library(dplyr)
library(readxl)
library(gt)
datos    <- read_excel("dataset_mundial_petro.xlsx")
Variable <- datos$Country

1 Configuración y Carga de Datos

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" ...

2 Extraer Variable

Se extrajo la variable Country del dataset, la cual registra el país donde se encuentra ubicado cada yacimiento de extracción de petróleo y gas. El dataset contiene un total de 8,334 observaciones distribuidas en 104 países a nivel mundial.

Variable <- datos$Country

3 Tabla de Distribución de Frecuencias

Se calculó la distribución de frecuencias absolutas (\(n_i\)) y relativas (\(h_i\)). Los resultados muestran que Estados Unidos concentra la mayor cantidad de yacimientos con el 37.11%, seguido de Canadá con el 14.13%, lo que evidencia una fuerte concentración en América del Norte.

Tabla <- as.data.frame(table(Variable))
colnames(Tabla) <- c("País", "ni")
Tabla$"País" <- as.character(Tabla$"País")
Tabla$`hi (%)` <- round((Tabla$ni / sum(Tabla$ni)) * 100, 2)

fila_total <- tibble(
  `País` = "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°7.1 de Distribución de Frecuencias por País de los Yacimientos de Petróleo y Gas**")
  ) %>%
  tab_source_note(
    source_note = "Autor: Grupo 5"
  ) %>%
  cols_label(
    `País` = "País",
    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°7.1 de Distribución de Frecuencias por País de los Yacimientos de Petróleo y Gas
País Frecuencia (ni) Porcentaje (hi%)
Albania 1 0.01
Algeria 58 0.70
Angola 77 0.92
Argentina 202 2.42
Australia 179 2.15
Austria 3 0.04
Azerbaijan 22 0.26
Bahrain 2 0.02
Bangladesh 7 0.08
Barbados 6 0.07
Bolivia 11 0.13
Brazil 97 1.16
Brunei 14 0.17
Cameroon 4 0.05
Canada 1178 14.13
Chad 10 0.12
Chile 1 0.01
China 111 1.33
China-Japan 1 0.01
Colombia 288 3.46
Côte d'Ivoire 5 0.06
Cuba 10 0.12
Cyprus 5 0.06
Denmark 23 0.28
Ecuador 93 1.12
Egypt 96 1.15
Ethiopia 5 0.06
France 2 0.02
Gabon 2 0.02
Germany 52 0.62
Ghana 4 0.05
Grenada 1 0.01
Guatemala 4 0.05
Guyana 19 0.23
Hungary 2 0.02
India 56 0.67
Indonesia 76 0.91
Iran 100 1.20
Iran-Iraq 3 0.04
Iraq 57 0.68
Ireland 15 0.18
Israel 14 0.17
Italy 38 0.46
Jamaica 1 0.01
Japan 1 0.01
Kazakhstan 47 0.56
Kenya 2 0.02
Kuwait 14 0.17
Kuwait-Saudi Arabia 6 0.07
Kuwait-Saudi Arabia-Iran 2 0.02
Libya 41 0.49
Madagascar 1 0.01
Malaysia 73 0.88
Mauritania 4 0.05
Mexico 197 2.36
Morocco 1 0.01
Mozambique 17 0.20
Myanmar 6 0.07
Namibia 5 0.06
Netherlands 164 1.97
New Zealand 7 0.08
Nigeria 246 2.95
Norway 113 1.36
Oman 41 0.49
Pakistan 38 0.46
Palestine 1 0.01
Papua New Guinea 5 0.06
Peru 26 0.31
Philippines 2 0.02
Poland 111 1.33
Qatar 25 0.30
Republic of the Congo 14 0.17
Romania 67 0.80
Russia 277 3.32
Russia-Kazakhstan 2 0.02
Saudi Arabia 28 0.34
Saudi Arabia-Bahrain 1 0.01
Saudi Arabia-Iran 1 0.01
Senegal 3 0.04
Senegal-Mauritania 1 0.01
South Africa 4 0.05
South Sudan 5 0.06
Spain 1 0.01
Suriname 5 0.06
Syria 8 0.10
Tanzania 22 0.26
Thailand 42 0.50
Thailand-Malaysia 2 0.02
Timor-Leste 2 0.02
Timor Gap 1 0.01
Trinidad and Tobago 35 0.42
Tunisia 5 0.06
Türkiye 6 0.07
Turkmenistan 23 0.28
Uganda 3 0.04
Ukraine 16 0.19
United Arab Emirates 42 0.50
United Arab Emirates-Iran 1 0.01
United Kingdom 317 3.80
United States 3093 37.11
Venezuela 128 1.54
Vietnam 26 0.31
Vietnam-Malaysia 1 0.01
Zimbabwe 1 0.01
TOTAL 8334 100.00
Autor: Grupo 5