---
title: "Reporte Covid-19 Chile"
output: 
  flexdashboard::flex_dashboard:
    #theme: readable
    logo: EA12_2.png
    #favicon: fae.png
    css: styles.css
    orientation: rows
    social: menu
    source_code: embed
    vertical_layout: fill
---

<style type="text/css">
.metricsgraphics-legend {
  margin-top:-20px;
  font-size:10pt;
  text-align:center;
}
.value-box .value {
    color: white;
}
.value-box .caption {
    color: white;
}
</style>


```{r setup, include=FALSE}
#------------------ Packages ------------------
library(readr)
library(dplyr)
library(flexdashboard)

#checks if there is data update on the Github version
#coronavirus::update_datasets(silence = TRUE)
#mudata2::update_datasets(coronavirus,silence = TRUE)

library(coronavirus)
library(covid19italy)

data(coronavirus)
data(italy_total)

`%>%` <- magrittr::`%>%`

#------------------ Parameters ------------------
# Set colors
# https://www.w3.org/TR/css-color-3/#svg-color

confirmed_color 	<- "purple"
new_color         <- "darkgoldenrod"
active_color 	    <- "#1f77b4"
recovered_color 	<- "forestgreen"
death_color 	    <- "red"

#------------------ Data ------------------

#---- df -------

confirmed  		<- read_csv(file = "https://raw.githubusercontent.com/MinCiencia/Datos-COVID19/master/output/producto3/CasosTotalesCumulativo.csv",col_names=T)
#recovered 		<- read_csv(file = "C:/Users/ctvas/Desktop/Tablero Coronavirus/Datos-COVID19-master/Datos-COVID19-master/output/producto3/CasosTotalesCumulativo.csv",col_names=T)
death      		<- read_csv(file = "https://raw.githubusercontent.com/MinCiencia/Datos-COVID19/master/output/producto14/FallecidosCumulativo.csv",col_names=T)
nuevos        <- read_csv(file = "https://raw.githubusercontent.com/MinCiencia/Datos-COVID19/master/output/producto13/CasosNuevosCumulativo.csv",col_names=T)
consintomas		<- read_csv(file = "https://raw.githubusercontent.com/MinCiencia/Datos-COVID19/master/output/producto26/CasosNuevosConSintomas.csv",col_names=T)
sinsintomas		<- read_csv(file = "https://raw.githubusercontent.com/MinCiencia/Datos-COVID19/master/output/producto27/CasosNuevosSinSintomas.csv",col_names=T)


confirmed  		<- confirmed[c(1,length(confirmed))]
death      		<- death[c(1,length(death))]
nuevos		    <- nuevos[c(1,length(nuevos))]	
consintomas		<- consintomas[c(1,length(consintomas))]
sinsintomas		<- sinsintomas[c(1,length(sinsintomas))]

names(confirmed) 		<- c("Region","Confirmados")
names(death)     		<- c("Region","Fallecidos")
names(nuevos) 		  <- c("Region","Casos Nuevos")
names(consintomas)  <- c("Region","Nuevos con Síntomas")
names(sinsintomas) 	<- c("Region","Nuevos sin Síntomas")


df <- dplyr::bind_cols(confirmed, death[2],nuevos[2],consintomas[2],sinsintomas[2])
df <-	df %>% 
		dplyr::filter(Region != "Total") 					%>%
		dplyr::arrange(-Confirmados)						%>%
		dplyr::mutate(Region = factor(Region, levels = rev(Region))) 

#---- df_daily -------

cum_recovered 	<- read_csv(file = "https://raw.githubusercontent.com/MinCiencia/Datos-COVID19/master/output/producto5/TotalesNacionales_T.csv",col_names=T)
cum_recovered   <- cum_recovered %>%
				dplyr::rename(recovered_cum = "Casos recuperados por FD", date = Fecha) %>%
				dplyr::select(date,recovered_cum) %>%
				dplyr::mutate(date = as.character(date))

cum_death	<- read_csv(file = "https://raw.githubusercontent.com/MinCiencia/Datos-COVID19/master/output/producto14/FallecidosCumulativo.csv",col_names=T)
cum_death	<- cum_death %>%
  			    	dplyr::filter(Region == "Total")	
cum_death <- tidyr::gather(cum_death, 2:length(cum_death), key = "date", value = "death_cum")   %>%
  				    dplyr::select(-Region)                          
  
cum_confirmed	 <- read_csv(file = "https://raw.githubusercontent.com/MinCiencia/Datos-COVID19/master/output/producto3/CasosTotalesCumulativo.csv",col_names=T)
cum_confirmed	 <- cum_confirmed %>%
  			    	      dplyr::filter(Region == "Total")	
cum_confirmed  <- tidyr::gather(cum_confirmed, 2:length(cum_confirmed), key = "date", value = "confirmed_cum")   %>%
  				          dplyr::select(-Region)                          

cum_act <- read_csv(file = "https://raw.githubusercontent.com/MinCiencia/Datos-COVID19/master/output/producto5/TotalesNacionales_T.csv",col_names=T)
cum_act	<- cum_act 										%>%
				    dplyr::rename(date = Fecha, active_cum = "Casos activos por FD") 	%>%
				    dplyr::select(date,active_cum)					%>%
