# ============================================================
# Taller IDH - Construcción de un índice propio
# Base: IDH Duty.xlsx
# ============================================================
# 1. Instalar paquetes si no están instalados
if (!requireNamespace("readxl", quietly = TRUE)) install.packages("readxl")
if (!requireNamespace("writexl", quietly = TRUE)) install.packages("writexl")
if (!requireNamespace("ggplot2", quietly = TRUE)) install.packages("ggplot2")
# 2. Cargar paquetes
library(readxl)
library(writexl)
library(ggplot2)
# 3. Definir ruta del archivo
ruta <- "C:/Users/Nina Sanchez/Documents/ACER -LENOVO-NINA 2019-20/1. USCO/ESTADISTICA/2026_Estadistica/Malaver/IDH Duty.xlsx"
# 4. Revisar hojas disponibles
readxl::excel_sheets(ruta)
## [1] "IDH" "Metadata"
# 5. Cargar la base de datos
# Si la hoja IDH no funciona, cambiar sheet = "IDH" por sheet = 1
base <- readxl::read_excel(ruta, sheet = "IDH")
# 6. Revisar estructura de la base
View(base)
str(base)
## tibble [30 × 8] (S3: tbl_df/tbl/data.frame)
## $ Country : chr [1:30] "Argentina" "Austria" "Belgium" "Bolivia (Plurinational State of)" ...
## $ Escolaridad: num [1:30] 17.7 16.1 19.8 14.2 15.4 16.2 16.4 14.4 15.7 14.6 ...
## $ Esperanza : num [1:30] 76.7 81.5 81.6 71.5 75.9 82.4 80.2 77.3 80.3 77 ...
## $ PIB : num [1:30] 21190 56197 52085 8554 14263 ...
## $ Gini : num [1:30] 41.4 29.7 27.4 42.2 53.9 33.8 44.4 50.4 48 45.4 ...
## $ Desempleo : num [1:30] 9.8 4.7 5.6 3.5 12.1 5.6 7.1 9.7 11.9 4 ...
## $ Cexterior : num [1:30] 32.4 107.7 163.3 56.4 29 ...
## $ Agr : chr [1:30] "South" "Euro" "Euro" "South" ...
summary(base)
## Country Escolaridad Esperanza PIB Gini
## Length :30 Min. : 9.70 Min. :64.00 Min. : 1709 Min. :27.40
## N.unique :30 1st Qu.:13.22 1st Qu.:75.08 1st Qu.:11339 1st Qu.:34.48
## N.blank : 0 Median :15.50 Median :77.60 Median :20627 Median :41.25
## Min.nchar: 4 Mean :14.99 Mean :77.76 Mean :26297 Mean :40.40
## Max.nchar:34 3rd Qu.:16.48 3rd Qu.:81.45 3rd Qu.:42326 3rd Qu.:46.00
## Max. :19.80 Max. :83.60 Max. :63826 Max. :53.90
## Desempleo Cexterior Agr
## Min. : 2.500 Min. : 26.40 Length :30
## 1st Qu.: 3.900 1st Qu.: 47.35 N.unique : 3
## Median : 5.600 Median : 65.55 N.blank : 0
## Mean : 6.977 Mean : 70.63 Min.nchar: 4
## 3rd Qu.: 9.475 3rd Qu.: 85.25 Max.nchar: 5
## Max. :17.200 Max. :163.30
names(base)
## [1] "Country" "Escolaridad" "Esperanza" "PIB" "Gini"
## [6] "Desempleo" "Cexterior" "Agr"
# ============================================================
# Construcción del IDH propio
# ============================================================
# 7. Crear una copia de la base
base_idh <- base
# 8. Transformación logarítmica del PIB
base_idh$log_PIB <- log(base_idh$PIB)
# 9. Índice de salud
base_idh$I_salud <- (base_idh$Esperanza - min(base_idh$Esperanza, na.rm = TRUE)) /
(max(base_idh$Esperanza, na.rm = TRUE) - min(base_idh$Esperanza, na.rm = TRUE))
