Análisis Exploratorio de Datos Mina O Nivel

#Librerias y Carga de datos

if (!require("e1071")) install.packages("e1071", dependencies = TRUE)

## Loading required package: e1071

library(e1071)

setwd("/cloud/project")
compCristina<-read.csv("O_NIVEL_Composito_Cristina.txt",header=T, sep = "",dec=".")
compJane<-read.csv("O_NIVEL_Composito_Jane.txt",header=T, sep= "",dec=".")
compX<-read.csv("O_NIVEL_Composito_X.txt",header=T, sep= "",dec=".")

Extraer las variables de interés

OroCristina<- compCristina$Au.ppm.
OroCristina<- na.omit(OroCristina)
OroJane<- compJane$Au.ppm.
OroJane<- na.omit(OroJane)
OroX<- compX$Au.ppm.
OroX<- na.omit(OroX)

Crear los histogramas

histCristina<- hist(OroCristina, 
                   main = "Histograma de leyes de oro del compósito en la Veta Cristina",
                   xlab = "Au (ppm)",  
                   ylab = "Frecuencia",               
                   col = "skyblue",                  
                   border = "black")
text(x = histCristina$mids, 
     y = histCristina$counts, 
     labels = histCristina$counts, 
     pos = 3,        # Posición del texto: arriba
     cex = 0.8,      # Tamaño del texto
     col = "black")  # Color del texto

histJane<- hist(OroJane, 
                    main = "Histograma de leyes de oro del compósito en la Veta Jane",
                    xlab = "Au (ppm)",  
                    ylab = "Frecuencia",               
                    col = "skyblue",                  
                    border = "black")
text(x = histJane$mids, 
     y = histJane$counts, 
     labels = histJane$counts, 
     pos = 3,        
     cex = 0.8,      
     col = "black")  

histX<- hist(OroX, 
                    main = "Histograma de leyes de oro del compósito en la Veta X",
                    xlab = "Au (ppm)",  
                    ylab = "Frecuencia",               
                    col = "skyblue",                  
                    border = "black")
text(x = histX$mids, 
     y = histX$counts, 
     labels = histX$counts, 
     pos = 3,        
     cex = 0.8,      
     col = "black")  

# Indicadores

cat("<b>Veta Cristina</b>")

## <b>Veta Cristina</b>

mediaCristina <- mean(OroCristina)
mediaCristina

## [1] 3.276414

medianaCristina <- median(OroCristina)
medianaCristina

## [1] 1.63

modaCristina <- as.numeric(names(which.max(table(OroCristina))))
modaCristina

## [1] 0.33

minimoCristina <- min(OroCristina)
minimoCristina

## [1] 0.07

maximoCristina <- max(OroCristina)
maximoCristina

## [1] 28.21

Q1Cristina <- quantile(OroCristina, 0.25)
Q1Cristina

##  25% 
## 0.74

Q3Cristina <- quantile(OroCristina, 0.75)
Q3Cristina

##  75% 
## 2.66

varianzaCristina <- var(OroCristina)
varianzaCristina

## [1] 34.20226

desvCristina <- sd(OroCristina)
desvCristina

## [1] 5.84827

coef_varCristina <- (sd(OroCristina) / mean(OroCristina)) * 100
coef_varCristina

## [1] 178.4961

sesgoCristina <- skewness(OroCristina)
sesgoCristina

## [1] 3.332659

curtosisCristina <- kurtosis(OroCristina)
curtosisCristina

## [1] 10.21265

mediaJane <- mean(OroJane)
mediaJane

## [1] 13.1148

medianaJane <- median(OroJane)
medianaJane

## [1] 6.58

modaJane <- as.numeric(names(which.max(table(OroJane))))
modaJane

## [1] 0.58

minimoJane <- min(OroJane)
minimoJane

## [1] 0.34

maximoJane <- max(OroJane)
maximoJane

## [1] 337.2

Q1Jane <- quantile(OroJane, 0.25)
Q1Jane

##  25% 
## 3.24

Q3Jane <- quantile(OroJane, 0.75)
Q3Jane

##    75% 
## 11.355

varianzaJane <- var(OroJane)
varianzaJane

## [1] 745.4867

desvJane <- sd(OroJane)
desvJane

## [1] 27.3036

coef_varJane <- (sd(OroJane) / mean(OroJane)) * 100
coef_varJane

## [1] 208.1892

sesgoJane <- skewness(OroJane)
sesgoJane

## [1] 8.404448

curtosisJane <- kurtosis(OroJane)
curtosisJane

## [1] 89.28647

mediaX <- mean(OroX)
mediaX

## [1] 2.219583

medianaX <- median(OroX)
medianaX

## [1] 2.2

modaX <- as.numeric(names(which.max(table(OroX))))
modaX

## [1] 1.19

minimoX <- min(OroX)
minimoX

## [1] 0.95

maximoX <- max(OroX)
maximoX

## [1] 3.21

Q1X <- quantile(OroX, 0.25)
Q1X

##   25% 
## 1.675

Q3X <- quantile(OroX, 0.75)
Q3X

##  75% 
## 2.86

varianzaX <- var(OroX)
varianzaX

## [1] 0.5184998

desvX <- sd(OroX)
desvX

## [1] 0.7200693

coef_varX <- (sd(OroX) / mean(OroX)) * 100
coef_varX

## [1] 32.44164

sesgoX <- skewness(OroX)
sesgoX

## [1] -0.1749864

curtosisX <- kurtosis(OroX)
curtosisX

## [1] -1.430328

Boxplot

CajaOroCristina <- boxplot(OroCristina, horizontal =  T,
        main = "Boxplot leyes de muestras del compósito en la Veta Cristina ",  
        xlab = "Valor de ley",     
        ylab = "Muestras",                 
        col = "skyblue",             
        border = "black")           

CajaOroJane <- boxplot(OroJane, horizontal =  T,
                           main = "Boxplot leyes de muestras del compósito en la Veta Jane",  
                           xlab = "Valor de ley",     
                           ylab = "Muestras",                 
                           col = "skyblue",             
                           border = "black")   

CajaOroX <- boxplot(OroX, horizontal =  T,
                       main = "Boxplot leyes de muestras del compósito en la Veta X",  
                       xlab = "Valor de ley",     
                       ylab = "Muestras",                 
                       col = "skyblue",             
                       border = "black")