BitsBites.R

# Alternative // Unused Code chunks Tracker

## Primary energy fossil fuels and energy share processing

## Mapping with continous legend
bins = c(0,10,20,40,60,70,80,90,100)
cv_pal <- colorBin("Blues", domain = country_overview_large$fossil_fuel_share_energy_2019, bins = bins)

## Version with fossil fuel share 2019
# create base map 
basemap = leaflet(plot_map) %>% 
    addTiles() %>% 
    addLayersControl(
        position = "topright",
        overlayGroups = c("Cities, States, Regions", "Governmental Policies", "Non-Governmental Policies", "Fossil Fuel Non-Proliferation"),
        options = layersControlOptions(collapsed = FALSE)) %>% 
    hideGroup(c("Cities, States, Regions", "Governmental Policies", "Non-Governmental Policies", "Fossil Fuel Non-Proliferation")) %>% 
    htmlwidgets::onRender("
        function() {
            $('.leaflet-control-layers-overlays').prepend('<label style=\"text-align:center\"><strong>Policy Level/Type</strong><br/></label>');
        }
    ") %>%
    addProviderTiles(providers$CartoDB.Positron) %>%
    fitBounds(~-100,-60,~60,70) %>%
    addLegend("bottomright", pal = cv_pal, values = ~country_overview_large$fossil_fuel_share_energy_2019,
              title = "Engergy Share Fossil Fuels") %>% 
    
    addPolygons(stroke = FALSE, smoothFactor = 0.4, fillOpacity = 0.65, fillColor = ~cv_pal(country_overview_large$fossil_fuel_share_energy_2019),
                label = sprintf("<strong>%s</strong><br/><small>Primary Energy from Fossil-Fuels: %s </small><br/><small>Climate Risk Index: %s</small><br/><small>Total number of policies: %g</small>", 
                                country_overview_large$Country, country_overview_large$fossil_fuel_share_energy_2019, country_overview_large$cri, country_overview_large$Policy_total) %>% 
                    lapply(htmltools::HTML),
                labelOptions = labelOptions(
                    style = list("font-weight" = "normal", "font-family" = "Poppins", padding = "3px 8px", "color" = cv_pal),
                    textsize = "15px", direction = "auto")) %>%
### Pull Fossil-Fuel Emissions to country_overview file via ISO3 and filter by Year 2019
baseline_ff_share_2019 <- baseline_ff_share %>% 
    filter(Year == 2019)

### EDA Distribution of Fossil Fuel share across countries in 2019
baseline_ff_share_2019 %>% ggplot(aes(Fossil.fuels....sub.energy.)) + 
    geom_histogram(binwidth = 7)

# Factor and label Fossil Fuel share across countries in 2019
baseline_ff_share_2019$ff_share_2019_cat <- cut(baseline_ff_share_2019$Fossil.fuels....sub.energy., breaks = c(0, 20, 40, 60, 70, 80, 90, 95, 100), 
                                                labels = c("No data", "0-20 fossil-fuel production", "0-20 fossil-fuel production", "20-40 fossil-fuel production",
                                                           "40-60 fossil-fuel production", "60-80 fossil-fuel production", 
                                                           "80-90 fossil-fuel production", "100 fossil-fuel production"), right = FALSE)

### Pull Fossil-Fuel Share factorized to country_overview file via ISO3 
country_overview_large["ff_share_2019_cat"] <- baseline_ff_share_2019$ff_share_2019_cat[match(country_overview_large$ISO3,
                                                                                              baseline_ff_share_2019$Code)]

### EDA Distribution of Fossil Fuel share across countries in 2019
fossil_fuels_share_energy_2019 %>% ggplot(aes(Fossil.fuels....sub.energy.)) + 
    geom_histogram(binwidth = 3)

# Factor and label Fossil Fuel share across countries in 2019
fossil_fuels_share_energy_2019$ff_share_2019_cat <- cut(fossil_fuels_share_energy_2019$Fossil.fuels....sub.energy., breaks = c(0, 20, 40, 60, 70, 80, 90, 95, 100), 
                                                        labels = c("No data", "0-20 fossil-fuel production", "0-20 fossil-fuel production", "20-40 fossil-fuel production",
                                                                   "40-60 fossil-fuel production", "60-80 fossil-fuel production", 
                                                                   "80-90 fossil-fuel production", "100 fossil-fuel production"), right = TRUE)

### Pull Fossil-Fuel Share factorized to country_overview file via ISO3 
country_overview_large["ff_share_2019_cat"] <- fossil_fuels_share_energy_2019$ff_share_2019_cat[match(country_overview_large$ISO3,
                                                                                                      fossil_fuels_share_energy_2019$Code)]


### Pull Fossil fuel consumption (which countries use the most energy from fossil fuels) to country_overview file via ISO3 and filter by Year 2019
fossil_fuel_primary_energy_2019 <- fossil_fuel_primary_energy %>% 
    filter(Year == 2019)

country_overview_large["fossil_fuel_primary_energy_2019"] <- fossil_fuel_primary_energy_2019$Fossil.fuels....sub.energy.[match(country_overview_large$ISO3,
                                                                                                                               fossil_fuel_primary_energy_2019$Code)]

### EDA Distribution of Fossil Fuel share across countries in 2019
fossil_fuel_primary_energy_2019 %>% ggplot(aes(Fossil.fuels....sub.energy.)) + 
    geom_histogram(binwidth = 3)

# Factor and label Fossil Fuel share across countries in 2019
fossil_fuel_primary_energy_2019$ff_primary_energy_2019_cat <- cut(fossil_fuel_primary_energy_2019$Fossil.fuels....sub.energy., breaks = c(0, 20, 40, 60, 70, 80, 90, 95, 100), 
                                                                  labels = c("No data", "0-20 fossil-fuel production", "0-20 fossil-fuel production", "20-40 fossil-fuel production",
                                                                             "40-60 fossil-fuel production", "60-80 fossil-fuel production", 
                                                                             "80-90 fossil-fuel production", "100 fossil-fuel production"), right = TRUE)

### Pull Fossil-Fuel Share factorized to country_overview file via ISO3 
country_overview_large["ff_share_2019_cat"] <- baseline_ff_share_2019$ff_share_2019_cat[match(country_overview_large$ISO3,
                                                                                              baseline_ff_share_2019$Code)]

## Version with CAIT MTCO2e

## create plotting parameters for map
#cv_pal <- colorFactor(palette = c("#FF0D0D","#FF4E11", "#FF8E15", "#FAB733", "#ACB334", "#69B34C", "#B1B6B9"), country_overview_large$CAT_rating)
cv_pal <- colorFactor(palette = c("#EFEFEF", "#FCDE9C", "#BEC5A9", "#8DA8AD", "#668BA8", "#466A9F", "#2C4B93", "#062A89"), country_overview_large$MTCO2e_cat)
plot_map <- worldcountry[worldcountry$ADM0_A3 %in% country_overview_large$ISO3, ]

