library(simplevis)
library(dplyr)
library(palmerpenguins)Introduction
simplevis provides gglot2 (and leaflet) wrapper functions with an objective to help users make beautiful visualisation with less brainpower.
In the current post, we discus how to make yoursimplevis ggplot2 plots interactive html widgets using plotly::ggplotly, including how to fine-tune your tooltips.
Turning a ggplot into an interactive html widget
The plotly::ggplotly function provides the ability to convert the ggplot object to an interactive plotly html object.
Given that simplevis functions are generally ggplot2 wrapper functions that output ggplot2 objects, we can use this plotly::ggplotly function on our output object to make it interactive.
This is pretty magical, as it is just so easy - thanks plotly!
plot <- gg_point_col(penguins,
x_var = bill_length_mm,
y_var = body_mass_g,
col_var = species)
plotly::ggplotly(plot) Turning off widgets other than the camera
The plotly widgets can sometimes look a bit cluttered, especially you are not using them.
Therefore, simplevis provides a plotly_camera function to turn off all widgets other than the camera.
plot <- gg_point_col(penguins,
x_var = bill_length_mm,
y_var = body_mass_g,
col_var = species)
plotly::ggplotly(plot) %>%
plotly_camera()Controlling the tooltip
Some users may want to have more or different variables in the tooltip than plotly::ggplotly defaults provide.
plotly::ggplotly provides a method for this which simplevis uses.
In the simplevis gg_* function, users can add a variable can be added to the text_var that can be used as the tooltip (for functions other than gg_density*() and gg_boxplot*()).
This variable is then used in the ggplotly tooltip when tooltip = text is added to the ggplotly function.
simplevis provides a mutate_text function which makes it easy to create a column that is a string of variable names and associated values separated by breaks for the tooltip.
This function creates a new column called text that can then be added to the text_var in the gg*() function.
If no column names are provided in a vector to mutate_text, then it defaults to providing all variable names and associated values in the dataset.
plot_data <- penguins %>%
mutate_text()
plot <- gg_point_col(plot_data,
x_var = bill_length_mm,
y_var = body_mass_g,
col_var = species,
text_var = text)
plotly::ggplotly(plot, tooltip = "text") %>%
plotly_camera()A vector of column names can be provided to mutate_text function to get the exact arguments that the user in looking for. Note mutate_text converts column names to sentence case using the snakecase::to_sentence_case function.
plot_data <- penguins %>%
mutate_text(c("species", "flipper_length_mm"))
plot <- gg_point_col(plot_data,
x_var = bill_length_mm,
y_var = body_mass_g,
col_var = species,
text_var = text)
plotly::ggplotly(plot, tooltip = "text") %>%
plotly_camera()You can also use this method if you were using ggplot2.
library(ggplot2)
plot_data <- penguins %>%
mutate_text()
plot <- ggplot(plot_data) +
geom_point(aes(x = bill_length_mm,
y = body_mass_g,
col = species,
text = text))
plotly::ggplotly(plot, tooltip = "text") %>%
plotly_camera()