---
title: "Invertebrados Marinos Golfo Nuevo"
output: 
  flexdashboard::flex_dashboard:
    theme: lumen
    social: menu
    source: embed
    logo: https://www.proyectosub.org.ar/wp-content/uploads/2020/04/logoinatproyectosub.png
---

```{r setup, include=FALSE}
library(flexdashboard)
library(leaflet)
library(ggplot2)
library(plotly)
library(spocc)
library(rinat)
library(mapr)


library(RColorBrewer)
palette(brewer.pal(8, "Set2"))


```

```{r dataread, message=FALSE, warning=FALSE, include=FALSE}


#Extract data from the project "biodiversidad-marina-bahia-pardelas"
#projecy_info <- pardelas_obs <- get_inat_obs_project("biodiversidad-marina-bahia-pardelas", type = "info", raw = FALSE)

#extract observations
#pardelas_obs <- get_inat_obs_project(projecy_info$id, type = "observations")

#create data frame with reduced info
#pardelas_obs_dataframe <- data.frame(name = pardelas_obs$taxon.name,longitude = as.numeric(pardelas_obs$longitude),latitude = as.numeric(pardelas_obs$latitude),user=pardelas_obs$user_login,date= as.Date(pardelas_obs$observed_on), taxonrank=pardelas_obs$taxon.rank,taxonid=pardelas_obs$taxon.id,taxon= pardelas_obs$iconic_taxon.name, stringsAsFactors = FALSE)

#As some of the taxon information  (eg Phylum) is not included in the rinat package we proceed to import data from csv. the package "spocc" shoul be explored for download data.

#Read data downloaded from inat site 
pardelas_obs_web <- read.csv("observations-GN_MAY27.csv")

#we create a dataframe with the variable of interest.
pardelas_obs_dataframe <- data.frame(
name = pardelas_obs_web$scientific_name,
longitude = pardelas_obs_web$longitude,
latitude = pardelas_obs_web$latitude,
user=pardelas_obs_web$user_login,
date= as.Date(pardelas_obs_web$observed_on),
taxonid=pardelas_obs_web$id,
taxon= pardelas_obs_web$iconic_taxon_name,
kindom= pardelas_obs_web$taxon_kingdom_name,
phylum=pardelas_obs_web$taxon_phylum_name,
class=pardelas_obs_web$taxon_class_name,
order=pardelas_obs_web$taxon_order_name,
genus=pardelas_obs_web$taxon_genus_name,
stringsAsFactors = FALSE)

#add year from date info
pardelas_obs_dataframe$year <- as.numeric(format(pardelas_obs_dataframe$date,"%Y"))

obs_byyear = as.data.frame(table(pardelas_obs_dataframe$year))
colnames(obs_byyear)=c("Año","Observaciones") 

```


Column1{data-width=250}
-------

### Tabla Observaciones {data-width=245}
```{r taxalist}
knitr::kable(as.data.frame(table(reorder(pardelas_obs_dataframe$name,rep(-1,length(pardelas_obs_dataframe$name)),sum))),col.names = c("Especies","Observaciones"))

```


Column2 {.tabset .tabset-fade}
-------

### Mapa
```{r map}
map_leaflet(pardelas_obs_dataframe,size=4) %>% 
  addMiniMap(toggleDisplay = T)
```


### Phylum 
```{r donut}
##numbers of observations by phylum 
taxranks = as.data.frame(table(pardelas_obs_dataframe$phylum))
##Donut plot
p = taxranks %>% plot_ly(labels = ~Var1, values=~Freq) %>% 
  add_pie(hole=0.6) %>% 
  layout(title = ~paste0("Numero total de Taxa: ", length(unique(pardelas_obs_dataframe$taxonid)))) 

plotly::config(p,displayModeBar = F) 
```

### Observaciones por año
```{r obsbyyear}
#plot number of observation by date 
ggplot(obs_byyear, aes(x=Año,y=Observaciones,group=1)) + geom_line() + geom_point()+ xlab("Año") + ylab("Observaciones") + theme_minimal()