# create base map 
basemap = leaflet(plot_map) %>% 
        addTiles() %>% 
        addLayersControl(
                position = "topright",
                overlayGroups = c("Cities, States, Regions", "Governmental Policies", "Non-Governmental Policies", "Fossil Fuel Non-Proliferation"),
                options = layersControlOptions(collapsed = FALSE)) %>% 
        hideGroup(c("Cities, States, Regions", "Governmental Policies", "Non-Governmental Policies", "Fossil Fuel Non-Proliferation")) %>% 
        htmlwidgets::onRender("
        function() {
            $('.leaflet-control-layers-overlays').prepend('<label style=\"text-align:center\"><strong>Policy Level/Type</strong><br/></label>');
        }
    ") %>%
        addProviderTiles(providers$CartoDB.Positron) %>%
        fitBounds(~-100,-60,~60,70) %>%
        addLegend("bottomright", colors = c("#EFEFEF", "#FCDE9C", "#BEC5A9", "#8DA8AD", "#668BA8", "#466A9F", "#2C4B93", "#062A89"), 
                  labels =  c("No data", "< 0", "1-169","169-500","500-1000","1000-5000",  
                              "5000-10000","> 10000"),values = ~country_overview_large$MTCO2e_cat,
                  title = "Country Greenhouse<br/>Gas Emissions (MtCO2e)<br/>(CAIT 2016)") %>% 
        
        addPolygons(stroke = FALSE, smoothFactor = 0.4, fillOpacity = 0.65, fillColor = ~cv_pal(country_overview_large$MTCO2e_cat),
                    label = sprintf("<strong>%s</strong><br/><small>Greenhouse Gas Emissions: %s MtCO2e</small><br/><small>Climate Risk Index: %s</small><br/><small>Total number of policies: %g</small>", 
                                    country_overview_large$Country, country_overview_large$MTCO2e, country_overview_large$cri, country_overview_large$Policy_total) %>% 
                            lapply(htmltools::HTML),
                    labelOptions = labelOptions(
                            style = list("font-weight" = "normal", "font-family" = "Poppins", padding = "3px 8px", "color" = cv_pal),
                            textsize = "15px", direction = "auto")) %>%

## Download button I am giving up 11.03.21

### Download Server Side
report_path <- tempfile(fileext = ".Rmd")
file.copy("report_template.Rmd", report_path, overwrite = TRUE)

render_report <- function(input, output, params) {
        rmarkdown::render(input,
                          output_file = output,
                          params = params,
                          envir = new.env(parent = globalenv())
        )
}

output$downloadReport <- downloadHandler(
        filename = "report_template.html",
        content = function(file) {
                params <- list(selection = input$country)
                callr::r(
                        render_report,
                        list(input = report_path, output = file, params = params)
                )
        }
)
output$downloadReport <- downloadHandler(
        filename = "report_template.html",
        content = function(file) {
                rmarkdown::render("report_template.Rmd", 
                                  output_file = file,
                                  envir = new.env(parent = globalenv())
                )
        }
)

## Country profiles 10.03.21
tabPanel("Country Profiles",
         tags$head(
                 tags$link(
                         type = "text/css",
                         rel = "stylesheet",
                         href = "css/styles.css"
                 )
         ),
         sidebarLayout(
                 sidebarPanel(width = 3,
                              tags$form(
                                      tags$legend("Select country from drop-down menu and press button to show country profiles"),
                                      tags$label(`for` = "country", ""),
                                      tags$select(id = "country", HTML(
                                              c("Select a Country",
                                                sapply(
                                                        sort(unique(country_overview_large$Country)),
                                                        function(x) {
                                                                paste0(
                                                                        "<option value='", x, "'>",
                                                                        x,
                                                                        "</option>"
                                                                )
                                                        }
                                                )
                                              )
                                      )
                                      ),
                                      tags$button(
                                              id = "render",
                                              class = "action-button shiny-bound-input",
                                              "Show"
                                      )
                              )
                 ),
                 mainPanel(
                         tabsetPanel(
                                 tabPanel("Overview", tags$article(
                                         `aria-label` = "report",
                                         htmlOutput("report")
                                 )),
                                 tabPanel("Moratorial, Limits, & Bans", tags$article(
                                         `aria-label` = "report1",
                                         htmlOutput("report1")
                                 )),
                                 tabPanel("Subsidy Removals", tags$article(
                                         `aria-label` = "report2",
                                         htmlOutput("report2")
                                 )),
                                 tabPanel("Divestments", tags$article(
                                         `aria-label` = "report3",
                                         htmlOutput("report3")
                                 ))
                         )
                 )
         )
),

# Server side
## country-specific profiles
# set initial ui for htmlOutput
output$report <- renderUI({
        tagList(
                tags$p(
                        "Rendering of profiles takes a couple of seconds. The data presented here is based on the Fossil Fuel Database ",
                        "which automatically searches the internet to identify ",
                        "existing climate change supply-side policies. Click here ",
                        tags$a(
                                href = "https://fossilfueltreaty.org",
                                "for more information"
                        ),
                        "."
                )
        )
})

# render report when button clicked
observeEvent(input$render, {
        country_overview_largeDF <- country_overview_large[country_overview_large$Country == input$country, ]
        moratoria_bans_limitsDF <- moratoria_bans_limits[moratoria_bans_limits$Country == input$country, ]
        subsidiy_removalDF <- subsidiy_removal[subsidiy_removal$Country == input$country, ]
        divestmentDF <- divestment[divestment$Country == input$country, ]
        output$report <- renderUI({
                includeHTML(
                        rmarkdown::render(
                                "report_template.Rmd",
                                params = list(
                                        selection = input$country,
                                        data = country_overview_largeDF,
                                        data = country_overview_largeDF,
                                        data_mbl = moratoria_bans_limitsDF,
                                        data_sr = subsidiy_removalDF,
                                        data_div = divestmentDF
                                )
                        )
                )
        })
})

# set initial ui for htmlOutput
output$report1 <- renderUI({
        tagList(
                tags$p(
                        "Rendering of profiles takes a couple of seconds. The data presented here is based on the Fossil Fuel Database ",
                        "which automatically searches the internet to identify ",
                        "existing climate change supply-side policies. Click here ",
                        tags$a(
                                href = "https://fossilfueltreaty.org",
                                "for more information"
                        ),
                        "."
                )
        )
})

# render report when button clicked
observeEvent(input$render, {
        moratoria_bans_limitsDF <- moratoria_bans_limits[moratoria_bans_limits$Country == input$country, ]
        output$report1 <- renderUI({
                includeHTML(
                        rmarkdown::render(
                                "report_template1.Rmd",
                                params = list(
                                        selection = input$country,
                                        data_mbl = moratoria_bans_limitsDF
                                )
                        )
                )
        })
})

# set initial ui for htmlOutput
output$report2 <- renderUI({
        tagList(
                tags$p(
                        "Rendering of profiles takes a couple of seconds. The data presented here is based on the Fossil Fuel Database ",
                        "which automatically searches the internet to identify ",
                        "existing climate change supply-side policies. Click here ",
                        tags$a(
                                href = "https://fossilfueltreaty.org",
                                "for more information"
                        ),
                        "."
                )
        )
})

# render report when button clicked
observeEvent(input$render, {
        subsidiy_removalDF <- subsidiy_removal[subsidiy_removal$Country == input$country, ]
        output$report2 <- renderUI({
                includeHTML(
                        rmarkdown::render(
                                "report_template2.Rmd",
                                params = list(
                                        selection = input$country,
                                        data_sr = subsidiy_removalDF
                                )
                        )
                )
        })
})