# 10. Índice de educación
base_idh$I_educacion <- (base_idh$Escolaridad - min(base_idh$Escolaridad, na.rm = TRUE)) /
(max(base_idh$Escolaridad, na.rm = TRUE) - min(base_idh$Escolaridad, na.rm = TRUE))
# 11. Índice de ingreso
base_idh$I_PIB <- (base_idh$log_PIB - min(base_idh$log_PIB, na.rm = TRUE)) /
(max(base_idh$log_PIB, na.rm = TRUE) - min(base_idh$log_PIB, na.rm = TRUE))
# 12. Índice de apertura económica
base_idh$I_apertura <- (base_idh$Cexterior - min(base_idh$Cexterior, na.rm = TRUE)) /
(max(base_idh$Cexterior, na.rm = TRUE) - min(base_idh$Cexterior, na.rm = TRUE))
# 13. Índice de equidad
# Se invierte porque mayor Gini indica mayor desigualdad
base_idh$I_equidad <- 1 - ((base_idh$Gini - min(base_idh$Gini, na.rm = TRUE)) /
(max(base_idh$Gini, na.rm = TRUE) - min(base_idh$Gini, na.rm = TRUE)))
# 14. Índice de empleo
# Se invierte porque mayor desempleo indica peor condición laboral
base_idh$I_empleo <- 1 - ((base_idh$Desempleo - min(base_idh$Desempleo, na.rm = TRUE)) /
(max(base_idh$Desempleo, na.rm = TRUE) - min(base_idh$Desempleo, na.rm = TRUE)))
# 15. Fórmula final del IDH propio
base_idh$IDH_propio <- 0.20 * base_idh$I_salud +
0.20 * base_idh$I_educacion +
0.20 * base_idh$I_PIB +
0.15 * base_idh$I_equidad +
0.15 * base_idh$I_empleo +
0.10 * base_idh$I_apertura
# 16. Revisar resultados
View(base_idh)
summary(base_idh$IDH_propio)
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.1421 0.4758 0.5774 0.5925 0.7272 0.9367
# ============================================================
# Ranking de países
# ============================================================
ranking_idh <- base_idh[order(-base_idh$IDH_propio), ]
ranking_idh <- ranking_idh[, c(
"Country",
"Agr",
"Escolaridad",
"Esperanza",
"PIB",
"Gini",
"Desempleo",
"Cexterior",
"I_salud",
"I_educacion",
"I_PIB",
"I_equidad",
"I_empleo",
"I_apertura",
"IDH_propio"
)]
View(ranking_idh)
print(ranking_idh)
## # A tibble: 30 × 15
## Country Agr Escolaridad Esperanza PIB Gini Desempleo Cexterior I_salud
## <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Belgium Euro 19.8 81.6 52085 27.4 5.6 163. 0.898
## 2 Germany Euro 17 81.3 55314 31.9 3 88.1 0.883
## 3 Austria Euro 16.1 81.5 56197 29.7 4.7 108. 0.893
## 4 United K… Euro 17.5 81.3 46071 34.8 3.9 64.3 0.883
## 5 Hungary Euro 15.2 76.9 31329 30.6 3.4 163 0.658
## 6 Canada North 16.2 82.4 48527 33.8 5.6 65 0.939
## 7 Portugal Euro 16.5 82 33967 33.8 6.3 87.6 0.918
## 8 France Euro 15.6 82.7 47173 31.6 8.4 64.5 0.954
## 9 Italy Euro 16.1 83.5 42776 35.9 9.9 60.1 0.995
## 10 Spain Euro 17.6 83.6 40975 34.7 14 66.9 1
## # ℹ 20 more rows
## # ℹ 6 more variables: I_educacion <dbl>, I_PIB <dbl>, I_equidad <dbl>,
## # I_empleo <dbl>, I_apertura <dbl>, IDH_propio <dbl>
# 17. Diez países con mayor IDH propio
top10 <- head(ranking_idh, 10)
print(top10)
