---
title: "Craywatch dashboard"
output: 
  flexdashboard::flex_dashboard:
    theme:
      version: 4
      bg: "#ffffff"
      fg: "#356196" 
      primary: "#c04384"
      navbar-bg: "#000000"
      # within `theme` you can set a lot more than just colors!
      base_font:
        Cailibri
      heading_font:
        Sans Pro
    # If vertical layout: `scroll` the table is not rendered properly
    vertical_layout: fill
    source_code: embed
---

```{r setup, include=FALSE}
library(tidyverse)      # to do datascience
library(here)           # to work easily with paths
library(sf)             # to work with geospatial vector data
library(leaflet)        # to make dynamic maps
library(DT)             # to make interactive tables
library(flexdashboard)  # to make dashboards
```


```{r load_data, include=FALSE}
cray_df <- readr::read_tsv(
  here::here("data", "20250224", "20250224_craywatch_cleaned.txt"),
  na = "",
  guess_max = 10000
)
```


Citizen science {data-orientation=rows}
=====================================  

Row
-------------------------------------

### Craywatch related data
    
```{r}
# Number of observations linked to craywatch (via waarnemingen.be)
dataset_name <- "Waarnemingen.be - Non-native animal occurrences in Flanders and the Brussels Capital Region, Belgium"
n_obs_craywatch <- cray_df %>%
  filter(datasetName == dataset_name) %>%
  nrow()
tot_obs <- nrow(cray_df)
percentage_craywatch <- n_obs_craywatch / tot_obs * 100
gauge(min = 0,
      max = tot_obs,
      value = n_obs_craywatch, label = "waarnemingen.be")
```

### Number of observations via waarneemingen.be

```{r}
# Number of observations
valueBox(n_obs_craywatch, icon = "ion-android-camera")
```


Row
-------------------------------------

### Number of observations per dataset

```{r}
n_obs_per_dataset <- cray_df %>%
  count(datasetName) %>%
  arrange(desc(n)) %>%
  # Abbreviate the dataset names
  mutate(datasetName = case_when(
    datasetName == "Waarnemingen.be - Non-native animal occurrences in Flanders and the Brussels Capital Region, Belgium" ~ "Waarnemingen.be",
    datasetName == "RATO - Daily operations commissioned by the province East Flanders, Belgium" ~ "RATO",
    datasetName == "Invasive species - American bullfrog (Lithobates catesbeianus) in Flanders, Belgium (post 2018)" ~ "American bullfrog ( INBO)",
    datasetName == "iNaturalist research-grade observations" ~ "iNaturalist",
    datasetName == "Monitoring of fishes and crustaceans by Province East Flanders in Flanders, Belgium" ~ "Monitoring POV",
    TRUE ~ stringr::str_trunc(.data$datasetName, 20)
  ))
# Plot the number of observations per dataset
ggplot(n_obs_per_dataset, aes(x = reorder(datasetName, n), y = n)) +
  geom_col(fill = "steelblue") +
  coord_flip() +
  # Add title and labels
  ggtitle("Number of observations per dataset") +
  ylab("Number of observations") + xlab("Dataset")
```



Taxonomic and temporal distribution
=====================================     
   
### Number of observations per month
    
```{r}
n_obs_per_month_species <-
  cray_df %>%
  count(year, month, species) %>%
  # combine year and month to a single date
  mutate(date = as.Date(paste0(year, "-", month, "-01"))) %>%
  arrange(date, species) %>%
  relocate(date,species, n, everything())
ggplot(n_obs_per_month_species,
       aes(x = date, y = n, fill = species)) +
  geom_bar(stat = 'identity') +
  # Use inferno colors for the species
  scale_fill_viridis_d(option = "inferno") +
  # Add title and labels
  ggtitle("Number of observations per month and species") +
  xlab("Date") + ylab("Number of observations")
```


### Distribution of observations

```{r}
cray_fl <- sf::st_as_sf(cray_df,
                        coords = c("decimalLongitude", "decimalLatitude"),
                        crs = 4326)

# Create a palette that maps species to colors
pal <- colorFactor("inferno", cray_fl$species)
leaflet(cray_fl) %>%
  addTiles() %>%
  addCircleMarkers(popup = ~paste0(cray_fl$eventDate, ": ", cray_fl$species),
                   color = pal(cray_fl$species),
                   stroke = FALSE,
                   fillOpacity = 0.5,
                   radius = 4) %>%
  addLegend(pal = pal, values = ~species,
            position = "bottomright")
```

Explore the data
=====================================

### Explore the data

```{r}
DT::datatable(cray_df)
```