CARGA DE DATOS
#Carga de datos
setwd("~/UNI/ESTADISTICA")
datos <- read.csv("Depositos_Sulfuro.csv",sep = ";",dec = ".",header = T)
datos2 <- read.csv2("Clasificacion depage.csv",sep = ";",dec = ".",header = T)
CARGA DE LIBRERIAS
#Carga de librerias
library(gt)
library(dplyr)
library(knitr)
TABLA DE DISTRIBUCION DE FRECUENCIA POR EDAD GEOLOGICA
# Extraer variable
edad <- datos$depage
# Frecuencia absoluta
ni <- table(edad)
# Frecuencia relativa en %
hi <- prop.table(ni) * 100
# Tabla principal
tabla_final <- data.frame(
edad = names(ni),
ni = as.numeric(ni),
hi = as.numeric(hi)
)
Fila total de las sumas de ni y hi
# Fila TOTAL
fila_total <- data.frame(
edad = "TOTAL",
ni = sum(tabla_final$ni),
hi = sum(tabla_final$hi)
)
# Unir
tabla_final_p <- rbind(tabla_final, fila_total)
tabla_final_p
## edad ni hi
## 1 Upper Devonian (378.3\xb139 - 364\xb115) 1 0.09174312
## 2 Upper Triassic (217\xb128, Re-Os) 1 0.09174312
## 3 Miocene-Pliocene (14\xb12 - 2.2) 1 0.09174312
## 4 3 0.27522936
## 5 Archean 114 10.45871560
## 6 Archean-Mid Proterozoic 1 0.09174312
## 7 Archean-Proterozoic 1 0.09174312
## 8 Cambrian 31 2.84403670
## 9 Cambrian-Ordovician 13 1.19266055
## 10 Cambrian-Silurian 3 0.27522936
## 11 Cambrian(?) 2 0.18348624
## 12 Carboniferous 35 3.21100917
## 13 Cretaceous 27 2.47706422
## 14 Cretaceous-Eocene 1 0.09174312
## 15 Cretaceous or Paleocene-Eocene 1 0.09174312
## 16 Devonian 27 2.47706422
## 17 Devonian-Carboniferous 6 0.55045872
## 18 Devonian-Mississippian 7 0.64220183
## 19 Devonian-Pennsylvanian 1 0.09174312
## 20 Devonian-Permian 1 0.09174312
## 21 Early- Middle Devonian (Emsian-Eifelian) 1 0.09174312
## 22 Early-Middle Devonian 2 0.18348624
## 23 Early-Middle Devonian (Emsian-Eifelian) 1 0.09174312
## 24 Early-Middle Devonian(Emsian-Eifelian) 1 0.09174312
## 25 Early Cambrian 9 0.82568807
## 26 Early Carboniferous 1 0.09174312
## 27 Early Carboniferous (Visean-Namurian) 4 0.36697248
## 28 Early Carboniferous (Visean-Namurian?) 1 0.09174312
## 29 Early Cretaceous 6 0.55045872
## 30 Early Devonian 5 0.45871560
## 31 Early Devonian (Emsian) 8 0.73394495
## 32 Early Ordovician 1 0.09174312
## 33 Early Proterozoic 1 0.09174312
## 34 Early Silurian 1 0.09174312
## 35 Early Silurian (Llandovery) 2 0.18348624
## 36 Early Silurian(Llandovery) 1 0.09174312
## 37 Early to Middle Cretaceous 1 0.09174312
## 38 Eocene 8 0.73394495
## 39 Eocene-Middle Miocene 1 0.09174312
## 40 Eocene-Pliocene 8 0.73394495
## 41 Jurassic 22 2.01834862
## 42 Jurassic-Early Cretaceous 1 0.09174312
## 43 Jurassic-Lower Cretaceous 4 0.36697248
## 44 Jurassic or Cretaceous 1 0.09174312
## 45 Late-Middle Triassic 1 0.09174312
## 46 Late Ordovician 1 0.09174312
## 47 Late Archean 27 2.47706422
## 48 Late Cambrian-Early Ordovician 1 0.09174312
## 49 Late Carboniferous 2 0.18348624
## 50 Late Cretaceous 1 0.09174312
## 51 Late Cretaceous (Turonian) 4 0.36697248
## 52 Late Devonian 3 0.27522936
## 53 Late Devonian (Frasnian) 3 0.27522936
## 54 Late Jurassic 1 0.09174312
## 55 Late Jurassic-Lower Cretaceous 4 0.36697248
## 56 Late Ordovician 6 0.55045872
## 57 Late Permian 2 0.18348624
## 58 Late Permian-Early Triassic 1 0.09174312
## 59 Late Precambrian 1 0.09174312
## 60 Late Proterozoic 1 0.09174312
## 61 Late Silurian 1 0.09174312
## 62 Late Silurian-Early Devonian 2 0.18348624
## 63 Late Silurian-Lower