## # A tibble: 10 × 15
## Country Agr Escolaridad Esperanza PIB Gini Desempleo Cexterior I_salud
## <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Belgium Euro 19.8 81.6 52085 27.4 5.6 163. 0.898
## 2 Germany Euro 17 81.3 55314 31.9 3 88.1 0.883
## 3 Austria Euro 16.1 81.5 56197 29.7 4.7 108. 0.893
## 4 United K… Euro 17.5 81.3 46071 34.8 3.9 64.3 0.883
## 5 Hungary Euro 15.2 76.9 31329 30.6 3.4 163 0.658
## 6 Canada North 16.2 82.4 48527 33.8 5.6 65 0.939
## 7 Portugal Euro 16.5 82 33967 33.8 6.3 87.6 0.918
## 8 France Euro 15.6 82.7 47173 31.6 8.4 64.5 0.954
## 9 Italy Euro 16.1 83.5 42776 35.9 9.9 60.1 0.995
## 10 Spain Euro 17.6 83.6 40975 34.7 14 66.9 1
## # ℹ 6 more variables: I_educacion <dbl>, I_PIB <dbl>, I_equidad <dbl>,
## # I_empleo <dbl>, I_apertura <dbl>, IDH_propio <dbl>
# 18. Diez países con menor IDH propio
bottom10 <- tail(ranking_idh, 10)
print(bottom10)
## # A tibble: 10 × 15
## Country Agr Escolaridad Esperanza PIB Gini Desempleo Cexterior I_salud
## <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Bolivia … South 14.2 71.5 8554 42.2 3.5 56.4 0.383
## 2 El Salva… North 11.7 73.3 8359 38.6 4.1 77.2 0.474
## 3 Paraguay South 12.7 74.3 12224 46.2 4.8 69.2 0.526
## 4 Colombia South 14.4 77.3 14257 50.4 9.7 38.1 0.679
## 5 Venezuel… South 12.8 72.1 7045 36.7 8.8 48.1 0.413
## 6 Nicaragua North 12.3 74.5 5284 46.2 6.8 95.1 0.536
## 7 Guatemala North 10.8 74.3 8494 48.3 2.5 45.9 0.526
## 8 Brazil South 15.4 75.9 14263 53.9 12.1 29 0.607
## 9 Honduras North 10.1 75.3 5308 52.1 5.4 96.6 0.577
## 10 Haiti North 9.7 64 1709 41.1 13.8 74.3 0
## # ℹ 6 more variables: I_educacion <dbl>, I_PIB <dbl>, I_equidad <dbl>,
## # I_empleo <dbl>, I_apertura <dbl>, IDH_propio <dbl>
# ============================================================
# Resumen por región o agrupación
# ============================================================
resumen_region <- aggregate(
cbind(
IDH_propio,
Escolaridad,
Esperanza,
PIB,
Gini,
Desempleo,
Cexterior
) ~ Agr,
data = base_idh,
FUN = mean,
na.rm = TRUE
)
View(resumen_region)
print(resumen_region)
## Agr IDH_propio Escolaridad Esperanza PIB Gini Desempleo Cexterior
## 1 Euro 0.7692348 16.93 81.66 43604.2 32.48 7.64 93.99
## 2 North 0.4958444 13.05 75.65 20871.1 44.41 6.11 71.42
## 3 South 0.5123489 15.00 75.96 14415.4 44.31 7.18 46.48
# ============================================================
# Gráfico: 10 países con mayor IDH propio
# ============================================================
ggplot(top10, aes(x = reorder(Country, IDH_propio), y = IDH_propio)) +
geom_col() +
coord_flip() +
labs(
title = "Diez países con mayor IDH propio",
x = "País",
y = "IDH propio"
)
# ============================================================
# Gráfico: 10 países con menor IDH propio
# ============================================================
ggplot(bottom10, aes(x = reorder(Country, IDH_propio), y = IDH_propio)) +
geom_col() +
coord_flip() +
labs(