				    dplyr::mutate(date = as.character(date))	

df_daily <- cum_confirmed %>%
				      dplyr::left_join(cum_recovered) %>%
				      dplyr::left_join(cum_death)	  %>%
				      dplyr::left_join(cum_act)	  %>%	
				      tidyr::replace_na(list(recovered_cum = 0, death_cum = 0, active_cum = 0)) %>%
		            dplyr::mutate(date = as.Date(date))

df_daily <- df_daily %>%
			        mutate(new_recovered_cum = confirmed_cum - death_cum - active_cum)

df1 <- coronavirus %>% dplyr::filter(date == max(date))

library(scales)


new_cases 	 <- read_csv(file = "https://raw.githubusercontent.com/MinCiencia/Datos-COVID19/master/output/producto5/TotalesNacionales_T.csv",col_names=T)
new_cases	 <- new_cases 												%>%
				dplyr::rename(date = Fecha, new  = "Casos nuevos totales") 	%>%
				dplyr::select(date,new)

df_ncases    <- new_cases  %>%
				dplyr::mutate(variacion =  round(c(0,diff(new)/new[1:(length(new)-1)]),2)) %>%
				dplyr::mutate(variacion = replace(variacion,list=which(variacion %in% c(Inf,-Inf,NA,NaN)),round(mean(variacion[which(!(variacion %in% c(Inf,-Inf,NA,NaN)))]),0))) %>%
				dplyr::mutate(variacion = formattable::percent(variacion,digits = 0))

casos_act 	 <- read_csv(file = "https://raw.githubusercontent.com/MinCiencia/Datos-COVID19/master/output/producto5/TotalesNacionales_T.csv",col_names=T)
casos_act	 <- casos_act 												%>%
				dplyr::rename(date = Fecha, Activos  = "Casos activos por FD") 	%>%
				dplyr::select(date,Activos)

casos_act   <- casos_act  %>%
				dplyr::mutate(variacion =  round(c(0,diff(Activos)/Activos[1:(length(Activos)-1)]),2)) %>%
				dplyr::mutate(variacion = replace(variacion,list=which(variacion %in% c(Inf,-Inf,NA,NaN)),round(mean(variacion[which(!(variacion %in% c(Inf,-Inf,NA,NaN)))]),0))) %>%
				dplyr::mutate(variacion = formattable::percent(variacion,digits = 0))


#new_cases 	 <- read_csv(file = "https://raw.githubusercontent.com/MinCiencia/Datos-COVID19/master/output/producto5/TotalesNacionales.csv",col_names=T)
#new_cases 	 <- new_cases %>% 
#				dplyr::filter(Fecha == "Casos nuevos totales") %>%
#				dplyr::mutate(Fecha = ifelse(Fecha == "Casos nuevos totales","Nuevos",NA))


#df_ncases    <- tidyr::gather(new_cases, 2:length(new_cases), key = "date", value = "new")  %>%                           
#     			    	dplyr::select(-Fecha)  %>%
#				dplyr::mutate(date = as.Date(date), variacion =  round(c(0,diff(new)/new[1:(length(new)-1)]),2)) %>%
#				dplyr::mutate(variacion = replace(variacion,list=which(variacion %in% c(Inf,-Inf,NA,NaN)),round(mean(variacion[which(!(variacion %in% c(Inf,-Inf,NA,NaN)))]),0))) %>%
#				dplyr::mutate(variacion = formattable::percent(variacion,digits = 0))


df_trajectory     <- read_csv(file = "https://raw.githubusercontent.com/MinCiencia/Datos-COVID19/master/output/producto3/CasosTotalesCumulativo_T.csv",col_names=T)
df_trajectory     <- df_trajectory 						%>%
				dplyr::mutate(date = as.Date(Region))	%>%
				dplyr::select(-Region,-Total)			%>%
				dplyr::select(date,Metropolitana,everything())

df_traj_region     <- read_csv(file = "https://raw.githubusercontent.com/MinCiencia/Datos-COVID19/master/output/producto13/CasosNuevosCumulativo_T.csv",col_names=T) %>%
				dplyr::mutate(Fecha = as.Date(Region))	%>%
				dplyr::select(-Total,-Region)	   		%>%
				dplyr::select(Fecha,everything())

dfact_traj_region	<- read_csv(file = "https://raw.githubusercontent.com/MinCiencia/Datos-COVID19/master/output/producto19/CasosActivosPorComuna_std.csv",col_names=T) %>%
				dplyr::filter(Comuna == "Total", !is.na(Region))	

orden_region	<- data_frame(Region = dfact_traj_region$Region[1:16],ID=1:16)

dfact_traj_region	<-	dfact_traj_region	%>%
					dplyr::left_join(orden_region,by = "Region")	%>%
					dplyr::arrange(ID, Region,Fecha)			%>%
					dplyr::rename(Activos = "Casos activos")		%>%
					dplyr::select(Region, Fecha, Activos)		%>%
					dplyr::mutate(Region = factor(Region,levels = orden_region$Region))	%>%			
					tidyr::spread(key = Region, value = Activos)  %>%
          dplyr::rename("O'Higgins" = "Del Libertador General Bernardo O’Higgins")

rm(orden_region)

df_act_traj_comuna <- read_csv(file = "https://raw.githubusercontent.com/MinCiencia/Datos-COVID19/master/output/producto19/CasosActivosPorComuna_std.csv",col_names=T) %>%
				dplyr::filter(Region == "Metropolitana", Comuna != "Total")	%>%
				dplyr::arrange(Comuna,Fecha)						%>%