# set initial ui for htmlOutput
output$report3 <- renderUI({
        tagList(
                tags$p(
                        "Rendering of profiles takes a couple of seconds. The data presented here is based on the Fossil Fuel Database ",
                        "which automatically searches the internet to identify ",
                        "existing climate change supply-side policies. Click here ",
                        tags$a(
                                href = "https://fossilfueltreaty.org",
                                "for more information"
                        ),
                        "."
                )
        )
})

# render report when button clicked
observeEvent(input$render, {
        divestmentDF <- divestment[divestment$Country == input$country, ]
        output$report3 <- renderUI({
                includeHTML(
                        rmarkdown::render(
                                "report_template3.Rmd",
                                params = list(
                                        selection = input$country,
                                        data_div = divestmentDF
                                )
                        )
                )
        })
})

## Country Profiles 08.03.21
tabPanel("Country Profiles",
         tags$head(
                 tags$link(
                         type = "text/css",
                         rel = "stylesheet",
                         href = "css/styles.css"
                 )
         ),
         tags$main(
                 tags$form(
                         tags$legend("Select country from drop-down menu and press button to show country profiles"),
                         tags$label(`for` = "country", ""),
                         tags$select(id = "country", HTML(
                                 c("Select a Country",
                                   sapply(
                                           sort(unique(country_overview_large$Country)),
                                           function(x) {
                                                   paste0(
                                                           "<option value='", x, "'>",
                                                           x,
                                                           "</option>"
                                                   )
                                           }
                                   )
                                 )
                         )
                         ),
                         tags$button(
                                 id = "render",
                                 class = "action-button shiny-bound-input",
                                 "Show"
                         )
                 ),
                 tags$article(
                         `aria-label` = "report",
                         htmlOutput("report")
                 )
         )
),

## server

## country-specific profiles
# set initial ui for htmlOutput
output$report <- renderUI({
        tagList(
                tags$p(
                        "Rendering of profiles takes a couple of seconds. The data presented here is based on the Fossil Fuel Database ",
                        "which automatically searches the internet to identify ",
                        "existing climate change supply-side policies. Click here ",
                        tags$a(
                                href = "https://fossilfueltreaty.org",
                                "for more information"
                        ),
                        "."
                )
        )
})

# render report when button clicked
observeEvent(input$render, {
        country_overview_largeDF <- country_overview_large[country_overview_large$Country == input$country, ]
        moratoria_bans_limitsDF <- moratoria_bans_limits[moratoria_bans_limits$Country == input$country, ]
        subsidiy_removalDF <- subsidiy_removal[subsidiy_removal$Country == input$country, ]
        divestmentDF <- divestment[divestment$Country == input$country, ]
        output$report <- renderUI({
                includeHTML(
                        rmarkdown::render(
                                "report_template.Rmd",
                                params = list(
                                        selection = input$country,
                                        data = country_overview_largeDF,
                                        data_mbl = moratoria_bans_limitsDF,
                                        data_sr = subsidiy_removalDF,
                                        data_div = divestmentDF
                                )
                        )
                )
        })
})

# import iso country codes
url <- "https://www.nationsonline.org/oneworld/country_code_list.htm"
iso_codes <- url %>%
        read_html() %>%
        html_nodes(xpath = '//*[@id="CountryCode"]') %>%
        html_table()
iso_codes <- iso_codes[[1]][, -1]
iso_codes <- iso_codes[!apply(iso_codes, 1, function(x){all(x == x[1])}), ]
names(iso_codes) <- c("Country", "ISO2", "ISO3", "UN")
head(iso_codes)
write.csv(iso_codes, file = "input_data/iso_codes.csv")
iso_codes = read.csv("input_data/iso_codes.csv")

country_iso = read_xlsx("input_data/FF NPT Tracker DRAFT WIP.xlsx", sheet = 8)

# Load world data with geographical coordinates directly from the ggplot2 package. These data contain geographical coordinates of all countries worldwide, 
# which we’ll later need to plot the worldmaps.
library(maps)
library(ggplot2)
world_data <- ggplot2::map_data('world')
world_data <- fortify(world_data)
head(world_data)
write.csv(world_data, file = "input_data/world_data.csv")


# Rename Alpha into ISO
countries <- countries %>% rename(ISO2 = alpha2, ISO3 = alpha3)
countries$X <- NULL
write.csv(countries, file = "input_data/countries_codes_and_coordinates.csv")
countries <- read.csv("input_data/countries_codes_and_coordinates.csv")
head(countries)

write.csv(country_overview, file = "input_data/country_overview_full.csv")
head(country_overview)
countries = read.csv("input_data/country_overview_full.csv")

## Transfer total number and breakdowns of policies to country_overview_large file
## Total number of policies
country_overview_large['Moratoria_bans_limits'] <- sum(moratoria_bans_limits$c)[match(country_overview_large$ISO3, moratoria_bans_limits$ISO3)]
country_overview_large['Subsidy_removal'] <- sum(subsidiy_removal$a)[match(country_overview_large$ISO3, subsidiy_removal$ISO3)]
country_overview_large['Divestment'] <- divestment$d[match(country_overview_large$ISO3, divestment$ISO3)]
country_overview_large <- country_overview_large %>% mutate(policy_total = country_overview_large$Moratoria_bans_limits+country_overview_large$Subsidy_removal +
                                                                    country_overview_large$Divestment)

##############################################################################################################################
# function to make a selected table output for MBL
mbl_table = function(moratoria_bans_limits){
        mbl = moratoria_bans_limits %>% 
                group_by(moratoria_bans_limits$City_state_or_province) %>% 
                select(c("City_state_or_province", "Category", "Fuel_type", "Fuel_subtype", "Sources_and_more_info")) %>% 
                replace(is.na(.), "--")
        names(mbl) = c("City state or province", "Category", "Fuel type", "Fuel subtype", "Sources")
        mbl
}

# function to make a selected table output for SR
sr_table = function(subsidiy_removal){
        sr = subsidiy_removal %>% 
                group_by(Category) %>%
                select(c("Category", "Fuel_type", "Fuel_subtype", "Description", "Sources_and_more_info")) %>% 
                replace(is.na(.), "--") 
        names(sr) = c("Category", "Fuel type", "Fuel subtype", "Description", "Sources")
        sr
}   

# function to make a selected table output for DIV
div_table = function(divestment_new){
        div = divestment_new %>% 
                group_by(Category) %>% 
                select(c("Category", "Type", "Organisation", "Organisation_type", "Sources_and_more_info"))%>% 
                replace(is.na(.), "--")
        names(div) = c("Category", "Type", "Organisation", "Organisation Type", "Sources")
        div
}

# Check correctness of data table functions
#mbl_table(moratoria_bans_limits)
#sr_table(subsidiy_removal)
#div_table(divestment_new)
##############################################################################################################################

