Select intputs to filter the data.
Filter the data to update the pie charts.
Filter the data to update the pie charts.
Select intputs to filter the data.
Licenses
---
title: "Cannabis Reparations"
output:
flexdashboard::flex_dashboard:
orientation: columns
theme: cosmo
vertical_layout: fill
source: embed
social: [ "twitter", "facebook" ]
logo: cannabisreparations1.ico
---
```{r setup, include=FALSE}
library(flexdashboard)# interactive dashboard
library(readxl) # import excel data set
library(leaflet) #create interactive maps
library(tidyverse) # load core packages for data visualisation (dplyr:for data manipulation, tidyr:for data tidying, readr:for data import, purrr:for functional programming, tibble:for tibbles, a modern re-imagining of data frames, stringr:for strings, forcats:for factors)
library(DT) #Display data tables
library(crosstalk) # extends htmlwidgets
library(sf) #load shapefiles
library(RColorBrewer) # color palaette
library(geojsonR) # need for geolines
library(shiny)
library(plyr)
library(plotly)
library(lubridate)
library(ggplot2)
library(sp)
library(icon)
library(emojifont)
library(geosphere)
```
```{r data, include=FALSE}
# Load Cannabis Data
Applications <- read_csv("Apps.csv")
License <- read_csv("Lic.csv")
Authority_Entities <- read_csv("AE.csv")
Business_Interets <- read_csv("BI.csv")
Geolines <- read_csv("Geolines.csv")
Applications$combo <- paste(Applications$Application_Status, Applications$Priority_Status,Applications$DBE_Category, Applications$License_Type, sep = "-")
Applications$Date_Created <- as.Date(Applications$Date_Created, format = "%m/%d/%y")
License$Date_Created <- as.Date(License$Date_Created, format = "%m/%d/%y")
License$Date_Submitted <- as.Date(License$Date_Submitted, format = "%m/%d/%y")
License$Date_Final_Licensure <- as.Date(License$Date_Final_Licensure, format = "%m/%d/%y")
# Load Shape Data
ADI_Merged_shape <-st_read("Cannabis_ADI_shape/Cannabis_ADI_shape.shp", stringsAsFactors=FALSE, quiet=TRUE)
ADI_Merged_shape <-st_transform(ADI_Merged_shape,'+proj=longlat +datum=WGS84')
Authority_Entities <- Authority_Entities %>%
mutate(AutAboxinfo = paste0('Authority Name: ', Full_Name, '
',
'Role: ', Role, '
',
'Ownership: ', Ownership, '
',
'Control: ', Control, '
',
'Business Name: ', Business_Name, '
',
'License Status: ', License_Status, '
',
'Priority Status: ', Priority_Status, '
',
'License Type: ', License_Type, '
',
'DBE Category: ', DBE_Category, '
',
'Business Address: ', Business_Address, '
',
'Total Authority Agents: ', Total_Authority_Agents, '
'))
Business_Interets <- Business_Interets %>%
mutate(BIboxinfo = paste0('Authority Name: ', Full_Name, '
',
'Role: ', Role, '
',
'Business Name: ', Business_Name, '
',
'License Status: ', License_Status, '
',
'Priority Status: ', Priority_Status, '
',
'License Type: ', License_Type, '
',
'DBE Category: ', DBE_Category, '
',
'Business Address: ', Business_Address, '
',
'Total Authority Agents: ', Total_Authority_Agents, '
'))
# Generate geolines data
flows <- gcIntermediate(Geolines[,2:3], Geolines[,5:6], sp = TRUE, addStartEnd = TRUE)
flows$Business_Name <- Geolines$business.name
flows$Total_Agents <- Geolines$total.agents
flows$Layer <- Geolines$layer
flows$Ownership <- Geolines$ownership
flows$Control <- Geolines$control
# created shared data for geolines
flows_sd <-SharedData$new(flows)
sd_df <- SharedData$new(flows@data, group = flows_sd$groupName())
# create hover information for geolines
hover <- paste0(flows_sd$data()$Business_Name, " to ",
flows_sd$data()$Priority_Status, ': ',
flows_sd$data()$DBE_Category, " | ",
as.character(flows_sd$data()$Total_Agents))
# Create sharedDataFrames
App_sd <-SharedData$new(Applications, group = "Applications")
Lic_sd <-SharedData$new(License, group = "Licenses")
AE_sd <-SharedData$new(Authority_Entities, group = "Entities")
BI_sd <-SharedData$new(Business_Interets, group = "Interests")
ADI_sd <- SharedData$new(ADI_Merged_shape, group = "ADI")
ADI_sd_df <- SharedData$new(as.data.frame(ADI_Merged_shape), group = ADI_sd$groupName())
```
ADI {data-icon="fa-cannabis"}