title = "Diez países con menor IDH propio",
x = "País",
y = "IDH propio"
)
# ============================================================
# Exportar resultados a Excel
# ============================================================
writexl::write_xlsx(
list(
"Base_con_IDH" = base_idh,
"Ranking_IDH" = ranking_idh,
"Resumen_region" = resumen_region
),
"Resultados_IDH_propio.xlsx"
)
# ============================================================
# Taller IDH - Construcción de un índice propio
# Base: IDH Duty.xlsx
# ============================================================
# 1. Instalar paquetes si no están instalados
if (!requireNamespace("readxl", quietly = TRUE)) install.packages("readxl")
if (!requireNamespace("writexl", quietly = TRUE)) install.packages("writexl")
if (!requireNamespace("ggplot2", quietly = TRUE)) install.packages("ggplot2")
# 2. Cargar paquetes
library(readxl)
library(writexl)
library(ggplot2)
# 3. Definir ruta del archivo
ruta <- "C:/Users/Nina Sanchez/Documents/ACER -LENOVO-NINA 2019-20/1. USCO/ESTADISTICA/2026_Estadistica/Malaver/IDH Duty.xlsx"
# 4. Revisar hojas disponibles
readxl::excel_sheets(ruta)
## [1] "IDH" "Metadata"
# 5. Cargar la base de datos
# Si la hoja IDH no funciona, cambiar sheet = "IDH" por sheet = 1
base <- readxl::read_excel(ruta, sheet = "IDH")
# 6. Revisar estructura de la base
View(base)
str(base)
## tibble [30 × 8] (S3: tbl_df/tbl/data.frame)
## $ Country : chr [1:30] "Argentina" "Austria" "Belgium" "Bolivia (Plurinational State of)" ...
## $ Escolaridad: num [1:30] 17.7 16.1 19.8 14.2 15.4 16.2 16.4 14.4 15.7 14.6 ...
## $ Esperanza : num [1:30] 76.7 81.5 81.6 71.5 75.9 82.4 80.2 77.3 80.3 77 ...
## $ PIB : num [1:30] 21190 56197 52085 8554 14263 ...
## $ Gini : num [1:30] 41.4 29.7 27.4 42.2 53.9 33.8 44.4 50.4 48 45.4 ...
## $ Desempleo : num [1:30] 9.8 4.7 5.6 3.5 12.1 5.6 7.1 9.7 11.9 4 ...
## $ Cexterior : num [1:30] 32.4 107.7 163.3 56.4 29 ...
## $ Agr : chr [1:30] "South" "Euro" "Euro" "South" ...
summary(base)
## Country Escolaridad Esperanza PIB Gini
## Length :30 Min. : 9.70 Min. :64.00 Min. : 1709 Min. :27.40
## N.unique :30 1st Qu.:13.22 1st Qu.:75.08 1st Qu.:11339 1st Qu.:34.48
## N.blank : 0 Median :15.50 Median :77.60 Median :20627 Median :41.25
## Min.nchar: 4 Mean :14.99 Mean :77.76 Mean :26297 Mean :40.40
## Max.nchar:34 3rd Qu.:16.48 3rd Qu.:81.45 3rd Qu.:42326 3rd Qu.:46.00
## Max. :19.80 Max. :83.60 Max. :63826 Max. :53.90
## Desempleo Cexterior Agr
## Min. : 2.500 Min. : 26.40 Length :30
## 1st Qu.: 3.900 1st Qu.: 47.35 N.unique : 3
## Median : 5.600 Median : 65.55 N.blank : 0
## Mean : 6.977 Mean : 70.63 Min.nchar: 4
## 3rd Qu.: 9.475 3rd Qu.: 85.25 Max.nchar: 5
## Max. :17.200 Max. :163.30
names(base)
## [1] "Country" "Escolaridad" "Esperanza" "PIB" "Gini"
## [6] "Desempleo" "Cexterior" "Agr"
# ============================================================
# Construcción del IDH propio
# ============================================================
# 7. Crear una copia de la base
base_idh <- base