# create plotting parameters for map
bins = c(0,10,50,100,500) 
cv_pal <- colorBin("Greens", domain =  country_overview_large$policy_total, bins = bins)
plot_map <- worldcountry[worldcountry$ADM0_A3 %in% country_overview_large$ISO3, ]

bins = c("No Rating", "Critically Insufficient","Highly Insufficient","Insufficient","2°C Compatible","1.5°C Paris Agreement Compatible", "Role Model") 
cv_pal <- colorFactor(palette = c("#B1B6B9","#686464", "#EF6948", "#EF9D24", "#F3DD3F", "#FFFFFF", "#568C45"), domain =  country_overview_large$CAT_rating)
plot_map <- worldcountry[worldcountry$ADM0_A3 %in% country_overview_large$ISO3, ]


# assign colours to countries to ensure consistency between plots 
cls = rep(c(brewer.pal(8,"Dark2"), brewer.pal(10, "Paired"), brewer.pal(12, "Set3"), brewer.pal(8,"Set2"), brewer.pal(9, "Set1"), brewer.pal(8, "Accent"),  brewer.pal(9, "Pastel1"),  brewer.pal(8, "Pastel2")),4)
cls_names = c(as.character(unique(country_overview_large$Country)), as.character(unique(country_overview_large$continent_level)),"Global")
country_cols = cls[1:length(cls_names)]
names(country_cols) = cls_names

#ä Polygons with types of policies instead of gov vs. non-gov policies
addPolygons(stroke = FALSE, smoothFactor = 0.2, fillOpacity = 0.4, fillColor = ~cv_pal(country_overview_large$CAT_rating),
            label = sprintf("<strong>%s</strong><br/>CAT Rating: %s<br/>Moratoria, bans, & limits: %g<br/>Subsidy Removals: %d<br/>Divestments: %g", 
                            country_overview_large$Country, country_overview_large$CAT_rating, country_overview_large$Moratoria_bans_limits_total, 
                            country_overview_large$Subsidy_removal_total, 
                            country_overview_large$Divestment_total) %>% lapply(htmltools::HTML),
            labelOptions = labelOptions(
                    style = list("font-weight" = "normal", "font-family" = "Roboto", padding = "3px 8px", "color" = cv_pal),
                    textsize = "15px", direction = "auto"))

## Basemap with types of policies as layers and hovering with gov vs. non-gov policies
# create base map 
basemap = leaflet(plot_map) %>% 
        addTiles() %>% 
        addLayersControl(
                position = "topright",
                overlayGroups = c("All Policies", "Moratoria, Bans, & Limits", "Subsidy Removal", "Divestment"),
                options = layersControlOptions(collapsed = FALSE)) %>% 
        hideGroup(c("All Policies", "Moratoria, Bans, & Limits", "Subsidy Removal", "Divestment")) %>%
        addProviderTiles(providers$CartoDB.Positron) %>%
        fitBounds(~-100,-60,~60,70) %>%
        addLegend("bottomright", colors = c("#FF0D0D","#FF4E11", "#FF8E15", "#FAB733", "#ACB334", "#69B34C", "#B1B6B9", "#EFEFEF"), 
                  labels =  c("<small>Critically Insufficient</small>","<small>Highly Insufficient</small>","<small>Insufficient</small>", 
                              "<small>2°C Compatible</small>","<small>1.5°C Paris Agreement Compatible</small>","<small>Role Model</small>", 
                              "<small>No Rating</small>", "<small>No Data</small>"),values = ~country_overview_large$CAT_rating,
                  title = "<small>Climate Action Tracker Rating</small>") %>% 
        
        addPolygons(stroke = FALSE, smoothFactor = 0.2, fillOpacity = 0.4, fillColor = ~cv_pal(country_overview_large$CAT_rating),
                    label = sprintf("<strong>%s</strong><br/>CAT Rating: %s<br/>Government policies: %g<br/>Non-governmental policies: %d", 
                                    country_overview_large$Country, country_overview_large$CAT_rating, country_overview_large$Government_policies_total, 
                                    country_overview_large$Non_Government_policies_total) %>% lapply(htmltools::HTML),
                    labelOptions = labelOptions(
                            style = list("font-weight" = "normal", "font-family" = "Roboto", padding = "3px 8px", "color" = cv_pal),
                            textsize = "15px", direction = "auto")) %>%
        
        addCircleMarkers(data = country_overview_large, lat = ~ latitude, lng = ~ longitude, weight = 1, radius = ~(Policy_total)^(1/1.5), 
                         fillOpacity = 0.2, color = All_policies, group = "All Policies",
                         label = sprintf("<strong>%s</strong><br/>Moratoria, bans, & limits: %g<br/>Subsidy Removals: %d<br/>Divestments: %g", 
                                         country_overview_large$Country, country_overview_large$Moratoria_bans_limits_total, country_overview_large$Subsidy_removal_total, 
                                         country_overview_large$Divestment_total) %>% lapply(htmltools::HTML),
                         labelOptions = labelOptions(
                                 style = list("font-weight" = "normal", "font-family" = "Roboto", padding = "3px 8px", "color" = All_policies),
                                 textsize = "15px", direction = "auto")) %>% 
        
        
        addCircleMarkers(data = country_overview_large, lat = ~ latitude, lng = ~ longitude, weight = 1, radius = ~(Moratoria_bans_limits_total)^(1/1.5), 
                         fillOpacity = 0.2, color = Moratoria_bans_limits, group = "Moratoria, Bans, & Limits",
                         label = sprintf("<strong>%s</strong><br/>Moratoria, bans, & limits: %g", 
                                         country_overview_large$Country, country_overview_large$Moratoria_bans_limits_total) %>% lapply(htmltools::HTML),
                         labelOptions = labelOptions(
                                 style = list("font-weight" = "normal", "font-family" = "Roboto", padding = "3px 8px", "color" = Moratoria_bans_limits),
                                 textsize = "15px", direction = "auto")) %>% 
        
        addCircleMarkers(data = country_overview_large, lat = ~ latitude, lng = ~ longitude, weight = 1, radius = ~(Subsidy_removal_total)^(1/1.5), 
                         fillOpacity = 0.2, color = Subsidy_removal, group = "Subsidy Removal",
                         label = sprintf("<strong>%s</strong><br/>Subsidy Removals: %g", 
                                         country_overview_large$Country, country_overview_large$Subsidy_removal_total) %>% lapply(htmltools::HTML),
                         labelOptions = labelOptions(
                                 style = list("font-weight" = "normal", "font-family" = "Roboto", padding = "3px 8px", "color" = Subsidy_removal),
                                 textsize = "15px", direction = "auto")) %>% 
        
        addCircleMarkers(data = country_overview_large, lat = ~ latitude, lng = ~ longitude, weight = 1, radius = ~(Divestment_total)^(1/1.5), 
                         fillOpacity = 0.2, color = Divestment, group = "Divestment",
                         label = sprintf("<strong>%s</strong><br/>Divestments: %g", 
                                         country_overview_large$Country, country_overview_large$Divestment_total) %>% lapply(htmltools::HTML),
                         labelOptions = labelOptions(
                                 style = list("font-weight" = "normal", "font-family" = "Roboto", padding = "3px 8px", "color" = Divestment),
                                 textsize = "15px", direction = "auto"))
### SHINY SERVER ###