=====================================
Column {data-width=300}
-----------------------------------------------------------------------
### A Geospatial Equity Analysis
```{r}
# What is a Geospoatioanl Equity Analysis
# What varibales are we exploring
```
Row {data-width=400}
-----------------------------------------------------------------------
### Areas of Disproportionate Impact (ADI)
```{r}
# Who are they and what are some overview charracsterics
```
Row {data-width=300}
-----------------------------------------------------------------------
### Industry Equity
```{r}
# Application Data vs Municupliaty Data
# add HTML link that directs folks to the MCCC data catelog
```
Applications {data-icon="fa-cannabis"}
=====================================
Column {data-width=200 .tabset .tabset-fade .colored}
-----------------------------------------------------------------------
### Applications
> Select intputs to filter the data.
```{r app town filter}
filter_select("Business_Town", "Select Town", App_sd, ~Business_Town)
```
```{r app county filter}
filter_select("Business_County", "Select a County", App_sd, ~Business_County)
```
```{r app prioirty status filter}
filter_checkbox("Priority_Status", "Priority Status", App_sd, ~Priority_Status, allLevels = TRUE)
```
```{r app applicatin status filter}
filter_checkbox("Application_Status", "Application Status", App_sd, ~Application_Status, allLevels = TRUE)
```
```{r app license type filter}
filter_select("License_Type","License Type", App_sd, ~License_Type)
```
```{r app date created filter}
```
```{r app total applications fitler}
filter_slider("Total_Apps", "Total Applications", App_sd, ~Total_Apps, step = 1)
```
```{r app dbe category filter}
filter_select("DBE_Category","DBE Category", App_sd, ~DBE_Category)
```
```{r app business name filter}
filter_select("Business_Name","Search Business Name ", App_sd, ~Business_Name)
```
### ADI
```{r adi filter}
filter_checkbox("Imp_C", "Area of Disproportionate Impact (ADI)", ADI_sd_df, ~Imp_C)
```
```{r aus filter}
filter_select("A_U_S", "Adult Use Status", ADI_sd_df, ~A_U_S)
```
```{r delivery filter}
filter_select("Dlv_A", "Delivery", ADI_sd_df,~Dlv_A)
```
```{r social consumption filter}
filter_select("S_C_P", "Social Consumption", ADI_sd_df,~S_C_P)
```
Column {data-width=650 .tabset .tabset-fade .colored}
-----------------------------------------------------------------------
### Map
```{r app map}
appPSpal <- colorFactor(palette = c("#2ca02c", "#bcbd22"), App_sd$Application_Status, na.color = "#808080", alpha = TRUE)
leaflet() %>%
setView(-71.931180, 42.385453, zoom = 8) %>%
addProviderTiles("CartoDB.DarkMatter", group = "Dark") %>%
addProviderTiles("Esri.WorldGrayCanvas", group = "Grey") %>%
addPolygons(data = ADI_sd,
weight = .4,
smoothFactor = 1,
fillOpacity = ifelse(test = ADI_sd$Imp_C == "Impact", yes = .5, no = 0),
color = "#878787",
fillColor = "#17b502",
label = ~Town_1, # name as a hover label
group = "ADI") %>%
addCircleMarkers(data = App_sd,
lng = ~longitude,
lat = ~latitude,
popup = ~Appboxinfo,
fillOpacity = ifelse(test = App_sd$data()$Priority_Status == "Economic Empowerment", yes = 1, no = 0),
fillColor = "red",
color = ~appPSpal(Application_Status),
radius = App_sd$data()$Total_Apps*2.5,
group = "Applications") %>%
addLegend("bottomleft",
pal = appPSpal,
values = App_sd$data()$Application_Status,
title = "Applications Status",
opacity = 1) %>%
addLayersControl(overlayGroups = c("ADI","Applications"),
baseGroups = c("Dark","Grey", "Applications"),
options = layersControlOptions(collapsed = FALSE)) %>%
addMeasure()
```
### Data
```{r app data table}
datatable(App_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')))
```
### Equity
```{r app equity }
# Summary break down with static charts and detailed descritpiton explaining what the data is telling us
```
ADI vs Non_ADI value boxes
```{r}
```
Column {data-width=350 .tabset .tabset-fade .colored}
-----------------------------------------------------------------------
### Applications
Filter the data to update the pie charts.
