library(dplyr)
library(readxl)
library(gt)
library(countrycode)datos <- read_excel("dataset_mundial_petro.xlsx")
Variable <- countrycode(datos$Country, origin = 'country.name', destination = 'continent')str(datos)## tibble [8,334 × 23] (S3: tbl_df/tbl/data.frame)
## $ Unit ID : chr [1:8334] "OG0000001" "OG0000002" "OG0000006" "OG0000007" ...
## $ Unit Name : chr [1:8334] "Matzen" "Abalone" "Aguilhada" "Agulha" ...
## $ Unit name local script : chr [1:8334] NA "Abalone" "Aguilhada" "Agulha" ...
## $ Fuel type : chr [1:8334] "oil and gas" "oil and gas" "oil and gas" "oil and gas" ...
## $ Unit type : chr [1:8334] "field" "field" "field" "field" ...
## $ Country : chr [1:8334] "Austria" "Brazil" "Brazil" "Brazil" ...
## $ Subnational unit (province, state): chr [1:8334] NA "Espírito Santo" "Sergipe" "Rio Grande do Norte" ...
## $ Latitude : num [1:8334] 48.4 -21.4 -10.7 -4.9 -22.1 ...
## $ Longitude : num [1:8334] 16.7 -39.6 -36.9 -36.3 -40 ...
## $ Location accuracy : chr [1:8334] "approximate" "exact" "exact" "exact" ...
## $ Status : chr [1:8334] "operating" "operating" "operating" "operating" ...
## $ Status year : num [1:8334] 2023 2022 2022 2022 2022 ...
## $ Discovery year : num [1:8334] 1949 2001 1966 1975 1984 ...
## $ FID Year : chr [1:8334] NA NA NA NA ...
## $ Production start year : chr [1:8334] "1951" "2009" "1969" "1979" ...
## $ Operator : chr [1:8334] "OMV" "Shell Brasil Petróleo Ltda." NA NA ...
## $ Owner : chr [1:8334] "OMV (100%)" "Shell Brasil (50%);ONGC Campos (27%);Qatarenergy (23%)" "Petrobras (100%)" "Petrobras (100%)" ...
## $ Parent : chr [1:8334] "OMV Aktiengesellschaft (100%)" "Shell plc (50%);Oil and Natural Gas Corporation (ONGC) (27%)" "Petróleo Brasileiro S.A. (100%)" "Petróleo Brasileiro S.A. (100%)" ...
## $ Basin : chr [1:8334] NA NA NA NA ...
## $ Concession / block : chr [1:8334] NA NA NA NA ...
## $ Project or complex : chr [1:8334] "Matzen" NA NA NA ...
## $ Government unit ID : chr [1:8334] NA NA NA NA ...
## $ Wiki URL : chr [1:8334] "https://www.gem.wiki/Matzen_Oil_and_Gas_Field_(Austria)" "https://www.gem.wiki/Abalone_Oil_and_Gas_Field_%28Esp%C3%ADrito_Santo%2C_Brazil%29" "https://www.gem.wiki/Aguilhada_Oil_and_Gas_Field_%28Sergipe%2C_Brazil%29" "https://www.gem.wiki/Agulha_Oil_and_Gas_Field_%28Rio_Grande_do_Norte%2C_Brazil%29" ...Se realizó la agrupación geográfica de la variable
Country mediante el paquete countrycode,
consolidando los 104 países del dataset en categorías
continentales para facilitar el análisis de los 8,334
yacimientos registrados a nivel global.
Variable <- countrycode(datos$Country, origin = 'country.name', destination = 'continent')Se calculó la distribución de frecuencias absolutas (\(n_i\)) y relativas (\(h_i\)). Los resultados muestran que América concentra la mayor proporción de yacimientos, seguida por Europa y Asia, evidenciando la distribución global de la actividad extractiva de hidrocarburos.
Tabla <- as.data.frame(table(Variable))
colnames(Tabla) <- c("Continente", "ni")
Tabla$"Continente" <- as.character(Tabla$"Continente")
Tabla$`hi (%)` <- round((Tabla$ni / sum(Tabla$ni)) * 100, 2)
fila_total <- tibble(
`Continente` = "TOTAL",
ni = sum(Tabla$ni),
`hi (%)` = 100.00
)
tabla_Final <- bind_rows(Tabla, fila_total)
tabla_gt <- tabla_Final %>%
gt() %>%
tab_header(
title = md("**Tabla N°7.2 de Distribución de Frecuencias por Continente de los Yacimientos de Petróleo y Gas**")
) %>%
tab_source_note(
source_note = "Autor: Grupo 5"
) %>%
cols_label(
`Continente` = "Continente",
ni = "Frecuencia (ni)",
`hi (%)` = "Porcentaje (hi%)"
) %>%
fmt_number(
columns = `hi (%)`,
decimals = 2
) %>%
tab_options(
heading.title.font.size = px(16),
column_labels.background.color = "#F0F0F0"
)
tabla_gt| Tabla N°7.2 de Distribución de Frecuencias por Continente de los Yacimientos de Petróleo y Gas | ||
| Continente | Frecuencia (ni) | Porcentaje (hi%) |
|---|---|---|
| Africa | 635 | 7.64 |
| Americas | 5395 | 64.91 |
| Asia | 889 | 10.70 |
| Europe | 1202 | 14.46 |
| Oceania | 191 | 2.30 |
| TOTAL | 8312 | 100.00 |
| Autor: Grupo 5 | ||