1 tldr

I recommend ggplotly() for quick interactive plots. And {highcharter} for more polished dashboard plots.

2 ggplot

# Load packages 
if(!require(pacman)) install.packages("pacman")
pacman::p_load(tidyverse, plotly, highcharter)

p <- ggplot(iris, 
       aes(x = Sepal.Length, y = Sepal.Width, color = Species)) +
  geom_point() + 
  facet_wrap(~ Species) + 
  labs(title = "A title for my plot", 
       color = "A custom label", 
       caption = "A caption for my plot")

p

3 Easy plotly

Use the ggplotly() function. Plotly is hard to make beautiful though, in my experience.

ggplotly(p)

4 Beautiful highcharter

First a basic plot.

highchart() %>% 
  hc_add_series(data = iris, type = "scatter", 
                hcaes(x = Sepal.Length, 
                      y = Sepal.Width, 
                      color = Species)) %>%
  hc_xAxis(title = list(text = "Sepal.Length")) %>%
  hc_yAxis(title = list(text = "Sepal.Width")) %>%
  hc_title(text = "A title for my beautiful plot") %>%
  hc_subtitle(text = "A subtitle for my wonderful plot") %>%
  hc_add_theme(hc_theme_flat()) %>%
  hc_credits(enabled = TRUE, text = "custom caption")

To get facets you need to do a bit of work.

# Create a list of plots, one for each species
list_of_plots <- map(unique(iris$Species), function(x) {
  
  # Filter the data to only include the current species
  filtered <- iris %>% filter(Species == x)
  spec_color <- c("setosa" = "#2074bd", 
                  "virginica" = "#cc5a74", 
                  "versicolor" = "#51a898")[[x]]
  
  # Create a chart with the filtered data
  highchart() %>%
    hc_add_series(data = filtered, type = "scatter", 
                  hcaes(x = Sepal.Length, y = Sepal.Width), 
                  color = spec_color) %>%
    hc_xAxis(title = list(text = "Sepal.Length")) %>%
    hc_yAxis(title = list(text = "Sepal.Width")) %>%
    hc_title(text = x) %>%
    hc_add_theme(hc_theme_flat()) %>%
    hc_legend(enabled = FALSE) %>%
    hc_credits(enabled = TRUE, text = "custom caption")

})

# Use the hw_grid() function to combine the charts
hw_grid(list_of_plots, rowheight = 300) %>%
  htmltools::browsable()

Here is a highcharter showcase: https://jkunst.com/highcharter/articles/showcase.html

Here is a highcharter tutorial: https://www.tmbish.me/lab/highcharter-cookbook/