CARGA DE DATOS
#Carga de datos
setwd("~/UNI/ESTADISTICA")
datos <- read.csv("Depositos_Sulfuro.csv", header = TRUE, sep = ";", dec = ".")
CARGA DE LIBRERIAS
#Carga de librerias
library(countrycode)
library(gt)
library(dplyr)
library(knitr)
TABLA DE DISTRIBUCION DE PROBABILIDAD POR PAIS
#Tabla de distribución de probabilidad por País
TablaPais <- as.data.frame(table(datos$country))
colnames(TablaPais) <- c("Pais", "ni")
TablaPais$hi <- round(TablaPais$ni / sum(TablaPais$ni), 4)
TablaPais$P <- round(TablaPais$hi * 100, 2)
#Fila TOTAL
total_pais <- data.frame(
Pais = "Total",
ni = sum(TablaPais$ni),
hi = round(sum(TablaPais$hi),),
P = round(sum(TablaPais$P),)
)
# Unir tabla final
TablaPaisFinal <- rbind(TablaPais, total_pais)
# Mostrar tabla
TablaPaisFinal
## Pais ni hi P
## 1 Argentina 2 0.0018 0.18
## 2 Armenia 4 0.0037 0.37
## 3 Australia 56 0.0514 5.14
## 4 Bolivia 1 0.0009 0.09
## 5 Brazil 3 0.0028 0.28
## 6 Canada 317 0.2908 29.08
## 7 Chile 2 0.0018 0.18
## 8 China 37 0.0339 3.39
## 9 Colombia 6 0.0055 0.55
## 10 Cuba 13 0.0119 1.19
## 11 Cyprus 18 0.0165 1.65
## 12 Dominican Republic 3 0.0028 0.28
## 13 Ecuador 2 0.0018 0.18
## 14 Egypt 1 0.0009 0.09
## 15 Eritrea 3 0.0028 0.28
## 16 Fiji 3 0.0028 0.28
## 17 Finland 12 0.0110 1.10
## 18 France 4 0.0037 0.37
## 19 Georgia 4 0.0037 0.37
## 20 Great Britain 1 0.0009 0.09
## 21 Guatemala 1 0.0009 0.09
## 22 Guyana 2 0.0018 0.18
## 23 India 2 0.0018 0.18
## 24 Indonesia 4 0.0037 0.37
## 25 Iran 2 0.0018 0.18
## 26 Ireland 1 0.0009 0.09
## 27 Japan 82 0.0752 7.52
## 28 Kazakhstan 46 0.0422 4.22
## 29 Mexico 16 0.0147 1.47
## 30 Mongolia 1 0.0009 0.09
## 31 Morocco 3 0.0028 0.28
## 32 Norway 49 0.0450 4.50
## 33 Oman 3 0.0028 0.28
## 34 Pakistan 1 0.0009 0.09
## 35 Peru 5 0.0046 0.46
## 36 Philippines 19 0.0174 1.74
## 37 Portugal 14 0.0128 1.28
## 38 Russia 90 0.0826 8.26
## 39 Saudi Arabia 21 0.0193 1.93
## 40 Spain 61 0.0560 5.60
## 41 Sweden 40 0.0367 3.67
## 42 Turkey 26 0.0239 2.39
## 43 Union of Myanmar 1 0.0009 0.09
## 44 United States 100 0.0917 9.17
## 45 Uzbekistan 5 0.0046 0.46
## 46 Venezuela 3 0.0028 0.28
## 47 Total 1090 1.0000 100.00
TABLA DE DISTRIBUCION DE PROBABILIDAD POR PAIS
tabla_pais_gt <- TablaPaisFinal %>%
gt() %>%
tab_header(
title = md("**Tabla N° 1**"),
subtitle = md("**Distribución de probabilidad de los Depósitos Masivos<br>
de Sulfuro Volcánicos por País**")
) %>%
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
) %>%
tab_style(
style = cell_text(weight = "bold"),
locations = cells_body(rows = Pais == "Total")
)
tabla_pais_gt
| Tabla N° 1 | |||
