###ESTABLECIENDO LAS LIBRERIAS PARA MAPAS 

library(sf)

## Warning: package 'sf' was built under R version 4.0.3

## Linking to GEOS 3.8.0, GDAL 3.0.4, PROJ 6.3.1

library(purrr)

## Warning: package 'purrr' was built under R version 4.0.3

library(tidyverse)

## Warning: package 'tidyverse' was built under R version 4.0.3

## -- Attaching packages --------------------------------------------------- tidyverse 1.3.0 --

## v ggplot2 3.3.3     v dplyr   1.0.4
## v tibble  3.0.3     v stringr 1.4.0
## v tidyr   1.1.1     v forcats 0.5.0
## v readr   1.3.1

## Warning: package 'ggplot2' was built under R version 4.0.3

## Warning: package 'dplyr' was built under R version 4.0.3

## -- Conflicts ------------------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag()    masks stats::lag()

library(ggplot2)
library(ggrepel)

## Warning: package 'ggrepel' was built under R version 4.0.3

library(readxl)

##Estableciendo y cargando la data 
##darse cuenta que las comillas van solo al inicio y al final y los "/" van hacia la derecha
##ver que es un shapefile
peru_d <- st_read ("D:/PRACTICANDO R STUDIO/DATA PARA PRACTICAR/Data para mapa/DEPARTAMENTOS.shp")

## Reading layer `DEPARTAMENTOS' from data source `D:\PRACTICANDO R STUDIO\DATA PARA PRACTICAR\Data para mapa\DEPARTAMENTOS.shp' using driver `ESRI Shapefile'
## Simple feature collection with 25 features and 4 fields
## geometry type:  MULTIPOLYGON
## dimension:      XY
## bbox:           xmin: -81.32823 ymin: -18.35093 xmax: -68.65228 ymax: -0.03860597
## geographic CRS: WGS 84

peru_d

## Simple feature collection with 25 features and 4 fields
## geometry type:  MULTIPOLYGON
## dimension:      XY
## bbox:           xmin: -81.32823 ymin: -18.35093 xmax: -68.65228 ymax: -0.03860597
## geographic CRS: WGS 84
## First 10 features:
##    IDDPTO   DEPARTAMEN      CAPITAL FUENTE                       geometry
## 1      01     AMAZONAS  CHACHAPOYAS   INEI MULTIPOLYGON (((-77.81211 -...
## 2      02       ANCASH       HUARAZ   INEI MULTIPOLYGON (((-77.64692 -...
## 3      03     APURIMAC      ABANCAY   INEI MULTIPOLYGON (((-73.74632 -...
## 4      04     AREQUIPA     AREQUIPA   INEI MULTIPOLYGON (((-71.98109 -...
## 5      05     AYACUCHO     AYACUCHO   INEI MULTIPOLYGON (((-74.34843 -...
## 6      06    CAJAMARCA    CAJAMARCA   INEI MULTIPOLYGON (((-78.70034 -...
## 7      07       CALLAO       CALLAO   INEI MULTIPOLYGON (((-77.13521 -...
## 8      08        CUSCO        CUSCO   INEI MULTIPOLYGON (((-72.9728 -1...
## 9      09 HUANCAVELICA HUANCAVELICA   INEI MULTIPOLYGON (((-74.57118 -...
## 10     10      HUANUCO      HUANUCO   INEI MULTIPOLYGON (((-76.00486 -...

names(peru_d)

## [1] "IDDPTO"     "DEPARTAMEN" "CAPITAL"    "FUENTE"     "geometry"

##Primer mapa: solo muestra los límites departamentales 
ggplot(data = peru_d) +
  geom_sf() ##geoms_sf () ya indica que una variable de geometría y eso hay en nuestra data 

##Graficar solo un departamento: graficaremos Arequipa 

ggplot(data = peru_d %>%   ##de la data peru_d %>%
         filter(DEPARTAMEN == "LAMBAYEQUE")) +   #filtrame el departamento de Lambayeque
  geom_sf()

#ggplot(data = peru_d %>%
         #filter(IDDPTO == "06")) +
         #geom_sf()

###SEGUNDA DATA PARA UNIR 

data <- read_excel("D:/PRACTICANDO R STUDIO/DATA PARA PRACTICAR/Ejemplo de departamentos para mapa.xlsx")

##Creando un data frame con un elemento en común 
##MERGE UNE LAS DATAS, by.x es la variable de la primera data en común y by.y es de la segunda data 
mapa_final <- merge(peru_d, data, by.x = "DEPARTAMEN", by.y = "Departamentos", all.x = TRUE) 

ggplot(mapa_final) +
  geom_sf(aes(fill = Frecuencia ))+
  labs(title = "TITULO",
       caption = "Fuente: Enaho (2018)
       Elaboración propia",
       x="Longitud",
       y="Latitud")+
  scale_fill_continuous(guide_legend(title = "TITULO DE LA LEYENDA"))

ggplot(mapa_final) +
  geom_sf(aes(fill = Frecuencia ))+
  labs(title = "TITULO",
       caption = "Fuente: Enaho (2018)
       Elaboración propia",
       x="Longitud",
       y="Latitud")+
  scale_fill_continuous(guide_legend(title = "TITULO DE LA LEYENDA")) -> ejem1
library(plotly)

## Warning: package 'plotly' was built under R version 4.0.3

## 
## Attaching package: 'plotly'

## The following object is masked from 'package:ggplot2':
## 
##     last_plot

## The following object is masked from 'package:stats':
## 
##     filter

## The following object is masked from 'package:graphics':
## 
##     layout

ggplotly(ejem1)