				dplyr::rename(Activos = "Casos activos")				%>%
				dplyr::select(Comuna, Fecha, Activos)				%>%			
				tidyr::spread(key = Comuna, value = Activos)

library(readr)
library(plotly)
library(ozmaps)
library(sf)
library(chilemapas)
library(mapview)

confirmedmap  <- read_csv(file = "https://raw.githubusercontent.com/MinCiencia/Datos-COVID19/master/output/producto3/CasosTotalesCumulativo.csv",col_names=T)
confcomudmap  <- read_csv(file = "https://raw.githubusercontent.com/MinCiencia/Datos-COVID19/master/output/producto1/Covid-19.csv",col_names=T) %>%
                  filter(!is.na(Poblacion))

pcr           <- read_csv(file = "https://raw.githubusercontent.com/MinCiencia/Datos-COVID19/master/output/producto7/PCR.csv",col_names=T)

confirmedmap  	  <- confirmedmap[c(1,length(confirmedmap))]
names(confirmedmap) <- c("Region","Confirmados")
confirmedmap        <- confirmedmap%>% 
				dplyr::mutate(ID = 1:17)

confcomudmap	  <- confcomudmap[c(3,4,5,length(confcomudmap)-1,length(confcomudmap))]
names(confcomudmap) <- c("Comuna","codigo_comuna","Poblacion_comuna", "confirmed_comuna", "Tasa_comuna")



names(pcr)[2] <- "codigo_region" 
pcr           <- pcr %>% 
			dplyr::select(Region, codigo_region, Poblacion) %>%
			dplyr::mutate(ID = 1:16)

df_mapa	<-   dplyr::inner_join(pcr,confirmedmap,by = "ID") %>%
		     	dplyr::mutate(Tasa =  round((Confirmados/Poblacion)*100000,2)) 
#			%>%
#			dplyr::mutate(FactorTasa = cut(Tasa,breaks = seq(min(Tasa),max(Tasa),length = 10),include.lowest=TRUE,ordered_result=T)) %>%
#			dplyr::mutate(FactorTasa = factor(FactorTasa, levels = levels(FactorTasa)))

Nmapa_regiones <-	generar_regiones(mapa = dplyr::filter(chilemapas::mapa_comunas,!(codigo_comuna %in% c("05104","05201"))))
Nmapa_regiones <- Nmapa_regiones							%>%
		      	dplyr::left_join(df_mapa,by = "codigo_region")  %>%
				dplyr::rename("Región" = Region.x,
							"Tasa Confirmados por 100,000" = Tasa)	%>%
				dplyr::select(-Region.y,-ID)

confcomudmap <- confcomudmap %>%
                  mutate(codigo_comuna = as.numeric(codigo_comuna))

Nmapa_comunas <- chilemapas::mapa_comunas 					%>%
          dplyr::mutate(codigo_comuna = as.numeric(codigo_comuna))         %>%
		     	dplyr::left_join(df_mapa,by = "codigo_region") 		%>%
			    dplyr::left_join(confcomudmap,by = "codigo_comuna") 	%>%
			    dplyr::select(-ID,-Region.y)					%>%
			    dplyr::rename("Código Comuna" = codigo_comuna,
					              "Código Provincia" = codigo_provincia,
					              Region  = Region.x,
					              "Población Comuna" = Poblacion_comuna,
					              "Confirmados Comuna" = confirmed_comuna,
					              "Tasa Confirmados por 100,000 comuna"= Tasa_comuna)							

filtro_region <- dplyr::distinct(Nmapa_comunas, codigo_region, Region, Confirmados) 	%>%
			dplyr::arrange(desc(Confirmados)) 							%>%
			dplyr::filter(codigo_region != "13") 					


Nmapa_comunas <- Nmapa_comunas %>%
			dplyr::rename("Tasa Confirmados por 100,000" = Tasa)	


shp_chile_1   = sf::st_as_sf(dplyr::filter(Nmapa_regiones,codigo_region %in% c("01","02","03","04","05","06","07","15","13"))%>%
					dplyr::rename("Código Región" = codigo_region))
	
shp_chile_2   = sf::st_as_sf(dplyr::filter(Nmapa_regiones,!(codigo_region %in% c("01","02","03","04","05","06","07","15","13")))%>%
					dplyr::rename("Código Región" = codigo_region))


shp_santiago = sf::st_as_sf(dplyr::filter(Nmapa_comunas,codigo_region=="13")%>% dplyr::rename("Código Región" = codigo_region, "Región" = Region, "Población"= Poblacion))

assign(paste0("shp_",gsub(" ", "",filtro_region$Region[1],fixed = TRUE)),sf::st_as_sf(dplyr::filter(Nmapa_comunas,!("Código Comuna" %in% c("05104","05201")),codigo_region==filtro_region$codigo_region[1])) %>% dplyr::rename("Código Región" = codigo_region, "Región" = Region, "Población"= Poblacion))
assign(paste0("shp_",gsub(" ", "",filtro_region$Region[2],fixed = TRUE)),sf::st_as_sf(dplyr::filter(Nmapa_comunas,!("Código Comuna" %in% c("05104","05201")),codigo_region==filtro_region$codigo_region[2])) %>% dplyr::rename("Código Región" = codigo_region, "Región" = Region,"Población"= Poblacion))
assign(paste0("shp_",gsub(" ", "",filtro_region$Region[3],fixed = TRUE)),sf::st_as_sf(dplyr::filter(Nmapa_comunas,!("Código Comuna" %in% c("05104","05201")),codigo_region==filtro_region$codigo_region[3])) %>% dplyr::rename("Código Región" = codigo_region, "Región" = Region, "Población"= Poblacion))