server = function(input, output, session) {
        
        # Policy tab 
        output$policy_count <- renderText({
                paste0(prettyNum(sum(country_overview_large$Policy_total), big.mark=","), " Policies Overall")
        })
        
        output$gov_pol_count <- renderText({
                paste0(prettyNum(sum(country_overview_large$Government_policies_total), big.mark=","), " Government policies")
        })
        
        output$Non_gov_pol_count <- renderText({
                paste0(prettyNum(sum(country_overview_large$Non_Government_policies_total), big.mark=","), " Non-government policies")
        })
        
        output$mbl_count <- renderText({
                paste0(prettyNum(sum(country_overview_large$Moratoria_bans_limits_total), big.mark=","), " Moratoria, bans, limits")
        })
        
        output$sr_count <- renderText({
                paste0(prettyNum(sum(country_overview_large$Subsidy_removal_total), big.mark=","), " Subsidy removals")
        })
        
        output$div_count <- renderText({
                paste0(prettyNum(sum(country_overview_large$Divestment_total), big.mark=","), "  Divestments")
        })
        
        output$mymap <- renderLeaflet({ 
                basemap
        })
        
        observeEvent(input$plot_date, {
                leafletProxy("mymap") %>% 
                        clearMarkers() %>%
                        clearShapes() %>%
                        
                        addPolygons(stroke = FALSE, smoothFactor = 0.2, fillOpacity = 0.4, fillColor = ~cv_pal(country_overview_large$CAT_rating),
                                    label = sprintf("<strong>%s</strong><br/>CAT Rating: %s<br/>Moratoria, bans, & limits: %g<br/>Subsidy Removals: %d<br/>Divestments: %g", 
                                                    country_overview_large$Country, country_overview_large$CAT_rating, country_overview_large$Moratoria_bans_limits, 
                                                    country_overview_large$Subsidy_removal, country_overview_large$Divestment) %>% lapply(htmltools::HTML),
                                    labelOptions = labelOptions(
                                            style = list("font-weight" = "normal", "font-family" = "Roboto", padding = "3px 8px", "color" = cv_pal),
                                            textsize = "15px", direction = "auto")) %>%
                        
                        addCircleMarkers(data = country_overview_large, lat = ~ latitude, lng = ~ longitude, weight = 1, radius = ~(Policy_total)^(1/3), 
                                         fillOpacity = 0.2, color = All_policies, group = "All Policies",
                                         label = sprintf("<strong>%s</strong><br/>Moratoria, bans, & limits: %g<br/>Subsidy Removals: %d<br/>Divestments: %g", 
                                                         country_overview_large$Country, country_overview_large$Moratoria_bans_limits_total, country_overview_large$Subsidy_removal_total, 
                                                         country_overview_large$Divestment_total) %>% lapply(htmltools::HTML),
                                         labelOptions = labelOptions(
                                                 style = list("font-weight" = "normal", "font-family" = "Roboto", padding = "3px 8px", "color" = All_policies),
                                                 textsize = "15px", direction = "auto")) %>% 
                        
                        addCircleMarkers(data = country_overview_large, lat = ~ latitude, lng = ~ longitude, weight = 1, radius = ~(Moratoria_bans_limits_total)^(1/3), 
                                         fillOpacity = 0.2, color = Moratoria_bans_limits, group = "Moratoria, Bans, & Limits",
                                         label = sprintf("<strong>%s</strong><br/>Moratoria, bans, & limits: %g", 
                                                         country_overview_large$Country, country_overview_large$Moratoria_bans_limits_total) %>% lapply(htmltools::HTML),
                                         labelOptions = labelOptions(
                                                 style = list("font-weight" = "normal", "font-family" = "Roboto", padding = "3px 8px", "color" = Moratoria_bans_limits),
                                                 textsize = "15px", direction = "auto")) %>% 
                        
                        addCircleMarkers(data = country_overview_large, lat = ~ latitude, lng = ~ longitude, weight = 1, radius = ~(Subsidy_removal_total)^(1/3), 
                                         fillOpacity = 0.2, color = Subsidy_removal, group = "Subsidy Removal",
                                         label = sprintf("<strong>%s</strong><br/>Subsidy Removals: %g", 
                                                         country_overview_large$Country, country_overview_large$Subsidy_removal_total) %>% lapply(htmltools::HTML),
                                         labelOptions = labelOptions(
                                                 style = list("font-weight" = "normal", "font-family" = "Roboto", padding = "3px 8px", "color" = Subsidy_removal),
                                                 textsize = "15px", direction = "auto")) %>% 
                        
                        addCircleMarkers(data = country_overview_large, lat = ~ latitude, lng = ~ longitude, weight = 1, radius = ~(Divestment_total)^(1/3), 
                                         fillOpacity = 0.2, color = Divestment, group = "Divestment",
                                         label = sprintf("<strong>%s</strong><br/>Divestments: %g", 
                                                         country_overview_large$Country, country_overview_large$Divestment_total) %>% lapply(htmltools::HTML),
                                         labelOptions = labelOptions(
                                                 style = list("font-weight" = "normal", "font-family" = "Roboto", padding = "3px 8px", "color" = Divestment),
                                                 textsize = "15px", direction = "auto"))
        })
        output$cumulative_mbl_plot <- renderPlot({
                cumulative_mbl_plot(moratoria_bans_limits)
        })
        
        output$cumulative_div_plot <- renderPlot({
                cumulative_div_plot(divestment)
        })
        output$cumulative_sr_plot <- renderPlot({
                cumulative_sr_plot(subsidiy_removal)
        })
        ## country-specific profiles
        # set initial ui for htmlOutput
        output$report <- renderUI({
                tagList(
                        tags$p(
                                "The data presented here is based on the Fossil Fuel Database ",
                                "which automatically searches the internet to identify ",
                                "existing climate change supply-side policies. Click here ",
                                tags$a(
                                        href = "https://fossilfueltreaty.org",
                                        "for more information"
                                ),
                                "."
                        )
                )
        })
        
        # render report when button clicked
        observeEvent(input$render, {
                country_overview_largeDF <- country_overview_large[country_overview_large$Country == input$country, ]
                moratoria_bans_limitsDF <- moratoria_bans_limits[moratoria_bans_limits$Country == input$country, ]
                subsidiy_removalDF <- subsidiy_removal[subsidiy_removal$Country == input$country, ]
                divestmentDF <- divestment[divestment$Country == input$country, ]
                output$report <- renderUI({
                        includeHTML(
                                rmarkdown::render(
                                        "report_template.Rmd",
                                        params = list(
                                                selection = input$country,
                                                data = country_overview_largeDF,
                                                data_mbl = moratoria_bans_limitsDF,
                                                data_sr = subsidiy_removalDF,
                                                data_div = divestmentDF
                                        )
                                )
                        )
                })
        })
}

###################################################
### SHINY SERVER ###

server = function(input, output, session) {
        
        # Policy tab 
        output$mymap <- renderLeaflet({ 
                basemap
        })
        
        observeEvent(input$plot_date, {
                leafletProxy("mymap") %>% 
                        clearMarkers() %>%
                        clearShapes() %>%
                        