# 8. Transformación logarítmica del PIB
base_idh$log_PIB <- log(base_idh$PIB)
# 9. Índice de salud
base_idh$I_salud <- (base_idh$Esperanza - min(base_idh$Esperanza, na.rm = TRUE)) /
(max(base_idh$Esperanza, na.rm = TRUE) - min(base_idh$Esperanza, na.rm = TRUE))
# 10. Índice de educación
base_idh$I_educacion <- (base_idh$Escolaridad - min(base_idh$Escolaridad, na.rm = TRUE)) /
(max(base_idh$Escolaridad, na.rm = TRUE) - min(base_idh$Escolaridad, na.rm = TRUE))
# 11. Índice de ingreso
base_idh$I_PIB <- (base_idh$log_PIB - min(base_idh$log_PIB, na.rm = TRUE)) /
(max(base_idh$log_PIB, na.rm = TRUE) - min(base_idh$log_PIB, na.rm = TRUE))
# 12. Índice de apertura económica
base_idh$I_apertura <- (base_idh$Cexterior - min(base_idh$Cexterior, na.rm = TRUE)) /
(max(base_idh$Cexterior, na.rm = TRUE) - min(base_idh$Cexterior, na.rm = TRUE))
# 13. Índice de equidad
# Se invierte porque mayor Gini indica mayor desigualdad
base_idh$I_equidad <- 1 - ((base_idh$Gini - min(base_idh$Gini, na.rm = TRUE)) /
(max(base_idh$Gini, na.rm = TRUE) - min(base_idh$Gini, na.rm = TRUE)))
# 14. Índice de empleo
# Se invierte porque mayor desempleo indica peor condición laboral
base_idh$I_empleo <- 1 - ((base_idh$Desempleo - min(base_idh$Desempleo, na.rm = TRUE)) /
(max(base_idh$Desempleo, na.rm = TRUE) - min(base_idh$Desempleo, na.rm = TRUE)))
# 15. Fórmula final del IDH propio
base_idh$IDH_propio <- 0.20 * base_idh$I_salud +
0.20 * base_idh$I_educacion +
0.20 * base_idh$I_PIB +
0.15 * base_idh$I_equidad +
0.15 * base_idh$I_empleo +
0.10 * base_idh$I_apertura
# 16. Revisar resultados
View(base_idh)
summary(base_idh$IDH_propio)
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.1421 0.4758 0.5774 0.5925 0.7272 0.9367
# ============================================================
# Ranking de países
# ============================================================
ranking_idh <- base_idh[order(-base_idh$IDH_propio), ]
ranking_idh <- ranking_idh[, c(
"Country",
"Agr",
"Escolaridad",
"Esperanza",
"PIB",
"Gini",
"Desempleo",
"Cexterior",
"I_salud",
"I_educacion",
"I_PIB",
"I_equidad",
"I_empleo",
"I_apertura",
"IDH_propio"
)]
View(ranking_idh)
print(ranking_idh)
## # A tibble: 30 × 15
## Country Agr Escolaridad Esperanza PIB Gini Desempleo Cexterior I_salud
## <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Belgium Euro 19.8 81.6 52085 27.4 5.6 163. 0.898
## 2 Germany Euro 17 81.3 55314 31.9 3 88.1 0.883
## 3 Austria Euro 16.1 81.5 56197 29.7 4.7 108. 0.893
## 4 United K… Euro 17.5 81.3 46071 34.8 3.9 64.3 0.883
## 5 Hungary Euro 15.2 76.9 31329 30.6 3.4 163 0.658
## 6 Canada North 16.2 82.4 48527 33.8 5.6 65 0.939
## 7 Portugal Euro 16.5 82 33967 33.8 6.3 87.6 0.918
## 8 France Euro 15.6 82.7 47173 31.6 8.4 64.5 0.954
## 9 Italy Euro 16.1 83.5 42776 35.9 9.9 60.1 0.995
## 10 Spain Euro 17.6 83.6 40975 34.7 14 66.9 1
## # ℹ 20 more rows
## # ℹ 6 more variables: I_educacion <dbl>, I_PIB <dbl>, I_equidad <dbl>,
## # I_empleo <dbl>, I_apertura <dbl>, IDH_propio <dbl>
# 17. Diez países con mayor IDH propio
top10 <- head(ranking_idh, 10)
