World Bank

Introducción

Los datos del World Bank Indicators (WBI) son una fuente completa de indicadores economicos, sociales y medioambientales de mas de 200 paises. [Fuente: WB] (https://data.worldbank.org/indicator?tab=a11)

Instalar paquetes y llamar librerias

#install.packages ("WDI")
library(WDI)
#install.packages ("wbstats")
library(wbstats)
#install.packages ("tidyverse")
library(tidyverse)

## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.4     ✔ readr     2.1.5
## ✔ forcats   1.0.0     ✔ stringr   1.5.1
## ✔ ggplot2   3.5.1     ✔ tibble    3.2.1
## ✔ lubridate 1.9.3     ✔ tidyr     1.3.1
## ✔ purrr     1.0.2     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

#install.packages ("ggplot2")
library(ggplot2)

Información de 1 país

gdp_mexico <- wb_data(country = "MX", indicator = "NY.GDP.PCAP.CD", start_date=1900, end_date=2024)
summary(gdp_mexico)

##     iso2c              iso3c             country               date     
##  Length:64          Length:64          Length:64          Min.   :1960  
##  Class :character   Class :character   Class :character   1st Qu.:1976  
##  Mode  :character   Mode  :character   Mode  :character   Median :1992  
##                                                           Mean   :1992  
##                                                           3rd Qu.:2007  
##                                                           Max.   :2023  
##  NY.GDP.PCAP.CD        unit            obs_status          footnote        
##  Min.   :  359.5   Length:64          Length:64          Length:64         
##  1st Qu.: 1431.5   Class :character   Class :character   Class :character  
##  Median : 4017.8   Mode  :character   Mode  :character   Mode  :character  
##  Mean   : 5132.1                                                           
##  3rd Qu.: 8959.9                                                           
##  Max.   :13926.1                                                           
##   last_updated       
##  Min.   :2024-06-28  
##  1st Qu.:2024-06-28  
##  Median :2024-06-28  
##  Mean   :2024-06-28  
##  3rd Qu.:2024-06-28  
##  Max.   :2024-06-28

head(gdp_mexico)

## # A tibble: 6 × 9
##   iso2c iso3c country  date NY.GDP.PCAP.CD unit  obs_status footnote
##   <chr> <chr> <chr>   <dbl>          <dbl> <chr> <chr>      <chr>   
## 1 MX    MEX   Mexico   1960           360. <NA>  <NA>       <NA>    
## 2 MX    MEX   Mexico   1961           378. <NA>  <NA>       <NA>    
## 3 MX    MEX   Mexico   1962           393. <NA>  <NA>       <NA>    
## 4 MX    MEX   Mexico   1963           424. <NA>  <NA>       <NA>    
## 5 MX    MEX   Mexico   1964           486. <NA>  <NA>       <NA>    
## 6 MX    MEX   Mexico   1965           511. <NA>  <NA>       <NA>    
## # ℹ 1 more variable: last_updated <date>

tail(gdp_mexico)

## # A tibble: 6 × 9
##   iso2c iso3c country  date NY.GDP.PCAP.CD unit  obs_status footnote
##   <chr> <chr> <chr>   <dbl>          <dbl> <chr> <chr>      <chr>   
## 1 MX    MEX   Mexico   2018         10130. <NA>  <NA>       <NA>    
## 2 MX    MEX   Mexico   2019         10435. <NA>  <NA>       <NA>    
## 3 MX    MEX   Mexico   2020          8896. <NA>  <NA>       <NA>    
## 4 MX    MEX   Mexico   2021         10363. <NA>  <NA>       <NA>    
## 5 MX    MEX   Mexico   2022         11477. <NA>  <NA>       <NA>    
## 6 MX    MEX   Mexico   2023         13926. <NA>  <NA>       <NA>    
## # ℹ 1 more variable: last_updated <date>

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

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

ggplot(gdp_mexico, aes(x= date, y= NY.GDP.PCAP.CD)) +
  geom_col(fill = "cyan") +
  geom_point(color = "blue") +
  labs(title="Producto Interno bruta en Mexico (US per Capita)", x = "Año", y = "PIB")

# Información de varios paises

gdp_varios <- wb_data(country= c("MX", "EC", "CL"), indicator = "NY.GDP.PCAP.CD", start_date= 1900, end_date= 2024)

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