```

Resumen
=======================================================================
Row
-----------------------------------------------------------------------

### confirmed {.value-box}

```{r}

valueBox(value = paste(format(sum(df$Confirmados), big.mark = ","), "", sep = " "), 
         caption = "Total Casos Confirmados", 
         icon = "fas fa-user-md", 
         color = confirmed_color)
```

### new {.value-box}

```{r}

valueBox(value = paste(format(sum(df$"Casos Nuevos"), big.mark = ","), "", sep = " "), 
         caption = "Casos Nuevos", 
         icon = "fas fa-users", 
         color = new_color)
```


### active {.value-box}

```{r}
valueBox(value = paste(format(df_daily$active_cum[length(df_daily$active_cum)], big.mark = ","), " (",
                       round(100 * sum(df_daily$active_cum[length(df_daily$active_cum)], na.rm = TRUE) / sum(df$Confirmados), 1), 
                       "%)", sep = ""), 
         caption = "Casos Activos (FD)", icon = "fas fa-ambulance", 
         color = active_color)
```

### recovered {.value-box}

```{r}
valueBox(value = paste(format(df_daily$new_recovered_cum[length(df_daily$new_recovered_cum)], big.mark = ","), " (",
                       round(100 * sum(df_daily$new_recovered_cum[length(df_daily$new_recovered_cum)], na.rm = TRUE) / sum(df$Confirmados), 1), 
                       "%)", sep = ""), 
         caption = "Casos Recuperados (FD)", icon = "fas fa-heartbeat", 
         color = recovered_color)
```

### death {.value-box}

```{r}

valueBox(value = paste(format(sum(df$Fallecidos, na.rm = TRUE), big.mark = ","), " (",
                       round(100 * sum(df$Fallecidos, na.rm = TRUE) / sum(df$Confirmados), 1), 
                       "%)", sep = ""),
         caption = "Casos Fallecidos", 
         icon = "fas fa-heart-broken", 
         color = death_color)
```


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

### Distribución de Casos Confirmados por Región

```{r daily_summary}

plotly::plot_ly(data = df[1:16,], 
                labels = ~ Region, 
                values = ~ Confirmados,
		    textposition = 'inside',
        	    textinfo = 'label+percent',
		    insidetextfont = list(color = '#FFFFFF'),
                # text =  ~ confirmed, 
                # textposition = 'auto',
                type = "pie", 
                name = "Confirmed",
		    domain = list(x = c(0, 0.5), y = c(0, 1)),	
                marker = list(color = active_color),
		            hole = 0.4) %>%
plotly::layout(annotations=list(text="Confirmados",showarrow =F,x = 0.20,y = 0.5,size = 35), "showarrow"=F,font=list(color="blue")) %>%
plotly::add_trace(data = df[1:16,], 
                labels = ~ Region, 
                values = ~ Fallecidos,
		    textposition = 'inside',
        	    textinfo = 'label+percent',
		    insidetextfont = list(color = '#FFFFFF'),
                # text =  ~ confirmed, 
                # textposition = 'auto',
                type = "pie", 
                name = "Death",
		    domain = list(x = c(0.5, 1), y = c(0, 1)),
                marker = list(color = active_color),
		            hole = 0.4) %>%
plotly::layout(annotations=list(text="Fallecidos",showarrow =F,x = 0.79,y = 0.5,size = 35), "showarrow"=F,font=list(color="blue"))
  


```

### Gráfico de Casos Confirmados por Región 

```{r, out.width = "20%"}
library(plotly)
p <- plot_ly()%>%
  layout(title = "Tendencia",
         xaxis = list(title = ""),
         yaxis = list (title = "Casos Confirmados Acumulados") )

ToAdd <- setdiff(colnames(df_trajectory),"date")

for(i in ToAdd){
  p <- p %>% add_trace(x = df_trajectory[["date"]], y = df_trajectory[[i]], name = i,
                       type = 'scatter',
                       mode = 'line+markers',
                       line = list(width = 4))
}

p
```


Row {data-width=400}
-----------------------------------------------------------------------


### Casos Acumulados Diarios por Diagnostico {.no-padding}
    
```{r}

# plotly::plot_ly(df_daily, x = ~date, y = ~active_cum, name = 'Active', type = 'scatter', mode = 'none', stackgroup = 'one', fillcolor = "#1f77b4") %>%
# plotly::add_trace(y = ~recovered_cum, name = 'Recovered', fillcolor = "green") %>%
# plotly::add_trace(y = ~death_cum, name = "Death", fillcolor = "red") %>%
#   plotly::layout(title = "",
#          xaxis = list(title = "",
#                       showgrid = FALSE),
#          yaxis = list(title = "Cumulative Number of Cases",
#                       showgrid = FALSE),
#          legend = list(x = 0.1, y = 0.9),
#                  hovermode = "compare")


plotly::plot_ly(data = df_daily,
                x = ~ date,
                y = ~ active_cum, 
                name = 'Activos', 
                fillcolor = active_color,
                type = 'scatter',
                mode = 'none', 
                stackgroup = 'one') %>%
  plotly::add_trace(y = ~ new_recovered_cum,
                    name = "Recuperados (FD)",
                    fillcolor = recovered_color) %>%
  plotly::add_trace(y = ~ death_cum,
                    name = "Fallecidos",
                    fillcolor = death_color) %>%
  plotly::layout(title = "",
                 yaxis = list(title = "Número de Casos Acumulados"),
                 xaxis = list(title = "Date"),
                 legend = list(x = 0.1, y = 0.9),
                 hovermode = "compare")
  

