---
title: "SuperWorld Plot Sales"
output: 
  flexdashboard::flex_dashboard:
    orientation: rows
    social: menu
    source_code: embed
---

Inputs {.sidebar}
-------------------------------------
More than half of plots sold are located in the United States, most notably in New York, California, Texas, and Nevada

```{r setup, include=FALSE}
library(flexdashboard)
library(leaflet)
library(htmltools)
library(leaflet.extras)
library(datasets)
library(sf)
library(crosstalk)
library(tidyverse)
library(reactable)
library(rnaturalearth)
library(rnaturalearthdata)
library(plotly)

load("~/SuperWorld/dashboard1_workspace.RData")
sold = read_csv("C:/Users/tzipo/SuperWorld_Plot_Recommendation/data/plots_sold.csv")

# plots_sold = unique(merge(sold, plots, by = c("lat", "lon"), all.x = TRUE))
# 
# 
# us_address = plots_sold[which(plots_sold$code == "US"),]$address
# 
# state = c()
# for (i in 1:length(us_address)){
#   add = unlist(str_split(us_address[i], pattern = ", "))
#   state = c(state, add[length(add) - 1])
# }
# for (i in 1:length(state)){
#   if (state[i] == "New Jersey") {
#     state[i] = "NJ"
#   }
#   else if (state[i] == "New York") {
#     state[i] = "NY"
#   }
#   else if (state[i] == "District of Columbia") {
#     state[i] = "DC"
#   }
#   else {
#     add = unlist(str_split(state[i], pattern = " "))
#     state[i] = add[1]
#   }
# }
# 
# state = ifelse(state == "Louisiana", "LA",
#                ifelse(state == "California", "CA",
#                       ifelse(state == "Missouri", "MO",
#                              ifelse(state == "Illinois", "IL", 
#                                     ifelse(state == "Utah", "UT", state)))))
```

Row {data-height=600}
-------------------------------------
    
### Plots Sold Across the World

```{r}
# world = ne_countries(scale = "medium", returnclass = "sf")
# df = st_sf(merge(plots_sold, world, by.x = "code", by.y = "iso_a2", all.x = TRUE, all.y = TRUE, returnclass = "sf"))
# 
# 
# df = df %>%
#     group_by(country) %>%
#     summarise(sold = n()) %>%
#     mutate(sold = ifelse(sold == 443, 0, sold)) %>%
#     ggplot() +
#       geom_sf(aes(fill = log(sold)))

ggplotly(df)
```


   
Row 
-------------------------------------
   
### Plot Locations

```{r}
leaflet(plots_sold) %>% 
  addTiles() %>% 
  addCircles(lng = ~lon, lat = ~lat) %>% 
  setView(lat = 37.0902, lng = -95.7129, zoom = 4)
```   
 
### Plots Sold in the US

```{r}
library(usmap)

# state_data = data.frame(state) %>%
#   group_by(state) %>%
#   summarise(sold = n())
#   
# us = plot_usmap(data = state_data, values = "sold", regions = "states") +
#   theme(legend.position = "right") +
#   scale_fill_continuous(name = "Plots Sold")
  
ggplotly(us)

```