library(readxl)
datos <- read_xlsx("IC2.xlsx", sheet = "1")
##estructura de los datos
str(datos)
## tibble [5,234 × 30] (S3: tbl_df/tbl/data.frame)
## $ Column1 : chr [1:5234] "0" "1" "2" "3" ...
## $ temporada : chr [1:5234] "2016-2017" "2016-2017" "2016-2017" "2016-2017" ...
## $ codreg : chr [1:5234] "3" "3" "3" "3" ...
## $ codprov : chr [1:5234] "33" "33" "33" "33" ...
## $ codcom : chr [1:5234] "3301" "3301" "3301" "3301" ...
## $ ambito : chr [1:5234] "Conaf" "Conaf" "Conaf" "Conaf" ...
## $ numero : chr [1:5234] "2.0" "3.0" "4.0" "5.0" ...
## $ nombre_inc: chr [1:5234] "CALLEJÓN MARTINEZ" "PERALES" "TORINO" "LA VERBENA" ...
## $ utm_este : chr [1:5234] "326931.0" "322031.0" "329713.0" "335543.0" ...
## $ utm_norte : chr [1:5234] "6838495.0" "6840235.0" "6836541.0" "6829112.0" ...
## $ inicio_c : chr [1:5234] "Camino secundario" "Camino secundario" "Orilla curso de agua" "Camino principal" ...
## $ combus_i : chr [1:5234] "Matorral" "Matorral" "Matorral" "Pastizal" ...
## $ causa_gene: chr [1:5234] "2.01" "2.01" "2.01" "1.02" ...
## $ causa_espe: chr [1:5234] "2.1.8." "2.1.8." "2.1.8." "1.2.4." ...
## $ pino_0010 : chr [1:5234] "0.0" "0.0" "0.0" "0.0" ...
## $ pino_11_17: chr [1:5234] "0.0" "0.0" "0.0" "0.0" ...
## $ pino_18 : chr [1:5234] "0.0" "0.0" "0.0" "0.0" ...
## $ eucalipto : chr [1:5234] "0.0" "0.0" "0.22" "0.0" ...
## $ otras_plan: chr [1:5234] "0.0" "0.0" "0.0" "0.0" ...
## $ total_plan: chr [1:5234] "0.0" "0.0" "0.22" "0.0" ...
## $ arbolado : chr [1:5234] "0.0" "0.0" "0.0" "0.0" ...
## $ matorral : chr [1:5234] "0.2" "0.1" "0.05" "0.0" ...
## $ pastizal : chr [1:5234] "0.0" "0.0" "0.0" "0.18" ...
## $ total_veg : chr [1:5234] "0.2" "0.1" "0.05" "0.18" ...
## $ agricola : chr [1:5234] "0.0" "0.0" "0.0" "0.0" ...
## $ desechos : chr [1:5234] "0.0" "0.0" "0.0" "0.0" ...
## $ total_otra: chr [1:5234] "0.0" "0.0" "0.0" "0.0" ...
## $ sup_t_a : chr [1:5234] "0.2" "0.1" "0.27" "0.18" ...
## $ long : chr [1:5234] "326931.0" "322031.0" "329713.0" "335543.0" ...
## $ lat : chr [1:5234] "6838495.0" "6840235.0" "6836541.0" "6829112.0" ...
##Extraer una variable nominal
adminterrenos <- datos$ambito
## eda variable nominal
TDFad <- table(adminterrenos)
TDFad
## adminterrenos
## Conaf Empresa
## 3583 1651
tabladmin <- as.data.frame(TDFad)
hi <- tabladmin$Freq/sum(tabladmin$Freq)
hi_porc <- hi*100
sum(hi_porc)
## [1] 100
tabladmin <- data.frame(tabladmin,hi_porc)
#distribucion de administradores
tabladmin
## adminterrenos Freq hi_porc
## 1 Conaf 3583 68.45625
## 2 Empresa 1651 31.54375
##GDF ni
####Local
barplot(tabladmin$Freq, main = "Grafica 1: DistribuciC3n de responsables del territorio ",
xlab = "",
ylab = "Cantidad",
names.arg = tabladmin$adminterrenos,
las=2, cex.names = 1, cex.axis = 0.5)
mtext("Entidad", side = 1, line = 4, cex = 1)
##General
barplot(tabladmin$Freq, main = "Grafica 1: Disribucion de responsables del territorio ",
xlab = "",
ylab = "Cantidad",
names.arg = tabladmin$adminterrenos,
las=2, cex.names = 1, cex.axis = 0.5, ylim = c(0, length(adminterrenos)))
mtext("Entidad", side = 1, line = 4, cex = 1)
##GDFhi#######
##general
barplot(tabladmin$hi_porc, main = "Grafica 2: Disribucion de porcentaje de responsables del territorio",
xlab = "",
ylab = "Porcentaje", col = "red",
names.arg = tabladmin$adminterrenos,
las=2, ylim = c(0,100), cex.names = 1, cex.axis = 0.8)
mtext("Entidad", side = 1, line = 4, cex = 1)
##Local
barplot(tabladmin$hi_porc, main = "Grafica 2: Disribucion de porcentaje de responsables del territorio",
xlab = "",
ylab = "Porcentaje", col = "red",
names.arg = tabladmin$adminterrenos,
las=2, cex.names = 1, cex.axis = 1)
##GDFcircular
porcentaje <- round(hi_porc)
etiqueta <- paste(porcentaje, "%", sep = " ")
colores <- topo.colors(length(hi_porc))
pie(tabladmin$hi_porc, labels = etiqueta, cex = 1, radius = 1, clockwise = TRUE, col = colores, init.angle = 0)
legend("topright", c("Conaf", "Empresas Forestales"), fill = colores, cex = 1)