```


### Casos Confirmados, Fallecidos, Casos Nuevos y Tasa de Letalidad por Región
    
```{r}
df_summary <- df %>%
		  dplyr::mutate("Letalidad" = Fallecidos / Confirmados)  

df_summary %>% 	DT::datatable(rownames = FALSE,
            		#colnames = c("Region", "Confirmados", "Fallecidos", "Death Rate"),
            		options = list(pageLength = nrow(df_summary), dom = 'tip')) %>%
  			DT::formatPercentage("Letalidad", 2)

```


Mapa Chile
=======================================================================

Column {data-width=400}
-------------------------------------
    
### Zona Norte y Centro
    
```{r}
at_aux = sort(df_mapa$Confirmados,partial=(length(df_mapa$Confirmados)-1))[length(df_mapa$Confirmados)-1]
at_region = round(c(lattice::do.breaks(endpoints = c(floor(min(df_mapa$Confirmados)), ceiling(at_aux)), nint = 6),lattice::do.breaks(endpoints = c(ceiling(at_aux), max(df_mapa$Confirmados)), nint = 4)[-1]),0)
#at_10 = round(as.numeric(quantile(df_mapa$Confirmados,probs = seq(0, 1, 0.2)),0))

#at_10 = round(lattice::do.breaks(endpoints = c(floor(min(df_mapa$confirmed)), ceiling(max(df_mapa$confirmed))), nint = 4),0)

shp_chile_1 <- rename(shp_chile_1,"Población" = Poblacion)

mapview(shp_chile_1,
  zcol = "Confirmados",
  alpha = 0.5,
  map.types = c("OpenStreetMap","CartoDB.Positron","CartoDB.DarkMatter","Esri.WorldImagery","OpenTopoMap"),
  layer.name = "Casos Confirmados",
  legend = TRUE,
  at = at_region
)
```


### Zona Sur

```{r}

shp_chile_2 <- rename(shp_chile_2,"Población" = Poblacion)

mapview(shp_chile_2,
  zcol = "Confirmados",
  alpha = 0.5,
  map.types = c("OpenStreetMap","CartoDB.Positron","CartoDB.DarkMatter","Esri.WorldImagery","OpenTopoMap"),
  layer.name = "Casos Confirmados",
  legend = TRUE,
  at    = at_region
)

```


Mapas Regiones
=======================================================================

Column {data-width=400}
-------------------------------------

### Mapa Santiago

```{r}

at_auxcom = sort(Nmapa_comunas$"Confirmados Comuna",partial=(length(Nmapa_comunas$"Confirmados Comuna")-1))[length(Nmapa_comunas$"Confirmados Comuna")-1]
#at_comuna = round(c(lattice::do.breaks(endpoints = c(floor(min(Nmapa_comunas$"Confirmados Comuna")), ceiling(at_auxcom)), nint = 6),lattice::do.breaks(endpoints = c(ceiling(at_auxcom), max(Nmapa_comunas$"Confirmados Comuna")), nint = 4)[-1]),0)

at_comuna = round(c(lattice::do.breaks(endpoints = c(floor(min(Nmapa_comunas$"Confirmados Comuna")), ceiling(quantile(Nmapa_comunas$"Confirmados Comuna",p=0.9,names=F))), nint = 6),lattice::do.breaks(endpoints = c(ceiling(quantile(Nmapa_comunas$"Confirmados Comuna",p=0.9,names=F)), max(Nmapa_comunas$"Confirmados Comuna")), nint = 4)[-1]),0)


#at_comuna = round(lattice::do.breaks(endpoints = c(floor(min(Nmapa_comunas$"Confirmados Comuna")), ceiling(max(Nmapa_comunas$"Confirmados Comuna"))), nint = 8),0)

mapview(shp_santiago,
  zcol = "Confirmados Comuna",
  alpha = 0.5,
  map.types = c("OpenStreetMap","CartoDB.Positron","CartoDB.DarkMatter","Esri.WorldImagery","OpenTopoMap"),
  layer.name = "Casos Confirmados",
  legend = TRUE,
  at = at_comuna
)
```

### Mapa `r  gsub(" ", "",filtro_region$Region[1],fixed = TRUE)`

```{r}

mapview(eval(parse(text=paste0("shp_",gsub(" ", "",filtro_region$Region[1],fixed = TRUE)))),
  zcol = "Confirmados Comuna",
  alpha = 0.5,
  map.types = c("OpenStreetMap","CartoDB.Positron","CartoDB.DarkMatter","Esri.WorldImagery","OpenTopoMap"),
  layer.name = "Casos Confirmados",
  legend = TRUE,
  at = at_comuna
)
```

Column {data-width=400}
-------------------------------------

### Mapa `r  gsub(" ", "",filtro_region$Region[2],fixed = TRUE)`

```{r}

mapview(eval(parse(text=paste0("shp_",gsub(" ", "",filtro_region$Region[2],fixed = TRUE)))),
  zcol = "Confirmados Comuna",
  alpha = 0.5,
  map.types = c("OpenStreetMap","CartoDB.Positron","CartoDB.DarkMatter","Esri.WorldImagery","OpenTopoMap"),
  layer.name = "Casos Confirmados",
  legend = TRUE,
  at = at_comuna
)
```