print(top10)
## # A tibble: 10 × 15
## Country Agr Escolaridad Esperanza PIB Gini Desempleo Cexterior I_salud
## <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Belgium Euro 19.8 81.6 52085 27.4 5.6 163. 0.898
## 2 Germany Euro 17 81.3 55314 31.9 3 88.1 0.883
## 3 Austria Euro 16.1 81.5 56197 29.7 4.7 108. 0.893
## 4 United K… Euro 17.5 81.3 46071 34.8 3.9 64.3 0.883
## 5 Hungary Euro 15.2 76.9 31329 30.6 3.4 163 0.658
## 6 Canada North 16.2 82.4 48527 33.8 5.6 65 0.939
## 7 Portugal Euro 16.5 82 33967 33.8 6.3 87.6 0.918
## 8 France Euro 15.6 82.7 47173 31.6 8.4 64.5 0.954
## 9 Italy Euro 16.1 83.5 42776 35.9 9.9 60.1 0.995
## 10 Spain Euro 17.6 83.6 40975 34.7 14 66.9 1
## # ℹ 6 more variables: I_educacion <dbl>, I_PIB <dbl>, I_equidad <dbl>,
## # I_empleo <dbl>, I_apertura <dbl>, IDH_propio <dbl>
# 18. Diez países con menor IDH propio
bottom10 <- tail(ranking_idh, 10)
print(bottom10)
## # A tibble: 10 × 15
## Country Agr Escolaridad Esperanza PIB Gini Desempleo Cexterior I_salud
## <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Bolivia … South 14.2 71.5 8554 42.2 3.5 56.4 0.383
## 2 El Salva… North 11.7 73.3 8359 38.6 4.1 77.2 0.474
## 3 Paraguay South 12.7 74.3 12224 46.2 4.8 69.2 0.526
## 4 Colombia South 14.4 77.3 14257 50.4 9.7 38.1 0.679
## 5 Venezuel… South 12.8 72.1 7045 36.7 8.8 48.1 0.413
## 6 Nicaragua North 12.3 74.5 5284 46.2 6.8 95.1 0.536
## 7 Guatemala North 10.8 74.3 8494 48.3 2.5 45.9 0.526
## 8 Brazil South 15.4 75.9 14263 53.9 12.1 29 0.607
## 9 Honduras North 10.1 75.3 5308 52.1 5.4 96.6 0.577
## 10 Haiti North 9.7 64 1709 41.1 13.8 74.3 0
## # ℹ 6 more variables: I_educacion <dbl>, I_PIB <dbl>, I_equidad <dbl>,
## # I_empleo <dbl>, I_apertura <dbl>, IDH_propio <dbl>
# ============================================================
# Resumen por región o agrupación
# ============================================================
resumen_region <- aggregate(
cbind(
IDH_propio,
Escolaridad,
Esperanza,
PIB,
Gini,
Desempleo,
Cexterior
) ~ Agr,
data = base_idh,
FUN = mean,
na.rm = TRUE
)
View(resumen_region)
print(resumen_region)
## Agr IDH_propio Escolaridad Esperanza PIB Gini Desempleo Cexterior
## 1 Euro 0.7692348 16.93 81.66 43604.2 32.48 7.64 93.99
## 2 North 0.4958444 13.05 75.65 20871.1 44.41 6.11 71.42
## 3 South 0.5123489 15.00 75.96 14415.4 44.31 7.18 46.48
# ============================================================
# Gráfico: 10 países con mayor IDH propio
# ============================================================
ggplot(top10, aes(x = reorder(Country, IDH_propio), y = IDH_propio)) +
geom_col() +
coord_flip() +