| Distribución de probabilidad de los Depósitos Masivos de Sulfuro Volcánicos por País |
|||
| Pais | ni | hi | P |
|---|---|---|---|
| Argentina | 2 | 0.0018 | 0.18 |
| Armenia | 4 | 0.0037 | 0.37 |
| Australia | 56 | 0.0514 | 5.14 |
| Bolivia | 1 | 0.0009 | 0.09 |
| Brazil | 3 | 0.0028 | 0.28 |
| Canada | 317 | 0.2908 | 29.08 |
| Chile | 2 | 0.0018 | 0.18 |
| China | 37 | 0.0339 | 3.39 |
| Colombia | 6 | 0.0055 | 0.55 |
| Cuba | 13 | 0.0119 | 1.19 |
| Cyprus | 18 | 0.0165 | 1.65 |
| Dominican Republic | 3 | 0.0028 | 0.28 |
| Ecuador | 2 | 0.0018 | 0.18 |
| Egypt | 1 | 0.0009 | 0.09 |
| Eritrea | 3 | 0.0028 | 0.28 |
| Fiji | 3 | 0.0028 | 0.28 |
| Finland | 12 | 0.0110 | 1.10 |
| France | 4 | 0.0037 | 0.37 |
| Georgia | 4 | 0.0037 | 0.37 |
| Great Britain | 1 | 0.0009 | 0.09 |
| Guatemala | 1 | 0.0009 | 0.09 |
| Guyana | 2 | 0.0018 | 0.18 |
| India | 2 | 0.0018 | 0.18 |
| Indonesia | 4 | 0.0037 | 0.37 |
| Iran | 2 | 0.0018 | 0.18 |
| Ireland | 1 | 0.0009 | 0.09 |
| Japan | 82 | 0.0752 | 7.52 |
| Kazakhstan | 46 | 0.0422 | 4.22 |
| Mexico | 16 | 0.0147 | 1.47 |
| Mongolia | 1 | 0.0009 | 0.09 |
| Morocco | 3 | 0.0028 | 0.28 |
| Norway | 49 | 0.0450 | 4.50 |
| Oman | 3 | 0.0028 | 0.28 |
| Pakistan | 1 | 0.0009 | 0.09 |
| Peru | 5 | 0.0046 | 0.46 |
| Philippines | 19 | 0.0174 | 1.74 |
| Portugal | 14 | 0.0128 | 1.28 |
| Russia | 90 | 0.0826 | 8.26 |
| Saudi Arabia | 21 | 0.0193 | 1.93 |
| Spain | 61 | 0.0560 | 5.60 |
| Sweden | 40 | 0.0367 | 3.67 |
| Turkey | 26 | 0.0239 | 2.39 |
| Union of Myanmar | 1 | 0.0009 | 0.09 |
| United States | 100 | 0.0917 | 9.17 |
| Uzbekistan | 5 | 0.0046 | 0.46 |
| Venezuela | 3 | 0.0028 | 0.28 |
| Total | 1090 | 1.0000 | 100.00 |
| Autor: Grupo 2 | |||
Debido a que la tabla presenta numerosos registros de paises, se decidió agruparlos por continentes
TABLA DE DISTRIBUCION DE PROBABILIDAD AGRUPADA
# Tabla de distribución de probabilidad por continente
# Asignar continente
TablaPais$Continente <- countrycode(
TablaPais$Pais,
origin = "country.name",
destination = "continent"
)
# Agregar por continente
TablaContinente <- aggregate(ni ~ Continente, data = TablaPais, sum)
# Calculo de frecuencias
TablaContinente$hi <- round(TablaContinente$ni / sum(TablaContinente$ni),4)
TablaContinente$P <- round( TablaContinente$hi * 100,2)
# Fila TOTAL
total_continente <- data.frame(
Continente = "Total",
ni = sum(TablaContinente$ni),
hi = round(sum(TablaContinente$hi),),
P = round(sum(TablaContinente$P),)
)
# Tabla final
TablaContinenteFinal <- rbind(TablaContinente, total_continente)
TablaContinenteFinal