### Mapa `r  gsub(" ", "",filtro_region$Region[3],fixed = TRUE)`

```{r}

mapview(eval(parse(text=paste0("shp_",gsub(" ", "",filtro_region$Region[3],fixed = TRUE)))),
  zcol = "Confirmados Comuna",
  alpha = 0.5,
  map.types = c("OpenStreetMap","CartoDB.Positron","CartoDB.DarkMatter","Esri.WorldImagery","OpenTopoMap"),
  layer.name = "Casos Confirmados",
  legend = TRUE,
  at = at_comuna
)
```

Casos Nuevos
=======================================================================

Column {data-width=400}
-------------------------------------

### Casos Nuevos Totales

```{r}
ay <- list(
  		tickfont = list(color = "red"),
  		overlaying = "y",
  		side = "right",
  		title = "Variación",
		tickformat = "%"
	)

plotly::plot_ly(data = df_ncases ,
                x = ~ date,
                y = ~ new, 
                name = 'Casos Nuevos', 
                #fillcolor = active_color,
                type = 'scatter',
                mode = 'line+markers', 
                stackgroup = 'one') %>%
  plotly::add_lines(data = df_ncases ,
                x = ~ date,
                y = ~ variacion,
		    name = 'Variación Diaria', 
		    yaxis = "y2")%>%	
  plotly::layout(title = "",
                 yaxis = list(title = "Casos Nuevos Diarios"),
                 xaxis = list(title = "Date"),
              #  legend = list(x = 1.05, y = 0.9),
                 hovermode = "compare",
		     yaxis2 = ay)
```

Column {data-width=400}
-------------------------------------

### Casos Nuevos por Región

```{r}
library(plotly)
plot_nregion <- plot_ly(df_traj_region, x = ~ Fecha)

ToAddRegion <- setdiff(colnames(df_traj_region),"Fecha")

for(i in ToAddRegion){
	if (i == "Arica y Parinacota"){
		plot_nregion <- plot_nregion %>% 
					add_trace(y = df_traj_region[[i]], name = i, mode = 'lines+markers')
						}
	if (i != "Arica y Parinacota"){
		plot_nregion <- plot_nregion %>% 
					add_trace(y = df_traj_region[[i]], name = i, visible = F, mode = 'lines+markers') 							
	}
}

plot_nregion <- plot_nregion %>% layout(
    						#title = "Tendencia de los Casos Nuevos",
		    				xaxis = list(rangeslider = "date"),
    						yaxis = list(title = "Casos Nuevos"),
				    		updatemenus = list(
      								list(
        									y = 1.0,
        									buttons = list(
												list(method = "restyle",
													args = list("visible", list(TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE)),
													label = ToAddRegion[1]),
												list(method = "restyle",
													args = list("visible", list(FALSE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE)),
													label = ToAddRegion[2]),
												list(method = "restyle",
													args = list("visible", list(FALSE, FALSE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE)),
													label = ToAddRegion[3]),
												list(method = "restyle",
													args = list("visible", list(FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE)),
													label = ToAddRegion[4]),
												list(method = "restyle",
													args = list("visible", list(FALSE, FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE)),
													label = ToAddRegion[5]),
												list(method = "restyle",
													args = list("visible", list(FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE)),
													label = ToAddRegion[6]),
												list(method = "restyle",
													args = list("visible", list(FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE)),
													label = ToAddRegion[7]),
												list(method = "restyle",
													args = list("visible", list(FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE)),
													label = ToAddRegion[8]),
												list(method = "restyle",
													args = list("visible", list(FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE)),
													label = ToAddRegion[9]),
												list(method = "restyle",
													args = list("visible", list(FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE)),
													label = ToAddRegion[10]),
												list(method = "restyle",
													args = list("visible", list(FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE)),
													label = ToAddRegion[11]),
												list(method = "restyle",
													args = list("visible", list(FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, FALSE, FALSE)),
													label = ToAddRegion[12]),
												list(method = "restyle",
													args = list("visible", list(FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, FALSE)),
													label = ToAddRegion[13]),
												list(method = "restyle",
													args = list("visible", list(FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, FALSE, FALSE)),
													label = ToAddRegion[14]),
												list(method = "restyle",
													args = list("visible", list(FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, FALSE)),
													label = ToAddRegion[15]),
												list(method = "restyle",
													args = list("visible", list(FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE)),
													label = ToAddRegion[16])))))


plot_nregion
```


Casos Activos
=======================================================================

Column {data-width=400}
-------------------------------------

### Casos Activos

```{r}
ay <- list(
  		tickfont = list(color = "red"),
  		overlaying = "y",
  		side = "right",
  		title = "Variación",
		tickformat = "%"
	)

plotly::plot_ly(data = casos_act ,
                x = ~ date,
                y = ~ Activos, 
                name = 'Casos Activos', 
                #fillcolor = active_color,
                type = 'scatter',
                mode = 'line+markers', 
                stackgroup = 'one') %>%
  plotly::layout(title = "",
                 yaxis = list(title = "Casos Activos Diarios"),
                 xaxis = list(title = "Date"),
              #  legend = list(x = 1.05, y = 0.9),
                 hovermode = "compare",
		     yaxis2 = ay)
```