```{r app priority status pie}
div(
div(plot_ly(App_sd,
labels = ~ Application_Status,
values = ~ Total_Apps,
type = 'pie',
marker = list(colors = c('#bcbd22', '#2ca02c')),
textposition = 'inside',
textinfo = 'label+percent',
showlegend=F) %>%
layout(legend = list(orientation ="h", xanchor = "center", x = 0.5, y = -0.1))),
div(plot_ly(App_sd,
labels = ~ Priority_Status,
values = ~ Total_Apps,
type = 'pie',
textposition = 'inside',
textinfo = 'label+percent',
showlegend=F) %>%
layout(legend = list(orientation ="h", xanchor = "center", x = 0.5, y = -0.1)))
)
```
```{r app lic type dbe pie}
div(
div(plot_ly(App_sd,
labels = ~ License_Type,
values = ~ Total_Apps,
type = 'pie',
textposition = 'inside',
textinfo = 'label+percent',
showlegend=F)),
div(plot_ly(App_sd,
labels = ~ DBE_Category,
values = ~ Total_Apps,
type = 'pie',
textposition = 'inside',
textinfo = 'label+percent',
showlegend=F))
)
```
```{r app town county pie}
div(
div(plot_ly(App_sd,
labels = ~ Business_Town,
values = ~ Total_Apps,
type = 'pie',
textposition = 'inside',
textinfo = 'label+percent',
showlegend=F) %>%
layout(title = "Town",legend = list(orientation ="h", xanchor = "center", x = 0.5, y = -0.1))),
div(plot_ly(App_sd,
labels = ~ Business_County,
values = ~ Total_Apps,
type = 'pie',
textposition = 'inside',
textinfo = 'label+percent',
showlegend=F) %>%
layout(title = "County",legend = list(orientation ="h", xanchor = "center", x = 0.5, y = -0.1)))
)
```
### ADI
Filter the data to update the pie charts.
```{r app adi pie}
div(
div(plot_ly(ADI_sd_df,
labels = ~ Imp_C,
values = ~ Ttl_Ap_A,
type = 'pie',
marker = list(colors = c('#bcbd22', '#2ca02c')),
textposition = 'inside',
textinfo = 'percent',
showlegend=F) %>%
layout(title = "Total Applications",legend = list(orientation ="h", xanchor = "center", x = 0.5, y = -0.1))),
div(plot_ly(ADI_sd_df,
labels = ~ Imp_C,
values = ~ Mrjn_Arr_1,
type = 'pie',
marker = list(colors = c('#bcbd22', '#2ca02c')),
textposition = 'inside',
textinfo = 'percent',
showlegend=F) %>%
layout(title = "Total Marijuana Arrests",legend = list(orientation ="h", xanchor = "center", x = 0.5, y = -0.1)))
)
```
```{r app adi msa ctat pie}
div(
div(plot_ly(ADI_sd_df,
labels = ~ Imp_C,
values = ~ M_S_A,
type = 'pie',
marker = list(colors = c('#bcbd22', '#2ca02c')),
textposition = 'inside',
textinfo = 'percent',
showlegend=F) %>%
layout(title = "Marijuana Sale Arrest Rate",legend = list(orientation ="h", xanchor = "center", x = 0.5, y = -0.1))),
div(plot_ly(ADI_sd_df,
labels = ~ Imp_C,
values = ~ C_T_A_T,
type = 'pie',
textposition = 'inside',
marker = list(colors = c('#bcbd22', '#2ca02c')),
textinfo = 'percent',
showlegend=F) %>%
layout(title = "Cannabis Tax Actual Total",legend = list(orientation ="h", xanchor = "center", x = 0.5, y = -0.1)))
)
```
```{r app adi pie}
```
Licenses {data-icon="fa-cannabis"}
=====================================
Column {data-width=200 .tabset .tabset-fade .colored}
-----------------------------------------------------------------------
### License
Select intputs to filter the data.
