 = c(8, 10, 12))
# Merge Datasets
DF_Merged_1 =
inner_join(Group_1_2020, Group_1_2021)
DFF_Merged_1 = DF_Merged_1 %>% dplyr::select(Code, Count_2020, Count_2021) %>%
gather(key = Type, value = Value, -Code) %>%
mutate(Type = ifelse(Type == "Count_2020", "2020", "2021"))
DF_Merged_2 =
inner_join(Group_2_2020, Group_2_2021)
DFF_Merged_2 = DF_Merged_2 %>% dplyr::select(Code, Count_2020, Count_2021) %>%
gather(key = Type, value = Value, -Code) %>%
mutate(Type = ifelse(Type == "Count_2020", "2020", "2021"))
# ggplot
ggplot_1 = DFF_Merged_1 %>%
ggplot(aes(x = reorder(Code,Value), y = Value, fill = Type,
text = paste("Count:", Value,
"<br>", "Offense Code:", Code,
"<br>", "Year:", Type))) +
geom_col(position = "dodge", show.legend = FALSE) +
xlab("Offense Code") +
ylab("Count") +
ggtitle("Arrest Counts for Group 1 in Year 2020 and 2021") +
theme(axis.text=element_text(size=8))
ggplot_2 = DFF_Merged_2 %>%
ggplot(aes(x = reorder(Code,Value), y = Value, fill = Type,
text = paste("Count:", Value,
"<br>", "Offense Code:", Code,
"<br>", "Year:", Type))) +
geom_col(position = "dodge", show.legend = FALSE) +
xlab("Offense Code") +
ylab("Count") +
ggtitle("Arrest Counts for Group 2 in Year 2020 and 2021") +
theme(axis.text=element_text(size=8))
# Interactive Plots
fig1 = ggplotly(ggplot_1, tooltip = "text")
fig2 = ggplotly(ggplot_2, tooltip = "text")
subplot(fig1, fig2)
You can use annotations
:
library(plotly)
gg1 <- ggplot(iris, aes(x = Sepal.Length, y = Sepal.Width)) + geom_point()
gg2 <- ggplot(iris, aes(x = Petal.Length, y = Petal.Width)) + geom_point()
pp1 <- ggplotly(gg1)
pp2 <- ggplotly(gg2)
subplot(pp1, pp2, margin = 0.05) %>%
layout(annotations = list(
list(x = 0.2 , y = 1.1, text = "Title 1", showarrow = FALSE, xref='paper', yref='paper'),
list(x = 0.8 , y = 1.1, text = "Title 2", showarrow = FALSE, xref='paper', yref='paper'))
)
As an alternative to subplot
, you can use manipulateWidget::combineWidgets
:
gg1 <- ggplot(iris, aes(x = Sepal.Length, y = Sepal.Width)) +
geom_point() + ggtitle("Title1")
gg2 <- ggplot(iris, aes(x = Petal.Length, y = Petal.Width)) +
geom_point() + ggtitle("Title2")
pp1 <- ggplotly(gg1)
pp2 <- ggplotly(gg2)
manipulateWidget::combineWidgets(pp1, pp2, nrow = 1)
Then, instead of renderPlotly
and plotlyOutput
, you have to use renderCombineWidgets
and combineWidgetsOutput
- see combineWidgets-shiny.