MAPAS CAFÉ ANTIOQUIA

library(tidyverse)
library(dplyr)
library(ggplot2)
library(sf)

eva_antioquia <- read_csv(file = "EVA.ANTIOQUIA.csv")

Rows: 18759 Columns: 17
-- Column specification -------------------------------
Delimiter: ","
chr (11): COD.DEP, DEPA, MUNI, GCULTI, SCULTI, CULT...
dbl  (6): COD.MUN, ANO, ASEMB, ACOSE, PRODUC, RENDI

i Use `spec()` to retrieve the full column specification for this data.
i Specify the column types or set `show_col_types = FALSE` to quiet this message.

mun_antioquia <- sf::st_read("C:/Users/hinca/Documents/(A) Hinca/UNAL/Semestre 5/Geomática/05_ANTIOQUIA/ADMINISTRATIVO/MGN_MPIO_POLITICO.shp")

Reading layer `MGN_MPIO_POLITICO' from data source 
  `C:\Users\hinca\Documents\(A) Hinca\UNAL\Semestre 5\Geomática\05_ANTIOQUIA\ADMINISTRATIVO\MGN_MPIO_POLITICO.shp' 
  using driver `ESRI Shapefile'
Simple feature collection with 125 features and 9 fields
Geometry type: POLYGON
Dimension:     XY
Bounding box:  xmin: -77.12783 ymin: 5.418558 xmax: -73.88128 ymax: 8.873974
Geodetic CRS:  WGS 84

mun_antioquia$COD.MUN <-  as.double(mun_antioquia$MPIO_CCDGO)

aguacate_antioquia <- eva_antioquia %>%  filter(CULTI == "AGUACATE")  %>%  dplyr::select(MUNI, COD.MUN, ANO, PERIO, PRODUC, RENDI, ASEMB) 

Warning: One or more parsing issues, see `problems()` for details

aguacate_antioquia%>% replace(is.na(.), 0) -> aguacate_antioquia2

aguacate_antioquia %>% group_by(MUNI, COD.MUN, ANO,ASEMB ) %>%
   summarize(PRODUC=sum(PRODUC)) -> aguacate_antioquia2

`summarise()` has grouped output by 'MUNI', 'COD.MUN', 'ANO'. You can override using the `.groups` argument.

aguacate_antioquia2 %>% 
  group_by(COD.MUN) %>% 
  gather("PRODUC", key = variable, value = number)   %>% 
  unite(combi, variable, ANO) %>%
  pivot_wider(names_from = combi, values_from = number, values_fill = 0) ->                                                                    aguacate_antioquia3

mun_antioquia_aguacate = left_join(mun_antioquia, aguacate_antioquia3, by="COD.MUN")

library(RColorBrewer)
library(leaflet)

bins <- c(0, 200, 400, 800, 1800, 3000, 8000, 12000, 54000 )
pal <- colorBin("YlOrRd", domain = mun_antioquia_aguacate$PRODUC_2018, bins = bins)

  mapa <- leaflet(data = mun_antioquia_aguacate) %>%
  addTiles() %>%
  addPolygons(label = ~PRODUC_2018,
              popup = ~MPIO_CNMBR,
              fillColor = ~pal(PRODUC_2018),
              color = "#444444",
              weight = 1,
              smoothFactor = 0.5,
              opacity = 1.0,
              fillOpacity = 0.5,
              highlightOptions = highlightOptions(color = "white", weight = 2, bringToFront = TRUE)
              ) %>%
  addProviderTiles(providers$OpenStreetMap) %>%
  addLegend("bottomright", pal = pal, values = ~PRODUC_2018,
    title = "Producción de Aguacate en Antioquia [Ton] (2018)",
    opacity = 1
  )

mapa

aguacate_antioquia2 %>% 
  group_by(COD.MUN) %>% 
  gather("ASEMB", key = variable, value = number)   %>% 
  unite(combi, variable, ANO) %>%
  pivot_wider(names_from = combi, values_from = number, values_fill = 0) ->                                                                    aguacate_antioquia4

mun_antioquia_aguacateas = left_join(mun_antioquia, aguacate_antioquia4, by="COD.MUN")

bins <- c(0, 250, 500, 750, 1000, 1500, 2000, 2500)
pal <- colorBin("YlOrRd", domain = mun_antioquia_aguacateas$ASEMB_2018, bins = bins)

  mapa <- leaflet(data = mun_antioquia_aguacateas) %>%
  addTiles() %>%
  addPolygons(label = ~ASEMB_2018,
              popup = ~MPIO_CNMBR,
              fillColor = ~pal(ASEMB_2018),
              color = "#444444",
              weight = 1,
              smoothFactor = 0.5,
              opacity = 1.0,
              fillOpacity = 0.5,
              highlightOptions = highlightOptions(color = "white", weight = 2, bringToFront = TRUE)
              ) %>%
  addProviderTiles(providers$OpenStreetMap) %>%
  addLegend("bottomright", pal = pal, values = ~ASEMB_2018,
    title = "Área de aguacate sembrada en Antioquia [Ha] (2018)",
    opacity = 1
  )

mapa