Devonian 1 0.09174312
## 64 Late Triassic 1 0.09174312
## 65 Late Triassic-Late Jurassic 1 0.09174312
## 66 Lower-Middle Carboniferous 1 0.09174312
## 67 Lower-Middle Devonian (Emsian-early Eifelian) 1 0.09174312
## 68 Lower-Middle Devonian (Emsian-Eifelian) 2 0.18348624
## 69 Lower-Middle Jurassic 1 0.09174312
## 70 Lower Cretaceous 14 1.28440367
## 71 Lower Devonian 1 0.09174312
## 72 Lower Devonian (407, U-Pb) 1 0.09174312
## 73 Lower Devonian (Emsian) 2 0.18348624
## 74 Lower Devonian (late Emsian) 2 0.18348624
## 75 Lower Jurassic 2 0.18348624
## 76 Lower or mid-Cretaceous 1 0.09174312
## 77 Lower Ordovician 7 0.64220183
## 78 Lower Paleocene-Upper Eocene 2 0.18348624
## 79 Lower Permian 1 0.09174312
## 80 Lower Permian-Late Carboniferous (292-283) 1 0.09174312
## 81 Lower Proterozoic 16 1.46788991
## 82 Lower Tertiary 5 0.45871560
## 83 Meso-Neoproterozoic 1 0.09174312
## 84 Mesoproterozoic 3 0.27522936
## 85 Mesoproterozoic (1216-1026, Sm-Nd) 1 0.09174312
## 86 Mesoproterozoic? (Riphean?) 1 0.09174312
## 87 Mesozoic 2 0.18348624
## 88 Mid Cretaceous 1 0.09174312
## 89 Middle-Late Devonian (Givetian-Frasnian) 1 0.09174312
## 90 Middle-Upper Devonian 3 0.27522936
## 91 Middle-Upper Devonian (Givetian-Frasnian) 6 0.55045872
## 92 Middle-Upper Jurassic 1 0.09174312
## 93 Middle Cambrian 5 0.45871560
## 94 Middle Devonian 23 2.11009174
## 95 Middle Devonian (Eifelian-Givetian) 12 1.10091743
## 96 Middle Devonian (Eifelian to early Givetian) 1 0.09174312
## 97 Middle Devonian (Eifelian) 13 1.19266055
## 98 Middle Devonian (Emsian-Eifelian) 1 0.09174312
## 99 Middle Devonian (Givetian) 4 0.36697248
## 100 Middle Devonian (Late Givetian) 1 0.09174312
## 101 Middle Devonian (lower Givetian) 1 0.09174312
## 102 Middle Devonian(Givetian) 2 0.18348624
## 103 Middle Jurassic (late Bajocian) 3 0.27522936
## 104 Middle Miocene 1 0.09174312
## 105 Middle Ordovician 2 0.18348624
## 106 Middle Proterozoic 2 0.18348624
## 107 Middle Proterozoic? 1 0.09174312
## 108 Miocene 39 3.57798165
## 109 Miocene? 1 0.09174312
## 110 Mississippian 4 0.36697248
## 111 Neoarchean-Paleoproterozoic (2.8-2.6 Ga) 1 0.09174312
## 112 Neoproterozoic 3 0.27522936
## 113 Neoproterozoic (976.4-802.3) 1 0.09174312
## 114 Neoproterozoic (Early Paleozoic?) 1 0.09174312
## 115 Neoproterozoic, Sinian 1 0.09174312
## 116 Oligocene 1 0.09174312
## 117 Ordovician 108 9.90825688
## 118 Ordovician-Silurian 5 0.45871560
## 119 Ordovician to Precambrian 1 0.09174312
## 120 Orodivician 1 0.09174312
## 121 Paleoproterozoic 2 0.18348624
## 122 Paleoproterozoic (1700-2000) 2 0.18348624
## 123 Paleozoic 29 2.66055046
## 124 Paleozoic-Mid Mesozoic 1 0.09174312
## 125 Paleozoic-Triassic 1 0.09174312
## 126 Pennsylvanian-Permian 1 0.09174312
## 127 Permian 9 0.82568807
## 128 Permian-Cretaceous 1 0.09174312
## 129 Permian-Triassic 2 0.18348624
## 130 Pliocene 1 0.09174312
## 131 pre-Eocene 1 0.09174312
## 132 Pre-Tertiary 1 0.09174312
## 133 Precambrian 2 0.18348624
## 134 Precambrian-Late Cambrian 2 0.18348624
## 135 Precambrian Z (570-800 Ma) 1 0.09174312
## 136 Proterozoic 154 14.12844037
## 137 Proterozoic or Ordovician 2 0.18348624
## 138 Silurian 39 3.57798165
## 139 Silurian-Devonian 2 0.18348624
## 140 Silurian to Carboniferous 1 0.09174312
## 141 Tertiary 1 0.09174312
## 142 Triassic 5 0.45871560
## 143 Triassic-Jurassic 1 