Licenses
```{r lic town filter}
# App Town filter
filter_select("Business_Town", "Select Town", Lic_sd, ~Business_Town)
```
```{r lic county filter}
# App County filter
filter_select("Business_County", "Select a County", Lic_sd, ~Business_County)
```
```{r lic prioirty status filter}
filter_checkbox("Priority_Status", "Prioirty Status", Lic_sd, ~Priority_Status, allLevels = TRUE)
```
```{r lic status filter}
filter_checkbox("License_Status", "License Status", Lic_sd, ~License_Status, allLevels = TRUE)
```
```{r lic license type filter}
filter_select("License_Type","License Type", Lic_sd, ~License_Type)
```
```{r lic date created filter}
```
```{r lic date submitted filter}
```
```{r lic date approved filter}
```
```{r lic total licenses fitler}
filter_slider("Total_Licenses", "Total Licenses", Lic_sd, ~Total_Licenses, step = 1)
```
```{r lic dbe category filter}
filter_select("DBE_Category","DBE Category", Lic_sd, ~DBE_Category)
```
```{r lic business name filter}
filter_select("Business_Name","Search Business Name ", Lic_sd, ~Business_Name)
```
### ADI
```{r lic adi filter}
filter_checkbox("Imp_C", "Area of Disproportionate Impact (ADI)", ADI_sd_df, ~Imp_C)
```
```{r lic aus filter}
filter_select("A_U_S", "Adult Use Status", ADI_sd_df, ~A_U_S)
```
```{r lic delivery filter}
filter_select("Dlv_A", "Delivery", ADI_sd_df,~Dlv_A)
```
```{r lic social consumption filter}
filter_select("S_C_P", "Social Consumption", ADI_sd_df,~S_C_P)
```
Column {data-width=650 .tabset .tabset-fade .colored}
-----------------------------------------------------------------------
### Map
```{r lic map}
LicPSpal <- colorFactor(palette = c("#2ca02c", "#bcbd22", "#1f77b4"), Lic_sd$License_Status, na.color = "#808080", alpha = TRUE)
leaflet() %>%
setView(-71.931180, 42.385453, zoom = 8) %>%
addProviderTiles("CartoDB.DarkMatter", group = "Dark") %>%
addProviderTiles("Esri.WorldGrayCanvas", group = "Grey") %>%
addPolygons(data = ADI_sd,
weight = .4,
smoothFactor = 1,
fillOpacity = ifelse(test = ADI_sd$Imp_C == "Impact", yes = .5, no = 0),
color = "#878787",
fillColor = "#17b502",
label = ~Town_1, # name as a hover label
group = "ADI") %>%
addCircleMarkers(data = Lic_sd,
lng = ~Lon,
lat = ~Lat,
popup = ~Licboxinfo,
fillOpacity = ifelse(test = Lic_sd$data()$Priority_Status == "Economic Empowerment", yes = 1, no = 0),
fillColor = "red",
color = ~LicPSpal(License_Status),
radius = Lic_sd$data()$Total_Licenses*2.5,
group = "Licenses") %>%
addLegend("bottomleft",
pal = LicPSpal,
values = Lic_sd$data()$License_Status,
title = "License Status",
opacity = 1) %>%
addLayersControl(overlayGroups = c("ADI","Licenses"),
baseGroups = c("Dark","Grey", "Licenses"),
options = layersControlOptions(collapsed = FALSE)) %>%
addMeasure()
```
### Data
```{r lic data table}
# add HTML link that directs folks to the MCCC data catelog
datatable(Lic_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')))
```
### Equity
```{r lic equity }
# Summary break down with static charts and detailed descritpiton explaining what the data is telling us
```
Column {data-width=350 .tabset .tabset-fade .colored}
-----------------------------------------------------------------------
### Licenses
```{r lisc status pie}
div(
div(plot_ly(Lic_sd,
labels = ~ License_Status,
values = ~ Total_Licenses,
type = 'pie',
marker = list(colors = c("#2ca02c", "#bcbd22", "#1f77b4")),
textposition = 'inside',
textinfo = 'label+percent',
showlegend=F) %>%