Column {data-width=400}
-------------------------------------

### Casos Activos por Región

```{r}
library(plotly)
plot_actregion <- plot_ly(dfact_traj_region, x = ~ Fecha)

rm(ToAddRegion)
ToAddRegion <- setdiff(colnames(dfact_traj_region),"Fecha")

for(i in ToAddRegion){
	if (i == "Arica y Parinacota"){
		plot_actregion <- plot_actregion %>% 
					add_trace(y = dfact_traj_region[[i]], name = i, mode = 'lines+markers')
						}
	if (i != "Arica y Parinacota"){
		plot_actregion <- plot_actregion %>% 
					add_trace(y = dfact_traj_region[[i]], name = i, visible = F, mode = 'lines+markers') 							
	}
}

plot_actregion <- plot_actregion %>% layout(
    						#title = "Tendencia de los Casos Activos",
		    				xaxis = list(rangeslider = "date"),
    						yaxis = list(title = "Casos Ativos"),
				    		updatemenus = list(
      								list(x=1.2,
        									y = 0.9,
        									buttons = list(
												list(method = "restyle",
													args = list("visible", list(TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE)),
													label = ToAddRegion[1]),
												list(method = "restyle",
													args = list("visible", list(FALSE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE)),
													label = ToAddRegion[2]),
												list(method = "restyle",
													args = list("visible", list(FALSE, FALSE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE)),
													label = ToAddRegion[3]),
												list(method = "restyle",
													args = list("visible", list(FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE)),
													label = ToAddRegion[4]),
												list(method = "restyle",
													args = list("visible", list(FALSE, FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE)),
													label = ToAddRegion[5]),
												list(method = "restyle",
													args = list("visible", list(FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE)),
													label = ToAddRegion[6]),
												list(method = "restyle",
													args = list("visible", list(FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE)),
													label = ToAddRegion[7]),
												list(method = "restyle",
													args = list("visible", list(FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE)),
													label = ToAddRegion[8]),
												list(method = "restyle",
													args = list("visible", list(FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE)),
													label = ToAddRegion[9]),
												list(method = "restyle",
													args = list("visible", list(FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE)),
													label = ToAddRegion[10]),
												list(method = "restyle",
													args = list("visible", list(FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE)),
													label = ToAddRegion[11]),
												list(method = "restyle",
													args = list("visible", list(FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, FALSE, FALSE)),
													label = ToAddRegion[12]),
												list(method = "restyle",
													args = list("visible", list(FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, FALSE)),
													label = ToAddRegion[13]),
												list(method = "restyle",
													args = list("visible", list(FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, FALSE, FALSE)),
													label = ToAddRegion[14]),
												list(method = "restyle",
													args = list("visible", list(FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, FALSE)),
													label = ToAddRegion[15]),
												list(method = "restyle",
													args = list("visible", list(FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE)),
													label = ToAddRegion[16])))))


plot_actregion
```

