---
title: "Crosstalk + Layers"
output: 
  flexdashboard::flex_dashboard:
    orientation: rows
    source_code: embed
    social: [ "twitter", "facebook", "menu" ]
---

```{r setup, include=FALSE}
# crosstalk03
  # adds layer of zipcode boundaries of zips with mean income >= $200k


knitr::opts_chunk$set(echo = FALSE)

library(tidyverse)
library(leaflet)
library(DT)
library(plotly)
library(crosstalk)
library(rgdal)
library(rgeos)

```

```{r data}
# load example data
df <- read_csv("https://raw.githubusercontent.com/majerus/NEDRA2018/master/example.csv")

# clean example data
df <- 
  df %>% 
    filter(!is.na(officer)) %>% 
    filter(status != "Not a Prospect") %>% 
    select(name, class, constituency, connection, status,  priority, cap16, officer, latitude, longitude)

# Wrap data in SharedData to use with crosstalk
sd <- SharedData$new(df)
```


Inputs {.sidebar}
-------------------------------------

```{r filters}
# Filter input - Officer
filter_select(id = "officer", 
              label = "Select Gift Officer(s)",
              sharedData = sd, 
              group = ~officer)

# Filter input - Status
filter_select(id = "status", 
              label = "Select Status",
              sharedData = sd, 
              group = ~status)


# Filter checkbox - constituency
filter_checkbox(id = "cons", 
                label = "Constituency",
                sharedData = sd, 
                group = ~constituency,
                inline = TRUE)

# Filter slider - capital giving 2016
filter_slider(id = "giving", 
              label = "2016 Giving",
              sharedData = sd, 
              column = ~cap16)
```


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

### Map

```{r map_prep, include=FALSE}
# mapping polygons 
# load geojson for zipcodes with mean income of $200k+
wealthy_zips <- readOGR("https://raw.githubusercontent.com/majerus/NEDRA2018/master/wealthiest_100_zipcodes_geojson.GeoJSON", "OGRGeoJSON")
```

```{r map}
sd %>% 
  leaflet() %>% 
    addProviderTiles("CartoDB") %>% 
  setView(lat = 39.8282, lng = -98.5795, zoom = 4) %>% 
    addCircleMarkers(popup = ~name, group = "Prospects", radius = 2) %>% 
    addPolygons(data=wealthy_zips,
                fillColor = "Green",
                weight = 2,
                opacity = 1,
                color = "Green",
                dashArray = "3",
                fillOpacity = .7,
                group = "Boundaries") %>% 
  addLayersControl(
    overlayGroups = c("Prospects", "Boundaries")) 
```

### Chart 

```{r plot}
plot_ly(sd, x = ~status) %>% add_histogram()
```

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

### Table

```{r table}
datatable(sd, extensions= c('Buttons', "Scroller"), 
          class="compact", width="100%", rownames = FALSE, 
            options=list(
              dom = 'Blfrtip',
              deferRender=TRUE, 
              scrollY=300,
              scroller=TRUE, 
              columnDefs = list(list(visible=FALSE, targets=c(8, 9))), 
              buttons = list(I('colvis'), 'csv', 'excel'))) %>% 
formatCurrency('cap16', digits = 0)  
```