```

### Especies exóticas 
```{r exotic, include=FALSE}
#based on https://alexis-catherine.github.io/visualization/inaturalist-invasive-bubble-plot/
library(curlconverter)
library(tidyverse)
library(ggraph)
library(packcircles)
library(lubridate)

iconic_name <- NULL
name <- NULL
common <- NULL
months <- NULL 
place_name <- "Golfo Nuevo"
proyect_id <- "invertebrados-marinos-golfo-nuevo"
#extract observation of "invertebrados-marinos-golfo-nuevo" project 

api <- paste("curl -X GET --header 'Accept: application/json' 'https://api.inaturalist.org/v1/observations?endemic=false&geo=true&introduced=true&project_id='", proyect_id, "&quality_grade=research&per_page=200&order=desc&order_by=created_at'", sep = "")

my_ip <- straighten(api) %>% 
    make_req()
dat <- content(my_ip[[1]](), as="parsed")

for(i in 1:length(dat$results)){
  iconic_name <- c(iconic_name, dat$results[[i]]$taxon$iconic_taxon_name)
  name <- c(name,dat$results[[i]]$taxon$name)
  if(is.null(dat$results[[i]]$taxon$preferred_common_name)){
    common <- c(common, NA)}else{
      common <- c(common, dat$results[[i]]$taxon$preferred_common_name)}
}
if (dat$total_results > 200){
  for (i in 2:floor(dat$total_results/200)){
    api <- paste("curl -X GET --header 'Accept: application/json' 'https://api.inaturalist.org/v1/observations?endemic=false&geo=true&introduced=true&place_id='", place_id, "&quality_grade=research&page=", i, "&per_page=200&order=desc&order_by=created_at'", sep = "")
    my_ip <- straighten(api) %>% 
      make_req()
    dat <- content(my_ip[[1]](), as="parsed")
    for(j in 1:length(dat$results)){
      iconic_name <- c(iconic_name, dat$results[[j]]$taxon$iconic_taxon_name)
      name <- c(name,dat$results[[j]]$taxon$name)
      if(is.null(dat$results[[j]]$taxon$preferred_common_name)){
        common <- c(common, NA)}else{
          common <- c(common, dat$results[[j]]$taxon$preferred_common_name)}
    }
  }
}


dat2 <- dat
dat2 <- data.frame(iconic_name,name,common)

dat2 %>% 
  group_by(name, iconic_name) %>%
  summarise(n = n()) -> data
names(data) <- c("group", "iconic", "value")

packing <- circleProgressiveLayout(data$value, sizetype='area')
data <- cbind(data, packing)
dat.gg <- circleLayoutVertices(packing, npoints=50)
dat.gg$group <- rep(data$iconic, each = 51)

```

```{r exotic2}
# Make the plot
ggplot() + 
  # Make the bubbles
  geom_polygon(data = dat.gg, aes(x, y, group = id), fill="chartreuse3",colour = "black", alpha = 0.6) +
  # Add text in the center of each bubble + control its size
  geom_text(data = data, aes(x, y, size=value, label = group),fontface = "italic") +
  scale_size_continuous(range = c(1,5), guide = F) +
  # General theme:
  theme_void() + 
  theme() +
  coord_equal() + 
  ggtitle(paste("Especies exóticas de", place_name)) +
  theme(plot.title = element_text(size = 12, face = "bold")) + 
  labs(caption ="El tamaño del circulo representa la cantidad de observaciones.\n Source code:https://alexis-catherine.github.io/") + 
  theme(legend.position = "none")+
  theme(plot.title = element_text(hjust = 0.5))
```

Column3{data-width=150}
-------

### Números
```{r}
#spp 
nspp = length(unique(pardelas_obs_dataframe$name))
gauge(nspp, min=0, max=200,label="Species")

```