labs(
title = "Diez países con mayor IDH propio",
x = "País",
y = "IDH propio"
)
# ============================================================
# Gráfico: 10 países con menor IDH propio
# ============================================================
ggplot(bottom10, aes(x = reorder(Country, IDH_propio), y = IDH_propio)) +
geom_col() +
coord_flip() +
labs(
title = "Diez países con menor IDH propio",
x = "País",
y = "IDH propio"
)
# ============================================================
# Exportar resultados a Excel
# ============================================================
writexl::write_xlsx(
list(
"Base_con_IDH" = base_idh,
"Ranking_IDH" = ranking_idh,
"Resumen_region" = resumen_region
),
"Resultados_IDH_propio.xlsx"
)
# ============================================================
# Tablas limpias para copiar al documento
# ============================================================
# Top 10 países con mayor IDH propio
top10_limpio <- top10[, c("Country", "Agr", "IDH_propio")]
top10_limpio$IDH_propio <- round(top10_limpio$IDH_propio, 4)
View(top10_limpio)
print(top10_limpio)
## # A tibble: 10 × 3
## Country Agr IDH_propio
## <chr> <chr> <dbl>
## 1 Belgium Euro 0.937
## 2 Germany Euro 0.828
## 3 Austria Euro 0.822
## 4 United Kingdom Euro 0.784
## 5 Hungary Euro 0.774
## 6 Canada North 0.762
## 7 Portugal Euro 0.753
## 8 France Euro 0.735
## 9 Italy Euro 0.705
## 10 Spain Euro 0.703
# Bottom 10 países con menor IDH propio
bottom10_limpio <- bottom10[, c("Country", "Agr", "IDH_propio")]
bottom10_limpio$IDH_propio <- round(bottom10_limpio$IDH_propio, 4)
View(bottom10_limpio)
print(bottom10_limpio)
## # A tibble: 10 × 3
## Country Agr IDH_propio
## <chr> <chr> <dbl>
## 1 Bolivia (Plurinational State of) South 0.482
## 2 El Salvador North 0.480
## 3 Paraguay South 0.475
## 4 Colombia South 0.451
## 5 Venezuela (Bolivarian Republic of) South 0.421
## 6 Nicaragua North 0.421
## 7 Guatemala North 0.411
## 8 Brazil South 0.406
## 9 Honduras North 0.368
## 10 Haiti North 0.142
# Resumen por región
resumen_region_limpio <- resumen_region
resumen_region_limpio$IDH_propio <- round(resumen_region_limpio$IDH_propio, 4)
resumen_region_limpio$Escolaridad <- round(resumen_region_limpio$Escolaridad, 2)
resumen_region_limpio$Esperanza <- round(resumen_region_limpio$Esperanza, 2)
resumen_region_limpio$PIB <- round(resumen_region_limpio$PIB, 2)
resumen_region_limpio$Gini <- round(resumen_region_limpio$Gini, 2)
resumen_region_limpio$Desempleo <- round(resumen_region_limpio$Desempleo, 2)
resumen_region_limpio$Cexterior <- round(resumen_region_limpio$Cexterior, 2)
View(resumen_region_limpio)
print(resumen_region_limpio)
## Agr IDH_propio Escolaridad Esperanza PIB Gini Desempleo Cexterior
## 1 Euro 0.7692 16.93 81.66 43604.2 32.48 7.64 93.99
## 2 North 0.4958 13.05 75.65 20871.1 44.41 6.11 71.42
## 3 South 0.5123 15.00 75.96 14415.4 44.31 7.18 46.48