output: flexdashboard::flex_dashboard: orientation: columns vertical_layout: fill runtime: shiny ---

General

Municipios con ATE activos

Tipo emergencia

form1$casusa <- if_else(form1$Tipo.de.emergencia == "Natural", form1$Causa.del.ATE, form1$Causa.del.ATE.1) 
form1$n <-1

x<- form1 %>% 
  select(Tipo.de.emergencia, casusa, n) %>% 
  group_by(Tipo.de.emergencia, casusa) %>% 
  summarise(n = sum(n)) %>% 
  filter(casusa != "")
## `summarise()` has grouped output by 'Tipo.de.emergencia'. You can override
## using the `.groups` argument.
  ggplot(x, aes(area = n, fill = Tipo.de.emergencia, label = casusa)) +
  geom_treemap() +
  geom_treemap_text()

Column

Tipo de ATE

form1 %>% 
  tabyl(Tipo.de.ATE) %>%
   adorn_pct_formatting() %>% 
  filter(Tipo.de.ATE != "") %>% 
ggplot(aes(x = "", y = n, fill = Tipo.de.ATE)) +
  geom_col() +
  geom_label(aes(label = percent),
             position = position_stack(vjust = 0.5),
             show.legend = FALSE) +
  coord_polar(theta = "y")+
  guides(fill = guide_legend(title = "Tipo de ATE")) +
  scale_fill_viridis_d() +
  coord_polar(theta = "y") + 
  theme_void()
## Coordinate system already present. Adding new coordinate system, which will
## replace the existing one.

Numero de ATE por Departamento

y1 <- form1 %>% 
  select(data_date, Department, n) %>% 
  group_by(data_date, Department) %>%
  summarise(n = sum(n))
## `summarise()` has grouped output by 'data_date'. You can override using the
## `.groups` argument.
ggplotly(
ggplot(y1, aes(x = as.Date(data_date), y = n, fill = Department)) +
  geom_stream(type = "ridge")+
  theme(axis.text.x = element_text(angle = 90))
)

Sanitario y Ambiental

Column

Agua Potable

form2$n <- 1

continuidad <- as.data.frame(c("Permanente", "Semanal", "No existe"))
colnames(continuidad)<- "Continuidad"

per <- as.data.frame(table(str_detect(form2$Continuidad.de.flujo.de.agua, "Permanen")))
sem <- as.data.frame(table(str_detect(form2$Continuidad.de.flujo.de.agua, "Seman")))
no <- as.data.frame(table(str_detect(form2$Continuidad.de.flujo.de.agua, "No")))

continuidad$Numero<- 0

continuidad[2,2]<- sem[2,2]
continuidad[1,2]<- per[2,2]
continuidad[3,2]<- no[2,2]

continuidad$porcentaje <- (continuidad$Numero * 100)/sum(continuidad$Numero)

ggplot(continuidad) +
 aes(x = Continuidad, y = porcentaje) +
 geom_col(fill = "#112446") +
 labs(x = "Continuidad de flujo", 
 y = "Porcentaje ATEs", title = "Continuidad de flujo de agua potable") +
 theme_minimal()

Agua Potable

Column

Tipo de ATE