0.09174312
## 144 Triassic or Jurassic 1 0.09174312
## 145 Upper-Devonian-Lower Carboniferous 1 0.09174312
## 146 Upper Carboniferous 1 0.09174312
## 147 Upper Cretaceous 29 2.66055046
## 148 Upper Devonian 2 0.18348624
## 149 Upper Devonian- Lower Carboniferous 1 0.09174312
## 150 Upper Devonian-Lower Carboniferou 2 0.18348624
## 151 Upper Devonian-Lower Carboniferous 27 2.47706422
## 152 Upper Devonian (Famennian) 2 0.18348624
## 153 Upper Devonian (Frasnian) 1 0.09174312
## 154 Upper Jurassic 1 0.09174312
## 155 Upper Jurassic-Lower Cretaceous 4 0.36697248
## 156 Upper Proterozoic 2 0.18348624
## 157 Upper Silurian 1 0.09174312
## 158 Upper Triassic 1 0.09174312
## 159 Upper Devonian (373\xb115) 1 0.09174312
## 160 TOTAL 1090 100.00000000
Debido a que la tabla presenta numerosos registros de edades geológicas, se decidió agruparlos por era geológica, pasando de una variable cualitativa nominal a una variable cualitativa ordinal
TABLA DE DISTRIBUCION DE FRECUENCIA AGRUPADA
# Extraer variable
Era <- as.character(datos2$Classificacion)
# Eliminar NA
Era <- Era[!is.na(Era)]
# Quitar tildes
Era <- chartr(
"áéíóúÁÉÍÓÚ",
"aeiouAEIOU",
Era
)
# Normalizar nombres
Era <- gsub("precámbico", "Precambrico", Era, ignore.case = TRUE)
Era <- gsub("precambico", "Precambrico", Era, ignore.case = TRUE)
# Definir variable ordinal
Era <- factor(
Era,
levels = c("Precambrico", "Paleozoico", "Mesozoico", "Cenozoico"),
ordered = TRUE
)
# Frecuencia absoluta
ni <- table(Era)
# Frecuencia relativa porcentual
hi <- round(prop.table(ni) * 100, 2)
# Crear tabla
tabla_era <- data.frame(
Era = names(ni),
ni = as.numeric(ni),
hi = as.numeric(hi)
)
# Corrección definitiva dentro de la tabla
tabla_era$Era <- gsub("precámbico", "Precambrico", tabla_era$Era, ignore.case = TRUE)
tabla_era$Era <- gsub("Precámbico", "Precambrico", tabla_era$Era, ignore.case = TRUE)
Fila total de las sumas de ni y hi
# Fila TOTAL
fila_total2 <- data.frame(
Era = "TOTAL",
ni = sum(tabla_era$ni),
hi = round(sum(tabla_era$hi), )
)
# Unir tablas
tabla_era <- rbind(tabla_era, fila_total2)
tabla_era
## Era ni hi
## 1 Precambrico 343 31.55
## 2 Paleozoico 522 48.02
## 3 Mesozoico 149 13.71
## 4 Cenozoico 73 6.72
## 5 TOTAL 1087 100.00
TABLA DE DISTRIBUCION DE FRECUENCIA AGRUPADA FINAL
tabla_era_gt <- tabla_era %>%
gt() %>%
tab_header(
title = md("**Tabla N° 1**"),
subtitle = md("Distribución de frecuencia simples por era geologica en <br>
depósitos Masivos de Sulfuro Volcánicos")
) %>%
tab_source_note(
source_note = md("Autor: Grupo 2")
) %>%
tab_options(
table.border.top.color = "black",
table.border.bottom.color = "black",
heading.border.bottom.color = "black",
heading.border.bottom.width = px(2),
column_labels.border.top.color = "black",
column_labels.border.bottom.color = "black",
column_labels.border.bottom.width = px(2),
table_body.hlines.color = "gray",
table_body.border.bottom.color = "black",
row.striping.include_table_body = TRUE
)
tabla_era_gt
| Tabla N° 1 | ||
| Distribución de frecuencia simples por era geologica en depósitos Masivos de Sulfuro Volcánicos |
||
| Era | ni | hi |
|---|---|---|
| Precambrico | 343 | 31.55 |
| Paleozoico | 522 | 48.02 |
| Mesozoico | 149 | 13.71 |
| Cenozoico | 73 | 6.72 |
| TOTAL | 1087 | 100.00 |
| Autor: Grupo 2 | ||
Diagrama de barras de frecuencia absoluta local
barplot(
tabla_era$ni[1:(nrow(tabla_era)-1)],