### Casos Activos por Comuna Región Metropolitana

```{r}
library(plotly)
plot_actcomuna <- plot_ly(df_act_traj_comuna, x = ~ Fecha)


ToAddComuna <- setdiff(colnames(df_act_traj_comuna),"Fecha")

for(i in ToAddComuna ){
	if (i == "Alhue"){
		plot_actcomuna <- plot_actcomuna %>% 
					add_trace(y = df_act_traj_comuna[[i]], name = i, mode = 'lines+markers')
						}
	if (i != "Alhue"){
		plot_actcomuna <- plot_actcomuna %>% 
					add_trace(y = df_act_traj_comuna[[i]], name = i, visible = F, mode = 'lines+markers') 							
	}
}

rm(k)
for (k in 1:52){
	if(k == 1){
		assign(paste0("list",as.character(k)),c(list(TRUE),rep(list(FALSE),51)))
	}
	if(k == 52){
		assign(paste0("list",as.character(k)),c(rep(list(FALSE),51),list(TRUE)))
	}
	assign(paste0("list",as.character(k)),c(rep(list(FALSE),k-1),list(TRUE),rep(list(FALSE),52-k)))
}

rm(auxpaste0)
for (l in 1:52){
	if(l == 1){
		auxpaste0 = paste0("list(method = 'restyle',args = list('visible', list",l,"),label = ToAddComuna[",l,"]),")
	}
	else{
		if(l == 52){
			auxpaste0 <-  paste0(auxpaste0,paste0("list(method = 'restyle',args = list('visible', list",l,"),label = ToAddComuna[",l,"])"))
		}else{
			auxpaste0 <-  paste0(auxpaste0,paste0("list(method = 'restyle',args = list('visible', list",l,"),label = ToAddComuna[",l,"]),"))
		}
	}
}

plot_actcomuna <- plot_actcomuna %>% 
				layout(
    					#title = "Tendencia de los Casos Activos",
		    			xaxis = list(rangeslider = "date"),
    					yaxis = list(title = "Casos Activos"),
				    	updatemenus = list(
      							list(x=1.2,
        								y = 0.9,
        								buttons = list(
list(method = "restyle",args = list("visible", list1),label = ToAddComuna[1]),
list(method = "restyle",args = list("visible", list2),label = ToAddComuna[2]),
list(method = "restyle",args = list("visible", list3),label = ToAddComuna[3]),
list(method = "restyle",args = list("visible", list4),label = ToAddComuna[4]),
list(method = "restyle",args = list("visible", list5),label = ToAddComuna[5]),
list(method = "restyle",args = list("visible", list6),label = ToAddComuna[6]),
list(method = "restyle",args = list("visible", list7),label = ToAddComuna[7]),
list(method = "restyle",args = list("visible", list8),label = ToAddComuna[8]),
list(method = "restyle",args = list("visible", list9),label = ToAddComuna[9]),
list(method = "restyle",args = list("visible", list10),label = ToAddComuna[10]),
list(method = "restyle",args = list("visible", list11),label = ToAddComuna[11]),
list(method = "restyle",args = list("visible", list12),label = ToAddComuna[12]),
list(method = "restyle",args = list("visible", list13),label = ToAddComuna[13]),
list(method = "restyle",args = list("visible", list14),label = ToAddComuna[14]),
list(method = "restyle",args = list("visible", list15),label = ToAddComuna[15]),
list(method = "restyle",args = list("visible", list16),label = ToAddComuna[16]),
list(method = "restyle",args = list("visible", list17),label = ToAddComuna[17]),
list(method = "restyle",args = list("visible", list18),label = ToAddComuna[18]),
list(method = "restyle",args = list("visible", list19),label = ToAddComuna[19]),
list(method = "restyle",args = list("visible", list20),label = ToAddComuna[20]),
list(method = "restyle",args = list("visible", list21),label = ToAddComuna[21]),
list(method = "restyle",args = list("visible", list22),label = ToAddComuna[22]),
list(method = "restyle",args = list("visible", list23),label = ToAddComuna[23]),
list(method = "restyle",args = list("visible", list24),label = ToAddComuna[24]),
list(method = "restyle",args = list("visible", list25),label = ToAddComuna[25]),
list(method = "restyle",args = list("visible", list26),label = ToAddComuna[26]),
list(method = "restyle",args = list("visible", list27),label = ToAddComuna[27]),
list(method = "restyle",args = list("visible", list28),label = ToAddComuna[28]),
list(method = "restyle",args = list("visible", list29),label = ToAddComuna[29]),
list(method = "restyle",args = list("visible", list30),label = ToAddComuna[30]),
list(method = "restyle",args = list("visible", list31),label = ToAddComuna[31]),
list(method = "restyle",args = list("visible", list32),label = ToAddComuna[32]),
list(method = "restyle",args = list("visible", list33),label = ToAddComuna[33]),
list(method = "restyle",args = list("visible", list34),label = ToAddComuna[34]),
list(method = "restyle",args = list("visible", list35),label = ToAddComuna[35]),
list(method = "restyle",args = list("visible", list36),label = ToAddComuna[36]),
list(method = "restyle",args = list("visible", list37),label = ToAddComuna[37]),
list(method = "restyle",args = list("visible", list38),label = ToAddComuna[38]),
list(method = "restyle",args = list("visible", list39),label = ToAddComuna[39]),
list(method = "restyle",args = list("visible", list40),label = ToAddComuna[40]),
list(method = "restyle",args = list("visible", list41),label = ToAddComuna[41]),
list(method = "restyle",args = list("visible", list42),label = ToAddComuna[42]),
list(method = "restyle",args = list("visible", list43),label = ToAddComuna[43]),
list(method = "restyle",args = list("visible", list44),label = ToAddComuna[44]),
list(method = "restyle",args = list("visible", list45),label = ToAddComuna[45]),
list(method = "restyle",args = list("visible", list46),label = ToAddComuna[46]),
list(method = "restyle",args = list("visible", list47),label = ToAddComuna[47]),
list(method = "restyle",args = list("visible", list48),label = ToAddComuna[48]),
list(method = "restyle",args = list("visible", list49),label = ToAddComuna[49]),
list(method = "restyle",args = list("visible", list50),label = ToAddComuna[50]),
list(method = "restyle",args = list("visible", list51),label = ToAddComuna[51]),
list(method = "restyle",args = list("visible", list52),label = ToAddComuna[52])
))))


plot_actcomuna
```





Referencias
=======================================================================

**Reporte Coronavirus Chile**

Este reporte nace de la necesidad de visualizar y comunicar de una manera sencilla e interactiva la situación actual de Chile frente a la pandemia covid-19. Aquí se presentan las principales estadísticas y tendencias según las cifras oficiales entregadas por el Ministerio de Salud.

Usted puede encontrar información a nivel país, regional y por comuna. Esta en una etapa de desarrollo y se agregarán más funcionalidades.

**Datos**

Los datos utilizados en este reporte corresponde a la extracción realidad por la Mesa de Datos COVID-19 liderada por el Ministerio de Ciencia, Tecnología, Conocimiento e Innovación de Chile [MinCiencia](https://github.com/MinCiencia/Datos-COVID19) a las cifras oficiales informadas por el Ministerio de Salud [MinSal](https://www.gob.cl/coronavirus/cifrasoficiales/). Para los casos activos y recuperados se utiliza la fecha de diagnóstico (FD).


**Packages**

* Reporte interactivo - librería [flexdashboard](https://rmarkdown.rstudio.com/flexdashboard/). 
* Visualización - la librería para gráficos [plotly](https://plot.ly/r/). 
* Mapas - las librerías [mapview](https://github.com/r-spatial/mapview) y [sf](https://cran.r-project.org/web/packages/sf/index.html) para mapas y mapas de vectores.
* Mapa de Chile - la librería [chilemapas](https://github.com/pachamaltese/chilemapas/).
* Manipulación de datos - las librerías [dplyr](https://dplyr.tidyverse.org/) y [tidyr](https://tidyr.tidyverse.org/).
* Tablas - the [DT](https://rstudio.github.io/DT/) package

**Desarrollado** 

Cristian Vásquez: Profesor Docente Asistente (full time), Escuela de Administración. Facultad de Economía y Adminstración. Pontificia Universidad Católica de Chile.

Este reporte fue desarrollado con la increíble colaboración de Vania Acevedo y Julián León Vásquez.