In leppott/ContDataSumViz: Create Visualizations of Continuous Monitoring Data

Species `r child_env$species`

library(ggplot2)
library(dplyr)
library(palmerpenguins)
library(tidyr)
library(plotly)
library(DT)
knitr::opts_chunk$set(echo = FALSE)

# Filter the penguins data by species
#data <- filter(penguins, species == species)

plot_species <- filter(penguins, species == child_env$species) %>%
  ggplot(aes(x = bill_length_mm, y = bill_depth_mm)) +
  geom_point(na.rm = TRUE) +
  labs(title = child_env$species)
plotly::ggplotly(plot_species)

df_species <- filter(penguins, species == child_env$species) %>% 
  pivot_longer(ends_with("mm"),
               names_to = "cols",
               values_to = "mm", 
               values_drop_na = TRUE) %>% 
  group_by(cols) %>% 
  summarise(across(mm, 
                   .fns = list(mean = mean, 
                               min = min, 
                               max = max,
                               N = length),
                    .names = "{.fn}")
  )
DT::datatable(df_species, caption = child_env$species)