UNIVERSIDAD CENTRAL DEL ECUADOR
PROYECTO: FOCOS DE CALOR EN EL ECUADOR
AUTORES: GUERRERO MARIA GABRIELA,PUCHAICELA MONICA, ZURITA JOHANNA
FECHA: 14/05/2025
datos <- read.csv("maate_focosdecalor_bdd_2021diciembre.csv",
header = T, sep = ",", dec = ".")
#Estructura de los datos
str(datos)
## 'data.frame': 22476 obs. of 17 variables:
## $ MES_REPORT: int 11 11 8 6 5 6 11 9 3 3 ...
## $ DIA_REPORT: int 20 20 6 10 28 10 20 29 22 22 ...
## $ DPA_DESPRO: chr "ZAMORA CHINCHIPE" "ZAMORA CHINCHIPE" "ZAMORA CHINCHIPE" "ZAMORA CHINCHIPE" ...
## $ DPA_DESCAN: chr "CHINCHIPE" "CHINCHIPE" "CHINCHIPE" "CHINCHIPE" ...
## $ DPA_DESPAR: chr "CHITO" "CHITO" "PUCAPAMBA" "PUCAPAMBA" ...
## $ TXT_1 : chr "PARROQUIA RURAL" "PARROQUIA RURAL" "PARROQUIA RURAL" "PARROQUIA RURAL" ...
## $ LATITUDE : chr "-4,981720000000000" "-4,969160000000000" "-4,958520000000000" "-4,957820000000000" ...
## $ LONGITUDE : chr "-79,041280000000000" "-79,049490000000006" "-79,118430000000004" "-79,111859999999993" ...
## $ BRIGHTNESS: chr "354,759999999999990" "342,009999999999990" "331,860000000000010" "331,399999999999980" ...
## $ SCAN : chr "0,510000000000000" "0,510000000000000" "0,150000000000000" "0,540000000000000" ...
## $ TRACK : chr "0,490000000000000" "0,490000000000000" "0,380000000000000" "0,420000000000000" ...
## $ SATELLITE : chr "1" "1" "1" "1" ...
## $ CONFIDENCE: chr "n" "n" "n" "n" ...
## $ VERSION : chr "2.0NRT" "2.0NRT" "2.0NRT" "2.0NRT" ...
## $ BRIGHT_T31: chr "299,420000000000020" "298,149999999999980" "299,160000000000030" "296,800000000000010" ...
## $ FRP : chr "12,100000000000000" "6,870000000000000" "3,770000000000000" "5,500000000000000" ...
## $ DAYNIGHT : chr "D" "D" "D" "D" ...
#Tabla Distribucion de Frecuencia
TDF_DAYNIGHT <- as.data.frame(table(datos$DAYNIGHT))
colnames(TDF_DAYNIGHT) <- c("DAYNIGHT", "ni")
TDF_DAYNIGHT$hi <- round((TDF_DAYNIGHT$ni / sum(TDF_DAYNIGHT$ni)) * 100, 2)
sum(TDF_DAYNIGHT$ni)
## [1] 22476
sum(TDF_DAYNIGHT$hi)
## [1] 100
print(TDF_DAYNIGHT)
## DAYNIGHT ni hi
## 1 D 18292 81.38
## 2 N 4184 18.62
str(TDF_DAYNIGHT)
## 'data.frame': 2 obs. of 3 variables:
## $ DAYNIGHT: Factor w/ 2 levels "D","N": 1 2
## $ ni : int 18292 4184
## $ hi : num 81.4 18.6
# Ordenar por nivel de gravedad
orden <- c("D", "N")
TDF_DAYNIGHT <- TDF_DAYNIGHT[order(factor(TDF_DAYNIGHT$DAYNIGHT, levels = orden)), ]
# Renombrar columnas
colnames(TDF_DAYNIGHT) <- c("DAYNIGHT","ni","hi (%)")
# Cargar librerías necesarias
library(knitr)
library(kableExtra)
# Mostrar la tabla con estilo
kable(TDF_DAYNIGHT, align = 'c',
caption = "Tabla de Distribución de Frecuencias de Incendio diurno o nocturno") %>%
kable_styling(full_width = FALSE, position = "center",
bootstrap_options = c("striped", "hover", "condensed"))
| DAYNIGHT | ni | hi (%) |
|---|---|---|
| D | 18292 | 81.38 |
| N | 4184 | 18.62 |
#Graficas
# Diagrama de barrras local
options(scipen = 999)
barplot(TDF_DAYNIGHT$ni,
main="Gráfica N°8.1: Distribución de cantidad de Incendio Diurno o Nocturno",
xlab = "Incendio Diurno o Nocturno",
ylab = "Cantidad",
col = "red",
cex.axis = 0.5,
ylim = c(0,60000),
las=1,
names.arg=TDF_DAYNIGHT$DAYNIGHT)
barplot(TDF_DAYNIGHT$hi,
main="Gráfica N°8.2: Distribución porcentual de Incendios Diurno o Nocturno",
xlab = "Incendio Diurno o Nocturno",
ylab = "Porcentaje (%)",
col = "pink",
ylim = c(0,80),
las=1,
names.arg=TDF_DAYNIGHT$DAYNIGHT)
# Diagrama de barrras global
barplot(TDF_DAYNIGHT$ni,
main="Gráfica N°8.3: Distribución de cantidad de Incendios Diurno o Nocturno",
ylab = "Cantidad",
col = "brown",
ylim = c(0,sum(TDF_DAYNIGHT$ni)),
las=1,
cex.axis = 0.7,
las=1,
names.arg = TDF_DAYNIGHT$DAYNIGHT)
barplot(TDF_DAYNIGHT$hi,
main="Gráfica N°8.4: Distribución porcentual de Incendios Diurno o Nocturno",
ylab = "Porcentaje (%)",
col = "yellow",
ylim = c(0,100),
names.arg=TDF_DAYNIGHT$DAYNIGHT)
# Diagrma circular
pie(TDF_DAYNIGHT$hi,
main = "Gráfica N°8.5: Distribución porcentual de Incendios Diurno o Noctuno",
radius = 1,
labels = paste0(TDF_DAYNIGHT$hi,"%"),
col = colores <- c(heat.colors(3)),
cex=1,
cex.main=1.2)
legend("topright",
legend = TDF_DAYNIGHT$DAYNIGHT,
fill = colores <- c(heat.colors(3)),
cex = 0.95,
title = "Leyenda")
# Indicadores estadísticos
# MODA
max_frecuencia <- max(TDF_DAYNIGHT$ni)
moda <- TDF_DAYNIGHT$DAYNIGHT[TDF_DAYNIGHT$ni==max_frecuencia]
print(moda)
## [1] D
## Levels: D N