                        addPolygons(stroke = FALSE, smoothFactor = 0.2, fillOpacity = 0.4, fillColor = ~cv_pal(country_overview_large$CAT_rating),
                                    label = sprintf("<strong>%s</strong><br/>CAT Rating: %s<br/>Moratoria, bans, & limits: %g<br/>Subsidy Removals: %d<br/>Divestments: %g", 
                                                    country_overview_large$Country, country_overview_large$CAT_rating, country_overview_large$Moratoria_bans_limits, country_overview_large$Subsidy_removal, 
                                                    country_overview_large$Divestment) %>% lapply(htmltools::HTML),
                                    labelOptions = labelOptions(
                                            style = list("font-weight" = "normal", padding = "3px 8px", "color" = All_policies),
                                            textsize = "15px", direction = "auto")) %>%
                        
                        
                        addCircleMarkers(data = country_overview_large, lat = ~ latitude, lng = ~ longitude, weight = 1, radius = ~(policy_total)^(1/3), 
                                         fillOpacity = 0.2, color = All_policies, group = "All Policies",
                                         label = sprintf("<strong>%s</strong><br/>Moratoria, bans, & limits: %g<br/>Subsidy Removals: %d<br/>Divestments: %g", 
                                                         country_overview_large$Country, country_overview_large$Moratoria_bans_limits, country_overview_large$Subsidy_removal, 
                                                         country_overview_large$Divestment) %>% lapply(htmltools::HTML),
                                         labelOptions = labelOptions(
                                                 style = list("font-weight" = "normal", padding = "3px 8px", "color" = All_policies),
                                                 textsize = "15px", direction = "auto")) %>% 
                        
                        addCircleMarkers(data = country_overview_large, lat = ~ latitude, lng = ~ longitude, weight = 1, radius = ~(Moratoria_bans_limits)^(1/3), 
                                         fillOpacity = 0.2, color = Moratoria_bans_limits, group = "Moratoria, Bans, & Limits",
                                         label = sprintf("<strong>%s</strong><br/>Moratoria, bans, & limits: %g", 
                                                         country_overview_large$Country, country_overview_large$Moratoria_bans_limits) %>% lapply(htmltools::HTML),
                                         labelOptions = labelOptions(
                                                 style = list("font-weight" = "normal", padding = "3px 8px", "color" = Moratoria_bans_limits),
                                                 textsize = "15px", direction = "auto")) %>% 
                        
                        addCircleMarkers(data = country_overview_large, lat = ~ latitude, lng = ~ longitude, weight = 1, radius = ~(Subsidy_removal)^(1/3), 
                                         fillOpacity = 0.2, color = Subsidy_removal, group = "Subsidy Removal",
                                         label = sprintf("<strong>%s</strong><br/>Subsidy Removals: %g", 
                                                         country_overview_large$Country, country_overview_large$Subsidy_removal) %>% lapply(htmltools::HTML),
                                         labelOptions = labelOptions(
                                                 style = list("font-weight" = "normal", padding = "3px 8px", "color" = Subsidy_removal),
                                                 textsize = "15px", direction = "auto")) %>% 
                        
                        addCircleMarkers(data = country_overview_large, lat = ~ latitude, lng = ~ longitude, weight = 1, radius = ~(Divestment)^(1/3), 
                                         fillOpacity = 0.2, color = Divestment, group = "Divestment",
                                         label = sprintf("<strong>%s</strong><br/>Divestments: %g", 
                                                         country_overview_large$Country, country_overview_large$Divestment) %>% lapply(htmltools::HTML),
                                         labelOptions = labelOptions(
                                                 style = list("font-weight" = "normal", padding = "3px 8px", "color" = Divestment),
                                                 textsize = "15px", direction = "auto"))
        })
        
}

runApp(shinyApp(ui, server), launch.browser = TRUE)
shinyApp(ui, server)

## Deploying app to shiny.io
#library(rsconnect)
#rsconnect::deployApp(account="fuenal")

## Mapping with reactive dates
### DATA PROCESSING: Policies converting Year from numeric to date format###
moratoria_bans_limits$Start <-lubridate::ymd(moratoria_bans_limits$Start, truncated = 2L)
subsidiy_removal$Start <-lubridate::ymd(subsidiy_removal$Start, truncated = 2L)
divestment$Start <-lubridate::ymd(divestment$Start, truncated = 2L)

# extract dates from moratoria_bans_limits data
moratoria_bans_limits$date = as.Date(moratoria_bans_limits$Start, format="%d/%m/%Y")
moratoria_bans_limits_min_date = min(moratoria_bans_limits$Start)
moratoria_bans_limits_max_date = max(moratoria_bans_limits$Start)
moratoria_bans_limits_max_date_clean = format(as.POSIXct(moratoria_bans_limits_max_date),"%d/%m/%Y")

# extract dates from moratoria_bans_limits data
subsidiy_removal$date = as.Date(subsidiy_removal$Start, format="%d/%m/%Y")
subsidiy_removal_min_date = min(subsidiy_removal$Start)
subsidiy_removal_max_date = max(subsidiy_removal$Start)
subsidiy_removal_max_date_clean = format(as.POSIXct(subsidiy_removal_max_date),"%d/%m/%Y")

# extract dates from moratoria_bans_limits data
divestment$date = as.Date(divestment$Start, format="%d/%m/%Y")
divestment_min_date = min(divestment$Start)
divestment_max_date = max(divestment$Start)
divestment_max_date_clean = format(as.POSIXct(divestment_max_date),"%d/%m/%Y")

# Set current date general
current_date = as.Date(max(moratoria_bans_limits$date),"%Y-%m-%d") 

#Set Main Plot output

reactive_case_count <- sum(country_overview_large$policy_total)
clean_date_reactive <- Sys.Date()


### MAP FUNCTIONS ###
# function to plot cumulative Moratoria, Bans, and Limit Policies by date
cumulative_mbl_plot = function(moratoria_bans_limits, plot_date) {
        plot_df = subset(moratoria_bans_limits, date<=plot_date)
        g1 <- ggplot(moratoria_bans_limits, aes(x = date, y = Policy)) + 
                geom_bar(position="stack", stat="identity", fill = Moratoria_bans_limits) + 
                ylab("Number of Moratoria, Bans, and Limit Policies") +  xlab("Year") + theme_bw() + ylim(0,50) +
                scale_fill_manual(values=c(Moratoria_bans_limits)) +
                xlim(c(moratoria_bans_limits_min_date,moratoria_bans_limits_max_date)) + 
                scale_x_date(date_labels = "%Y", limits=c(moratoria_bans_limits_min_date,moratoria_bans_limits_max_date)) +
                theme(legend.title = element_blank(), legend.position = "", plot.title = element_text(size=10), 
                      plot.margin = margin(5, 5, 5, 5))
        g1
}

# function to plot cumulative Divestments by date
cumulative_div_plot = function(divestment, plot_date) {
        plot_df = subset(divestment, date<=plot_date)
        g1 <- ggplot(divestment, aes(x = date, y = Policy)) + 
                geom_bar(position="stack", stat="identity", fill = Divestment) + 
                ylab("Number of Divestments") +  xlab("Year") + theme_bw() + ylim(0,500) +
                scale_fill_manual(values=c(Divestment)) +
                xlim(c(divestment_min_date,divestment_max_date)) + 
                scale_x_date(date_labels = "%Y", limits=c(divestment_min_date,divestment_max_date)) +
                theme(legend.title = element_blank(), legend.position = "", plot.title = element_text(size=10), 
                      plot.margin = margin(5, 5, 5, 5))
        g1
}