layout(title = "License Status",legend = list(orientation ="h", xanchor = "center", x = 0.5, y = -0.1))),
div(plot_ly(Lic_sd,
labels = ~ Priority_Status,
values = ~ Total_Licenses,
type = 'pie',
textposition = 'inside',
marker = list(colors = c("#2ca02c", "#bcbd22", "#1f77b4")),
textinfo = 'label+percent',
showlegend=F) %>%
layout(title = "Priority Status",legend = list(orientation ="h", xanchor = "center", x = 0.5, y = -0.1))),
div(plot_ly(Lic_sd,
labels = ~ License_Type,
values = ~ Total_Licenses,
type = 'pie',
textposition = 'inside',
textinfo = 'label+percent',
showlegend=F) %>%
layout(title = "License Type",legend = list(orientation ="h", xanchor = "center", x = 0.5, y = -0.1))),
div(plot_ly(Lic_sd,
labels = ~ DBE_Category,
values = ~ Total_Licenses,
type = 'pie',
textposition = 'inside',
textinfo = 'label+percent',
showlegend=F) %>%
layout(title = "DBE Category", legend = list(orientation ="h", xanchor = "center", x = 0.5, y = -0.1)))
)
```
```{r lic priority status pie}
div(
div(plot_ly(Lic_sd,
labels = ~ Business_Town,
values = ~ Total_Licenses,
type = 'pie',
textposition = 'inside',
textinfo = 'label+percent',
showlegend=F) %>%
layout(title = "Town Licenses",legend = list(orientation ="h", xanchor = "center", x = 0.5, y = -0.1))),
div(plot_ly(Lic_sd,
labels = ~ Business_Town,
values = ~ Application_Fee,
type = 'pie',
textposition = 'inside',
textinfo = 'label+percent',
showlegend=F) %>%
layout(title = "Town Application Fees",legend = list(orientation ="h", xanchor = "center", x = 0.5, y = -0.1))),
div(plot_ly(Lic_sd,
labels = ~ Business_Town,
values = ~ Lic_Fee,
type = 'pie',
textposition = 'inside',
textinfo = 'label+percent',
showlegend=F) %>%
layout(title = "Town License Fees",legend = list(orientation ="h", xanchor = "center", x = 0.5, y = -0.1)))
)
div(
div(plot_ly(Lic_sd,
labels = ~ Business_County,
values = ~ Total_Licenses,
type = 'pie',
textposition = 'inside',
textinfo = 'label+percent',
showlegend=F) %>%
layout(title = "County Licenses",legend = list(orientation ="h", xanchor = "center", x = 0.5, y = -0.1))),
div(plot_ly(Lic_sd,
labels = ~ Business_County,
values = ~ Application_Fee,
type = 'pie',
textposition = 'inside',
textinfo = 'label+percent',
showlegend=F) %>%
layout(title = "County Application Fees",legend = list(orientation ="h", xanchor = "center", x = 0.5, y = -0.1))),
div(plot_ly(Lic_sd,
labels = ~ Business_County,
values = ~ Lic_Fee,
type = 'pie',
textposition = 'inside',
textinfo = 'label+percent',
showlegend=F) %>%
layout(title = "County License Fees",legend = list(orientation ="h", xanchor = "center", x = 0.5, y = -0.1)))
)
```
### ADI
```{r adi lic town pie}
div(
div(plot_ly(ADI_sd_df,
labels = ~ Imp_C,
values = ~ Ttl_Ap_A,
type = 'pie',
marker = list(colors = c('#bcbd22', '#2ca02c')),
textposition = 'inside',
textinfo = 'percent',
showlegend=F) %>%
layout(title = "Total Applications",legend = list(orientation ="h", xanchor = "center", x = 0.5, y = -0.1))),
div(plot_ly(ADI_sd_df,
labels = ~ Imp_C,
values = ~ Mrjn_Arr_1,
type = 'pie',
marker = list(colors = c('#bcbd22', '#2ca02c')),
textposition = 'inside',
textinfo = 'percent',
showlegend=F) %>%
layout(title = "Total Marijuana Arrests",legend = list(orientation ="h", xanchor = "center", x = 0.5, y = -0.1))),
div(plot_ly(ADI_sd_df,
labels = ~ Imp_C,
values = ~ M_S_A,
type = 'pie',
marker = list(colors = c('#bcbd22', '#2ca02c')),
textposition = 'inside',
textinfo = 'percent',
showlegend=F) %>%
layout(title = "Marijuana Sale Arrest Rate",legend = list(orientation ="h", xanchor = "center", x = 0.5, y = -0.1))),
