“WBI”

Instalar paquetes

install.packages(“WDI”) install.packages(“wbstats”) *install.packages(“tidyverse”)

Informacion de 1 país

library(wbstats)

gdp_data <- wb_data(country = "MX" , indicator = "NY.GDP.PCAP.CD" , start_date = 1973 , end_date = 2022)
summary(gdp_data)

##     iso2c              iso3c             country               date     
##  Length:49          Length:49          Length:49          Min.   :1973  
##  Class :character   Class :character   Class :character   1st Qu.:1985  
##  Mode  :character   Mode  :character   Mode  :character   Median :1997  
##                                                           Mean   :1997  
##                                                           3rd Qu.:2009  
##                                                           Max.   :2021  
##  NY.GDP.PCAP.CD        unit            obs_status          footnote        
##  Min.   :  981.5   Length:49          Length:49          Length:49         
##  1st Qu.: 2569.2   Class :character   Class :character   Class :character  
##  Median : 5650.0   Mode  :character   Mode  :character   Mode  :character  
##  Mean   : 5751.7                                                           
##  3rd Qu.: 9068.3                                                           
##  Max.   :10928.9                                                           
##   last_updated       
##  Min.   :2022-09-16  
##  1st Qu.:2022-09-16  
##  Median :2022-09-16  
##  Mean   :2022-09-16  
##  3rd Qu.:2022-09-16  
##  Max.   :2022-09-16

head(gdp_data)

## # A tibble: 6 × 9
##   iso2c iso3c country  date NY.GDP.PCAP.CD unit  obs_status footnote last_upda…¹
##   <chr> <chr> <chr>   <dbl>          <dbl> <chr> <chr>      <chr>    <date>     
## 1 MX    MEX   Mexico   1973           981. <NA>  <NA>       <NA>     2022-09-16 
## 2 MX    MEX   Mexico   1974          1242. <NA>  <NA>       <NA>     2022-09-16 
## 3 MX    MEX   Mexico   1975          1476. <NA>  <NA>       <NA>     2022-09-16 
## 4 MX    MEX   Mexico   1976          1454. <NA>  <NA>       <NA>     2022-09-16 
## 5 MX    MEX   Mexico   1977          1301. <NA>  <NA>       <NA>     2022-09-16 
## 6 MX    MEX   Mexico   1978          1589. <NA>  <NA>       <NA>     2022-09-16 
## # … with abbreviated variable name ¹​last_updated

tail(gdp_data)

## # A tibble: 6 × 9
##   iso2c iso3c country  date NY.GDP.PCAP.CD unit  obs_status footnote last_upda…¹
##   <chr> <chr> <chr>   <dbl>          <dbl> <chr> <chr>      <chr>    <date>     
## 1 MX    MEX   Mexico   2016          8745. <NA>  <NA>       <NA>     2022-09-16 
## 2 MX    MEX   Mexico   2017          9288. <NA>  <NA>       <NA>     2022-09-16 
## 3 MX    MEX   Mexico   2018          9687. <NA>  <NA>       <NA>     2022-09-16 
## 4 MX    MEX   Mexico   2019          9950. <NA>  <NA>       <NA>     2022-09-16 
## 5 MX    MEX   Mexico   2020          8432. <NA>  <NA>       <NA>     2022-09-16 
## 6 MX    MEX   Mexico   2021          9926. <NA>  <NA>       <NA>     2022-09-16 
## # … with abbreviated variable name ¹​last_updated

library(ggplot2)

ggplot(gdp_data, aes(x = date, y = NY.GDP.PCAP.CD)) + 
  geom_point()

ggplot(gdp_data, aes(x = date, y = NY.GDP.PCAP.CD)) + 
  geom_col()

ggplot(gdp_data, aes(x = date, y = NY.GDP.PCAP.CD)) + 
  geom_col(fill = "red") + 
  geom_point(color = "blue")

Información de varios países

more_gdp_data <- wb_data(country = c("NG","HT","KE"),
                         indicator= "NY.GDP.PCAP.CD" , 
                         start_date= 1981, end_date = 2015)

ggplot(more_gdp_data, aes(x = date, y = NY.GDP.PCAP.CD, color = country, shape=country))+ 
  geom_point()

Conclusiones

El Banco Mundial es una organización multinacional especializada en finanzas y asistencia. Con esta base de datos en RStudio, se puede consultar el ingreso per capita de diferentes países ya sea de uno solo o de varios en un mismo código. Una de las recomendaciones para realizar esta base de datos, es descargar de manera correcta todas las librerías necesarias.