# function to plot cumulative subsidiy_removal by date
cumulative_sr_plot = function(subsidiy_removal, plot_date) {
        plot_df = subset(subsidiy_removal, date<=plot_date)
        g1 <- ggplot(subsidiy_removal, aes(x = date, y = Policy)) + 
                geom_bar(position="stack", stat="identity", fill = Subsidy_removal) + 
                ylab("Number of Subsidy Removals") +  xlab("Year") + theme_bw() + ylim(0,10) +
                scale_fill_manual(values=c(Subsidy_removal)) +
                xlim(c(subsidiy_removal_min_date,subsidiy_removal_max_date)) + 
                scale_x_date(date_labels = "%Y", limits=c(subsidiy_removal_min_date,subsidiy_removal_max_date)) +
                theme(legend.title = element_blank(), legend.position = "", plot.title = element_text(size=10), 
                      plot.margin = margin(5, 5, 5, 5))
        g1
}


})
output$cumulative_mbl_plot <- renderPlot({
        cumulative_mbl_plot(moratoria_bans_limits, formatted_date())
})

output$cumulative_div_plot <- renderPlot({
        cumulative_div_plot(divestment, formatted_date())
})
}

runApp(shinyApp(ui, server), launch.browser = TRUE)
shinyApp(ui, server)


## Tabs in the website

tabPanel("Country Profiles",
         sidebarLayout(
                 sidebarPanel(width = 2,
                              pickerInput("region_select", "Country:",   
                                          choices = as.character(country_overview_large$Country), 
                                          options = list(`none-selected-text` = "Please make a selection!"),
                                          selected = as.character(country_overview_large$Country)["United Kingdom"],
                                          multiple = FALSE),
                              "Select country from drop-down menues to update geographical information.",
                 ),
                 
                 mainPanel(
                         tabsetPanel(
                                 tags$div(
                                         tags$h2("Country Name & Flag"),
                                         tags$br(),tags$br(),tags$h3("Overview & Context"), 
                                         tags$h4("Total number of supply-side policies:"), tags$br(), 
                                         tags$b("Moratoria, Bans, Limitations: "), "99",tags$br(),
                                         tags$b("Subsidy Removals: "), "13 ",tags$br(),
                                         tags$b("Number of Divestments: "), "213",tags$br(),
                                         
                                         tags$br(),tags$br(),
                                         tags$h4("Breakdown of policies across sectors (government vs. non-government) and levels (country vs. state/city vs. organization): "), tags$br(), 
                                         tags$b("Number of national level governmental policies: "), "99 ",tags$br(),
                                         tags$b("Number of state/city governmental level policies: "), "13 ",tags$br(),
                                         tags$b("Number of non-governmental policies: "), "213",tags$br(),
                                         tags$br(),
                                         tags$br(),tags$br(),tags$h4("Sources"), 
                                         tags$br(),tags$br(),tags$h4("Groups to contact"), tags$br(), tags$br(), 
                                         tags$div(
                                                 infoBox("All policies", 10 * 200, icon = icon("list")),
                                                 infoBox("Moratoria, bans, & limits", 30 * 2, icon = icon("list")),
                                                 infoBox("Subsidy removals", 40 * 2, icon = icon("list")),
                                                 infoBox("Divestment", 90 * 200, icon = icon("list")),
                                         ),
                                 )
                         )
                 )
         )
),
tabPanel("Country comparisons",
         
         sidebarLayout(
                 sidebarPanel(width = 2,
                              pickerInput("region_select", "Country:",   
                                          choices = as.character(country_overview_large$Country), 
                                          options = list(`none-selected-text` = "Please make a selection!"),
                                          selected = as.character(country_overview_large$Country)["United Kingdom"],
                                          multiple = FALSE),
                              "Select country from drop-down menues to update geographical information.",
                              radioButtons('format', 'Document format', c('PDF', 'HTML', 'Word'),
                                           inline = TRUE),
                              downloadButton('downloadReport')
                 ),
                 
                 mainPanel(plotlyOutput("comparison_plot"), width = 6)
         )
),

tabPanel("Country Profiles",
         sidebarLayout(
                 sidebarPanel(
                         
                         span(tags$i(h6("Reported numbers of policies are subject to variation in policy types between countries.")), style="color:#045a8d"),
                         
                         pickerInput("level_select", "Level:",   
                                     choices = c("Global", "Continent", "Country", "Sub-national"), 
                                     selected = c("Country"),
                                     multiple = FALSE),
                         
                         pickerInput("region_select", "Country/Region:",   
                                     choices = as.character(country_overview_large$Country), 
                                     options = list(`actions-box` = TRUE, `none-selected-text` = "Please make a selection!"),
                                     selected = as.character(country_overview_large$country)[1:10],
                                     multiple = TRUE), 
                         
                         pickerInput("outcome_select", "Policy type:",   
                                     choices = c("Policies (total)", "Moratoria, Bans, Limitations", "Subsidy Removals", "Divestments"), 
                                     selected = c("Policies (total)"),
                                     multiple = FALSE),
                         
                         "Select level, regions, and policy types from drop-down menues to update geographical information."
                 ),
                 
                 mainPanel(
                         tabsetPanel(
                                 
                                 tags$div(
                                         tags$h2("Country Name & Flag"),
                                         tags$br(),tags$br(),tags$h3("Overview & Context"), 
                                         tags$h4("Total number of supply-side policies:"), tags$br(), 
                                         tags$b("Moratoria, Bans, Limitations: "), "99",tags$br(),
                                         tags$b("Subsidy Removals: "), "13 ",tags$br(),
                                         tags$b("Number of Divestments: "), "213",tags$br(),
                                         
                                         tags$br(),tags$br(),
                                         tags$h4("Breakdown of policies across sectors (government vs. non-government) and levels (country vs. state/city vs. organization): "), tags$br(), 
                                         tags$b("Number of national level governmental policies: "), "99 ",tags$br(),
                                         tags$b("Number of state/city governmental level policies: "), "13 ",tags$br(),
                                         tags$b("Number of non-governmental policies: "), "213",tags$br(),
                                         tags$br(),
                                         tags$br(),tags$br(),tags$h4("Sources"), 
                                         tags$br(),tags$br(),tags$h4("Groups to contact"), 
                                 )
                         )
                 )
         )
),

### Download Server Side

output$report_down <- downloadHandler(
        # For PDF output, change this to "report.pdf"
        filename = "report_template.html",
        content = function(file) {
                # Copy the report file to a temporary directory before processing it, in
                # case we don't have write permissions to the current working dir (which
                # can happen when deployed).
                tempReport <- file.path(tempdir(), "report.Rmd")
                file.copy("report_template.Rmd", tempReport, overwrite = TRUE)
                
                # Set up parameters to pass to Rmd document
                params <- list(selection = input$country,
                               data = country_overview_largeDF,
                               data_mbl = moratoria_bans_limitsDF,
                               data_sr = subsidiy_removalDF,
                               data_div = divestmentDF)
                