div(plot_ly(ADI_sd_df,
labels = ~ Imp_C,
values = ~ C_T_A_T,
type = 'pie',
textposition = 'inside',
marker = list(colors = c('#bcbd22', '#2ca02c')),
textinfo = 'percent',
showlegend=F) %>%
layout(title = "Cannabis Tax Actual Total",legend = list(orientation ="h", xanchor = "center", x = 0.5, y = -0.1)))
)
```
```{r adi lic app fee pie}
div(
div(plot_ly(ADI_sd_df,
labels = ~ Imp_C,
values = ~ App_F,
type = 'pie',
textposition = 'inside',
marker = list(colors = c('#bcbd22', '#2ca02c')),
textinfo = 'percent',
showlegend=F) %>%
layout(title = "ADI Application Fee",legend = list(orientation ="h", xanchor = "center", x = 0.5, y = -0.1))),
div(plot_ly(ADI_sd_df,
labels = ~ Imp_C,
values = ~ Lcn_F,
type = 'pie',
textposition = 'inside',
marker = list(colors = c('#bcbd22', '#2ca02c')),
textinfo = 'percent',
showlegend=F) %>%
layout(title = "ADI Licenses Fee",legend = list(orientation ="h", xanchor = "center", x = 0.5, y = -0.1)))
)
```
Authority {data-icon="fa-cannabis"}
=====================================
Column {data-width=200 .tabset .tabset-fade .colored}
-----------------------------------------------------------------------
### Authority
Select intputs to filter the data.
Entities
```{r ent town filter}
filter_select("Business_Town", "Select Town", AE_sd, ~Business_Town)
```
```{r ent county filter}
filter_select("Business_County", "Select a County", AE_sd, ~Business_County)
```
```{r ent prioirty status filter}
filter_checkbox("Priority_Status", "Prioirty Status", AE_sd, ~Priority_Status, allLevels = TRUE)
```
```{r ent status filter}
filter_checkbox("License_Status", "License Status", AE_sd, ~License_Status, allLevels = TRUE)
```
```{r ent license type filter}
filter_select("License_Type","License Type", AE_sd, ~License_Type)
```
```{r ent total authority fitler}
filter_slider("Total_Authority_Agents", "Total Authority Agents", AE_sd, ~Total_Authority_Agents, step = 5)
```
```{r ent dbe category filter}
filter_select("DBE_Category","DBE Category", AE_sd, ~DBE_Category)
```
```{r ent role filter}
filter_select("Role", "Role", AE_sd, ~Role)
```
```{r ent ownership filter}
filter_slider("Ownership", "% Ownership", AE_sd, ~Ownership, step = 10)
```
```{r ent control filter}
filter_slider("Control", "% Controls", AE_sd, ~Control, step = 10)
```
```{r ent business name filter}
filter_select("Business_Name","Business Name", AE_sd, ~Business_Name)
```
Interests
```{r int town filter}
filter_select("Business_Town", "Select Town", BI_sd, ~Business_Town)
```
```{r int county filter}
filter_select("Business_County", "Select a County", BI_sd, ~Business_County)
```
```{r int prioirty status filter}
filter_checkbox("Priority_Status", "Prioirty Status", BI_sd, ~Priority_Status, allLevels = TRUE)
```
```{r int status filter}
filter_checkbox("License_Status", "License Status", BI_sd, ~License_Status, allLevels = TRUE)
```
```{r int license type filter}
filter_select("License_Type","License Type", BI_sd, ~License_Type)
```
```{r int total authority fitler}
filter_slider("Total_Authority_Agents", "Total Authority Agents", BI_sd, ~Total_Authority_Agents, step = 5)
```
```{r int dbe category filter}
filter_select("DBE_Category","DBE Category", BI_sd, ~DBE_Category)
```
```{r int role filter}
filter_select("Role", "Role", BI_sd, ~Role)
```
```{r int business name filter}
filter_select("Business_Name","Business Name", BI_sd, ~Business_Name)
```
### ADI
Select intputs to filter the data.