## Continente ni hi P
## 1 Africa 7 0.0064 0.64
## 2 Americas 476 0.4367 43.67
## 3 Asia 276 0.2532 25.32
## 4 Europe 272 0.2495 24.95
## 5 Oceania 59 0.0541 5.41
## 6 Total 1090 1.0000 100.00
TABLA DE DISTRIBUCION DE PROBABILIDAD AGRUPADA FINAL
tabla_continente_gt <- TablaContinenteFinal %>%
gt() %>%
tab_header(
title = md("**Tabla N° 2**"),
subtitle = md("**Distribución de probabilidad de los Depósitos Masivos<br>
de Sulfuro Volcánicos por continente**")
) %>%
tab_source_note(
source_note = md("Autor: Grupo 2")
) %>%
tab_options(
table.border.top.color = "black",
table.border.bottom.color = "black",
heading.border.bottom.color = "black",
heading.border.bottom.width = px(2),
column_labels.border.top.color = "black",
column_labels.border.bottom.color = "black",
column_labels.border.bottom.width = px(2),
table_body.hlines.color = "gray",
table_body.border.bottom.color = "black",
row.striping.include_table_body = TRUE
) %>%
tab_style(
style = cell_text(weight = "bold"),
locations = cells_body(rows = Continente == "Total")
)
tabla_continente_gt
| Tabla N° 2 | |||
| Distribución de probabilidad de los Depósitos Masivos de Sulfuro Volcánicos por continente |
|||
| Continente | ni | hi | P |
|---|---|---|---|
| Africa | 7 | 0.0064 | 0.64 |
| Americas | 476 | 0.4367 | 43.67 |
| Asia | 276 | 0.2532 | 25.32 |
| Europe | 272 | 0.2495 | 24.95 |
| Oceania | 59 | 0.0541 | 5.41 |
| Total | 1090 | 1.0000 | 100.00 |
| Autor: Grupo 2 | |||
Diagrama de barras
# Extraer porcentajes
P_global <- as.numeric(
TablaContinenteFinal$P[1:(nrow(TablaContinenteFinal) - 1)]
)
continentes <- TablaContinenteFinal$Continente[
1:(nrow(TablaContinenteFinal) - 1)
]
#Diagrama de barras
barplot(
P_global,
main = "Gráfica Nº1: Distribución de probabilidad de los Depósitos Masivos
de Sulfuros Volcánicos en Continentes",
xlab = "Continente",
ylab = "Probabilidad (%)",
col = "blue",
names.arg = continentes,
cex.names = 1,
ylim = c(0, 100)
)
# Identificar el continente con mayor probabilidad (excluye Total)
tabla_sin_total <- TablaContinenteFinal[TablaContinenteFinal$Continente != "Total", ]
continente_mayor <- tabla_sin_total$Continente[
which.max(tabla_sin_total$P)
]
prob_mayor <- tabla_sin_total$P[
which.max(tabla_sin_total$P)
]
# Gráfico de texto explicativo
plot(1, type = "n", axes = FALSE, xlab = "", ylab = "")
text(
x = 1, y = 1,
labels = paste(
"Cálculo de probabilidad\n(Estimación general)\n\n",
"¿Qué continente es más probable\n",
"que concentre la mayor cantidad de\n",
"depósitos masivos de sulfuros volcánicos?\n\n",
"R: ", continente_mayor, "\n",
"Probabilidad = ", prob_mayor, " (%)",
sep = ""
),
cex = 1.4,
col = "black",
font = 2
)