Solar_Aptitude_Class

Escritura

setwd("/cloud/project")

Datos <- read.csv("DataSet_.csv", sep = ";", fileEncoding = "latin1")

install.packages("dplyr")

## Installing package into '/cloud/lib/x86_64-pc-linux-gnu-library/4.5'
## (as 'lib' is unspecified)

library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

install.packages("ggplot2")

## Installing package into '/cloud/lib/x86_64-pc-linux-gnu-library/4.5'
## (as 'lib' is unspecified)

library(ggplot2)

Tabla Base

Solar <- Datos$solar_aptittude_class
TDF_solar <- table(Solar)

tabla_solar <- as.data.frame(TDF_solar)
hi <- tabla_solar$Freq/sum(tabla_solar$Freq)
hi_porc <- hi*100

tabla_SOLAR <- data.frame(tabla_solar, hi_porc)

colnames(tabla_SOLAR)[1] <- "Aptitud"

Agrupación

tabla_resumen <- tabla_SOLAR %>%
  mutate(grupo = case_when(
    grepl("Alta", Aptitud, ignore.case = TRUE) ~ "Alta",
    grepl("Media", Aptitud, ignore.case = TRUE) ~ "Media",
    grepl("Baja", Aptitud, ignore.case = TRUE) ~ "Baja",
    TRUE ~ "Otros"
  )) %>%
  group_by(grupo) %>%
  summarise(
    Frecuencia = sum(Freq),
    Porcentaje = sum(hi_porc)
  ) %>%
  arrange(desc(Frecuencia))

colnames(tabla_resumen) <- c("Aptitud","ni","hi (%)")
tabla_resumen

## # A tibble: 4 × 3
##   Aptitud    ni `hi (%)`
##   <chr>   <int>    <dbl>
## 1 Alta     4440  62.2   
## 2 Media    2641  37.0   
## 3 Baja       60   0.840 
## 4 Otros       1   0.0140

Totales

totales <- c(
  Aptitud = "TOTAL",
  ni = sum(tabla_resumen$ni),
  hi = sum(tabla_resumen$`hi (%)`)
)

tabla_Solar_Final <- rbind(tabla_resumen, totales)
tabla_Solar_Final

## # A tibble: 5 × 3
##   Aptitud ni    `hi (%)`          
##   <chr>   <chr> <chr>             
## 1 Alta    4440  62.1674600952114  
## 2 Media   2641  36.9784374124895  
## 3 Baja    60    0.840100812097452 
## 4 Otros   1     0.0140016802016242
## 5 TOTAL   7142  100

GRÁFICOS

Gráfico 1 – Frecuencia local

par(mar = c(8, 4, 4, 2))
barplot(tabla_resumen$ni,main="Gráfica N°1: Distribución de la Aptitud Solar",
        ylab = "Cantidad",
        col = "skyblue",
        names.arg=tabla_resumen$Aptitud,
        cex.names = 0.8, las = 2)
mtext("Categoría de Aptitud", side = 1, line = 6)

Gráfico 2 – Frecuencia global

barplot(tabla_resumen$ni,main="Gráfica N°2: Distribución de Aptitud Solar (Global)",
        ylab = "Cantidad",
        col = "skyblue",
        ylim = c(0,8000),
        names.arg=tabla_resumen$Aptitud,
        cex.names = 0.8, las = 2)
mtext("Categoría de Aptitud", side = 1, line = 6)

Gráfico 3 – Porcentaje local

barplot(tabla_resumen$`hi (%)`,main="Gráfica N°3: Distribución porcentual de Aptitud Solar",
        ylab = "Porcentaje %",
        col = "skyblue",
        names.arg=tabla_resumen$Aptitud,
        cex.names = 0.8, las = 2)
mtext("Categoría de Aptitud", side = 1, line = 6)

Gráfico 4 – Porcentaje global

barplot(tabla_resumen$`hi (%)`,main="Gráfica N°4: Distribución porcentual global",
        ylab = "Porcentaje %",
        col = "skyblue",
        ylim = c(0,100),
        names.arg=tabla_resumen$Aptitud,
        cex.names = 0.8, las = 2)
mtext("Categoría de Aptitud", side = 1, line = 6)

Gráfico 5 – Diagrama Circular

pie(tabla_resumen$`hi (%)`,
    main = "Gráfica N°5: Distribución porcentual de Aptitud Solar",
    radius = 0.9,
    labels = paste0(round(tabla_resumen$`hi (%)`,2),"%"),
    col = colores <- c("red", "orange", "yellow"),
    cex = 0.6)

legend(x = 1.3, y = 0.9,
       legend = tabla_resumen$Aptitud,
       fill = colores,
       cex = 0.6,
       title = "Aptitud")

par(xpd = TRUE)

Tabla de Conlusiones

install.packages("knitr")

## Installing package into '/cloud/lib/x86_64-pc-linux-gnu-library/4.5'
## (as 'lib' is unspecified)

library(knitr)

tabla_indicadores <- data.frame(
  "Variable" = "Aptitud Solar",
  "Rango" = "Alta - Media - Baja",
  "X" = "-",
  "Me" = "-",
  "Mo" = "Alta",
  "V" = "-",
  "Sd" = "-",
  "Cv" = "-",
  "As" = "-",
  "K" = "-",
  "Valores Atipicos" = "-"
)

kable(tabla_indicadores, align = 'c', caption = "Conclusiones de la variable Aptitud Solar")

Conclusiones de la variable Aptitud Solar

Variable	Rango	X	Me	Mo	V	Sd	Cv	As	K	Valores.Atipicos
Aptitud Solar	Alta - Media - Baja	-	-	Alta	-	-	-	-	-	-