                # Knit the document, passing in the `params` list, and eval it in a
                # child of the global environment (this isolates the code in the document
                # from the code in this app).
                rmarkdown::render(tempReport, output_file = file,
                                  params = params,
                                  envir = new.env(parent = globalenv())
                )
        }
)

# render report when button clicked
observeEvent(input$report_down, {
        country_overview_largeDF <- country_overview_large[country_overview_large$Country == input$country, ]
        moratoria_bans_limitsDF <- moratoria_bans_limits[moratoria_bans_limits$Country == input$country, ]
        subsidiy_removalDF <- subsidiy_removal[subsidiy_removal$Country == input$country, ]
        divestmentDF <- divestment[divestment$Country == input$country, ]
        output$report <- renderUI({
                includeHTML(
                        rmarkdown::render(
                                "report_template.Rmd",
                                params = list(
                                        selection = input$country,
                                        data = country_overview_largeDF,
                                        data_mbl = moratoria_bans_limitsDF,
                                        data_sr = subsidiy_removalDF,
                                        data_div = divestmentDF
                                )
                        )
                )
        })
})

## RSelenium Sraping Divestment
## Testing out string processing
dfDemo2$Name_of_Organisation[1] <- str_replace(dfDemo2$Name_of_Organisation[1], pattern = '<a ', replacement = "")
dfDemo2$Name_of_Organisation[1] <- str_replace(dfDemo2$Name_of_Organisation[1], pattern = 'class=\"text-underline-none\"', replacement = "")
dfDemo2$Name_of_Organisation[1] <- str_replace(dfDemo2$Name_of_Organisation[1], pattern = ' href=\"', replacement = "'")
dfDemo2$Name_of_Organisation[1] <- str_replace(dfDemo2$Name_of_Organisation[1], pattern = ' ', replacement = '[')
dfDemo2$Name_of_Organisation[1] <- str_replace(dfDemo2$Name_of_Organisation[1], pattern = '\">', replacement = "' ")
dfDemo2$Name_of_Organisation[1] <- str_replace(dfDemo2$Name_of_Organisation[1], pattern = ' ', replacement = '[')
dfDemo2$Name_of_Organisation[1] <- str_replace(dfDemo2$Name_of_Organisation[1], pattern = '</a>', replacement = '')
dfDemo2$Name_of_Organisation[1]

#######
dfDemo2 <- dfDemo2 %>% mutate_at(1, function(t) {
        str_replace(t, pattern = '<a ', replacement = "")
        str_replace(t, pattern = 'class=\"text-underline-none\"', replacement = "")
        str_replace(t, pattern = 'href=', replacement = "")
        str_replace(t, pattern = ' \"', replacement = "[")
        str_replace(t, pattern = '\">', replacement = "]")
        str_replace(t, pattern = ' ', replacement = '(')
        str_replace(t, pattern = '</a>', replacement = ')')
})

## Same as above for column 5

dfDemo2 <- read.csv("input_data/divestment_scrape.csv")
dfDemo2 <- dfDemo2 %>% select(-X)
str(dfDemo2)
head(dfDemo2$More_Info)
tail(dfDemo2$More_Info)
print(dfDemo2$More_Info)

dfDemo2$More_Info[1] <- str_replace(dfDemo2$More_Info[1], pattern = '<a ', replacement = "")
#dfDemo2$More_Info[1] <- str_replace(dfDemo2$More_Info[1], pattern = 'class=\"text-underline-none\"', replacement = "")
dfDemo2$More_Info[1] <- str_replace(dfDemo2$More_Info[1], pattern = 'href=\"', replacement = "'")
#dfDemo2$More_Info[1] <- str_replace(dfDemo2$More_Info[1], pattern = ' ', replacement = '[')
dfDemo2$More_Info[1] <- str_replace(dfDemo2$More_Info[1], pattern = '\">→</a>', replacement = "'")
dfDemo2$More_Info[1] <- str_replace(dfDemo2$More_Info[1], pattern = ' ', replacement = '[')
dfDemo2$More_Info[1] <- str_replace(dfDemo2$More_Info[1], pattern = '</a>', replacement = '')
dfDemo2$More_Info[1]


# , data_mbl(), data_sr(), data_div())

# render report when button clicked
observeEvent(input$render, {
        country_overview_largeDF <- country_overview_large[country_overview_large$Country == input$country, ]
        moratoria_bans_limitsDF <- moratoria_bans_limits[moratoria_bans_limits$Country == input$country, ]
        subsidiy_removalDF <- subsidiy_removal[subsidiy_removal$Country == input$country, ]
        divestmentDF <- divestment[divestment$Country == input$country, ]
        output$report <- renderUI({
                includeHTML(
                        rmarkdown::render(
                                "report_template.Rmd",
                                params = list(
                                        selection = input$country,
                                        data_overview = country_overview_largeDF,
                                        data_mbl = moratoria_bans_limitsDF,
                                        data_sr = subsidiy_removalDF,
                                        data_div = divestmentDF
                                )
                        )
                )
        })
})
}

# Filter out country_overview_large for 0 values
reactive_db = reactive({
        country_overview_large %>% filter(Policy_total>0)
})

reactive_db_large = reactive({
        country_overview_large = reactive_db() %>% filter(ISO3 %in% worldcountry$ADM0_A3)
        #large_countries = reactive %>% filter(alpha3 %in% worldcountry$ADM0_A3)
        worldcountry_subset = worldcountry[worldcountry$ADM0_A3 %in% country_overview_large$ISO3, ]
        country_overview_large = country_overview_large[match(worldcountry_subset$ADM0_A3, country_overview_large$ISO3),]
        country_overview_large
})


## Mobile Responisveness testing

tabPanel("Supply Side Policy Mapper",
         div(class="outer",
             tags$head(includeCSS("styles.css")),
             leafletOutput("mymap", width="100%", height="100%"),
             
             absolutePanel(id = "controls", class = "panel panel-default",
                           top = 75, left = 55, width = 300, fixed=TRUE,
                           draggable = TRUE, height = "auto",
                           
                           span(tags$i(h6("Reported numbers of policies are subject to variation in policy types between countries.")), style="color:#045a8d"),
                           h4(textOutput("policy_count"), align = "right"),
                           h5(textOutput("gov_pol_count"), align = "right"),
                           h5(textOutput("Non_gov_pol_count"), align = "right"),
                           #h6(textOutput("mbl_count"), align = "right"), 
                           #h6(textOutput("div_count"), align = "right"), 
                           #h6(textOutput("sr_count"), align = "right"), 
                           plotOutput("cumulative_mbl_plot", height="185px", width="100%"),
                           plotOutput("cumulative_div_plot", height="175px", width="100%"),
                           plotOutput("cumulative_sr_plot", height="175px", width="100%"),
                           
             ),
             
             absolutePanel(id = "logo", class = "card", bottom = 20, left = 20, width = 80, fixed=TRUE, draggable = FALSE, height = "auto",
                           tags$a(href='https://fossilfueltreaty.org', tags$img(src='output-onlinepngtools.png',height='80',width='80')))
             
         )
),