main = "Gráfica Nº1: Distribución de frecuencia absoluta local de era
geologica de los depositos masivos de sulfuros volcanicos ",
cex.main = 0.8,
col = "gray",
xlab = "Era geologica",
ylab = "Cantidad (ni)",
names.arg = tabla_era$Era[1:(nrow(tabla_era)-1)]
)
Diagrama de barras de frecuencia absoluta global
barplot(
tabla_era$ni[1:(nrow(tabla_era)-1)],
main = "Gráfica Nº2: Distribución de frecuencia absoluta global de era
geologica de los depositos masivos de sulfuros volcanicos",
cex.main = 0.8,
xlab = "Era geologica",
ylab = "Cantidad (ni)",
col = "gray",
names.arg = tabla_era$Era[1:(nrow(tabla_era)-1)],
ylim = c(0, 1090)
)
Diagrama de barras de frecuencia relativa local
hi_local <- as.numeric(tabla_era$hi[1:(nrow(tabla_era)-1)])
barplot(
hi_local,
main = "Gráfica Nº3: Distribución de frecuencia relativa local de era
geologica de los depositos masivos de sulfuros volcanicos",
cex.main = 0.8,
xlab = "Era geologica",
ylab = "Porcentaje (%)",
col = "gray",
names.arg = tabla_era$Era[1:(nrow(tabla_era)-1)]
)
Diagrama de barras de frecuencia relativa global
hi_global <- as.numeric(tabla_era$hi[1:(nrow(tabla_era)-1)])
barplot(
hi_global,
main = "Gráfica Nº4: Distribución de frecuencia relativa global de era
geologica de los depositos masivos de sulfuros volcanicos",
cex.main = 0.8,
xlab = "Era geologica",
ylab = "Porcentaje (%)",
col = "gray",
names.arg = tabla_era$Era[1:(nrow(tabla_era)-1)],
ylim = c(0, 100)
)
DIAGRAMA CIRCULAR
hi_era <- as.numeric(tabla_era$hi[1:(nrow(tabla_era)-1)])
eras <- tabla_era$Era[1:(nrow(tabla_era)-1)]
Colores <- colorRampPalette(c("lightskyblue", "darkblue"))(length(hi_era))
etiquetas <- paste0(hi_era, "%")
par(mfrow = c(1,2))
par(mar = c(2,2,4,2))
pie(
hi_era,
radius = 0.8,
col = Colores,
labels = etiquetas,
main = "Gráfica Nº5: Distribución de frecuencias
relativas de era geologica de los depositos masivos
de sulfuros volcanicos",
cex.main = 0.8
)
plot.new()
legend(
"center",
title = "Era geologica",
legend = eras,
fill = Colores,
cex = 0.7,
bg = "white",
box.lwd = 0.7
)
Indicadores Estadisticos
POSICION MODA
# Asegurar que ERA sea vector
ERA_limpia <- as.character(Era)
ERA_limpia <- ERA_limpia[!is.na(ERA_limpia)]
# Tabla de frecuencias
tabla_era <- table(ERA_limpia)
# Moda
moda_era <- names(tabla_era)[which.max(as.numeric(tabla_era))]
moda_era
## [1] "Paleozoico"
Se puede calcualar la mediana debido a que es una variable ordianal y su tamaño muestral es impar
MEDIANA
Me<-median(ERA_limpia)
Me
## [1] "Paleozoico"
TABLA DE INDICADORES ESTADISTICOS
Variable<-c("Era Geologica")
TablaIndicadores<-data.frame(Variable,moda_era,Me)
colnames(TablaIndicadores)<-c("Variable","Moda","Mediana")
kable(TablaIndicadores, format = "markdown", caption = "Tabla N°3. Indicadores estadíticos de la variable era geologica de los depositos masivos de sulfuros volcanicos")
| Variable | Moda | Mediana |
|---|---|---|
| Era Geologica | Paleozoico | Paleozoico |
CONCLUSÍON
La variable Era Geológica presenta registros que fluctúan entre Precámbrico y Cenozoico, y sus valores se encuentran en torno a la era Paleozoica. Lo resulta beneficiosa para el análisis minero, ya que dicho periodo geológico está asociado a la formación de numerosos yacimientos minerales, lo que facilita la evaluación del potencial geológico y la orientación de las actividades de exploración.