```{r int ent adi filter}
filter_checkbox("Imp_C", "Area of Disproportionate Impact (ADI)", ADI_sd_df, ~Imp_C)
```
```{r int ent aus filter}
filter_select("A_U_S", "Adult Use Status", ADI_sd_df, ~A_U_S)
```
```{r int ent delivery filter}
filter_select("Dlv_A", "Delivery", ADI_sd_df,~Dlv_A)
```
```{r int ent social consumption filter}
filter_select("S_C_P", "Social Consumption", ADI_sd_df,~S_C_P)
```
Column {data-width=650 .tabset .tabset-fade .colored}
-----------------------------------------------------------------------
### Map
```{r ent int map}
AEPSpal <- colorFactor(palette = 'Spectral', levels=AE_sd$data()$Role, ordered=FALSE)
leaflet() %>%
setView(-71.931180, 42.385453, zoom = 8) %>%
addProviderTiles("CartoDB.DarkMatter", group = "Dark") %>%
addProviderTiles("Esri.WorldGrayCanvas", group = "Grey") %>%
addPolygons(data = ADI_sd,
weight = .4,
smoothFactor = 1,
fillOpacity = ifelse(test = ADI_sd$Imp_C == "Impact", yes = 0.5, no = 0),
color = "#878787",
fillColor = "#17b502",
label = ~Town_1, # name as a hover label
group = "ADI") %>%
addCircleMarkers(data = AE_sd,
lng = ~Lon,
lat = ~Lat,
popup = ~AutAboxinfo,
color = ~AEPSpal(Role),
radius = ~AE_sd$data()$Total_Authority_Agents/3,
group = "Entities") %>%
addCircleMarkers(data = BI_sd,
lng = ~Lon,
lat = ~Lat,
popup = ~BIboxinfo,
color = ~AEPSpal(Role),
radius = ~BI_sd$data()$Total_Authority_Agents/10,
group = "Interests") %>%
addPolylines(data = flows_sd,
weight = flows_sd$data()$Ownership/10,
label = hover,
group = "Travel Interests",
color="#00b3ff") %>%
addPolylines(data = flows_sd,
weight = flows_sd$data()$Total_Authority_Agents/10,
label = hover,
group = "Travel Entities",
color="#00b3ff") %>%
addCircleMarkers(Geolines$end.latitude,
Geolines$end.longitude,
color="orange",
radius=Geolines$ownership/15,
group= "Travel Points") %>%
addCircleMarkers(Geolines$start.latitude,
Geolines$start.longitude,
color="orange",
radius=Geolines$control/15,
group = "Travel Points") %>%
addLegend("bottomleft",
pal = AEPSpal,
values = AE_sd$data()$Role,
title = "Authority Role",
opacity = 1) %>%
addLayersControl(overlayGroups = c("ADI","Entities", "Interests","Travel Points", "Travel Interests", "Travel Entities"),
baseGroups = c("Dark","Grey"),
options = layersControlOptions(collapsed = FALSE)) %>%
addMeasure()
```
### Data
```{r ent data table}
DT::datatable(AE_sd, rownames = FALSE, class = 'cell-border stripe' ,
extensions = c('ColReorder','Responsive'), options = list(colReorder = TRUE))
```
```{r int data table}
DT::datatable(BI_sd, rownames = FALSE, class = 'cell-border stripe' ,
extensions = c('ColReorder','Responsive'), options = list(colReorder = TRUE))
```
### Equity
```{r ent int equity }
# Summary break down with static charts and detailed descritpiton explaining what the data is telling us
```
Column {data-width=350 .tabset .tabset-fade .colored}
-----------------------------------------------------------------------
### Authority
```{r ent int lic status pie}
div(
div(plot_ly(AE_sd, labels = ~ License_Status, values = ~ Total_Authority_Agents, type = 'pie', textposition = 'inside', textinfo = 'label+percent', showlegend=F) %>% layout(title = "Entitites", legend = list(orientation ="h", xanchor = "center", x = 0.5, y = -0.1))),
div(plot_ly(BI_sd, labels = ~ License_Status, values = ~ Total_Authority_Agents, type = 'pie', textposition = 'inside', textinfo = 'label+percent', showlegend=F) %>% layout(title = "Interests", legend = list(orientation ="h", xanchor = "center", x = 0.5, y = -0.1)))
)
```
```{r ent int lic priority status pie}
div(
div(plot_ly(AE_sd, labels = ~ Priority_Status, values = ~ Total_Authority_Agents, type = 'pie', textposition = 'inside', textinfo = 'label+percent', showlegend=F) %>% layout(title = "Entitites", legend = list(orientation ="h", xanchor = "center", x = 0.5, y = -0.1))),
div(plot_ly(BI_sd, labels = ~ Priority_Status, values = ~ Total_Authority_Agents, type = 'pie', textposition = 'inside', textinfo = 'label+percent', showlegend=F) %>% layout(title = "Interests", legend = list(orientation ="h", xanchor = "center", x = 0.5, y = -0.1)))
)
```
```{r ent int lic license type pie}
div(
div(plot_ly(AE_sd, labels = ~ License_Type, values = ~ Total_Authority_Agents, type = 'pie', textposition = 'inside', textinfo = 'label+percent', showlegend=F) %>% layout(title = "Entitites", legend = list(orientation ="h", xanchor = "center", x = 0.5, y = -0.1))),
div(plot_ly(BI_sd, labels = ~ License_Type, values = ~ Total_Authority_Agents, type = 'pie', textposition = 'inside', textinfo = 'label+percent', showlegend=F) %>% layout(title = "Interests", legend = list(orientation ="h", xanchor = "center", x = 0.5, y = -0.1)))
)
```
```{r ent int lic dbe category pie}
div(
div(plot_ly(AE_sd, labels = ~ DBE_Category, values = ~ Total_Authority_Agents, type = 'pie', textposition = 'inside', textinfo = 'label+percent', showlegend=F) %>% layout(title = "Entitites", legend = list(orientation ="h", xanchor = "center", x = 0.5, y = -0.1))),
div(plot_ly(BI_sd, labels = ~ DBE_Category, values = ~ Total_Authority_Agents, type = 'pie', textposition = 'inside', textinfo = 'label+percent', showlegend=F) %>% layout(title = "Interests", legend = list(orientation ="h", xanchor = "center", x = 0.5, y = -0.1)))
)
```
```{r}
div(
div(plot_ly(AE_sd, labels = ~ Business_Town, values = ~ Total_Authority_Agents, type = 'pie', textposition = 'inside', textinfo = 'label+percent', showlegend=F) %>% layout(title = "Entitites", legend = list(orientation ="h", xanchor = "center", x = 0.5, y = -0.1))),
div(plot_ly(BI_sd, labels = ~ Business_Town, values = ~ Total_Authority_Agents, type = 'pie', textposition = 'inside', textinfo = 'label+percent', showlegend=F) %>% layout(title = "Interests", legend = list(orientation ="h", xanchor = "center", x = 0.5, y = -0.1)))
)
```
```{r}
div(
div(plot_ly(AE_sd, labels = ~ Business_County, values = ~ Total_Authority_Agents, type = 'pie', textposition = 'inside', textinfo = 'label+percent', showlegend=F) %>% layout(title = "Entitites", legend = list(orientation ="h", xanchor = "center", x = 0.5, y = -0.1))),
div(plot_ly(BI_sd, labels = ~ Business_County, values = ~ Total_Authority_Agents, type = 'pie', textposition = 'inside', textinfo = 'label+percent', showlegend=F) %>% layout(title = "Interests", legend = list(orientation ="h", xanchor = "center", x = 0.5, y = -0.1)))
)
```