World Bank

Instalar programas requeridos

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

## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ──
## ✔ ggplot2 3.3.6      ✔ purrr   0.3.4 
## ✔ tibble  3.1.8      ✔ dplyr   1.0.10
## ✔ tidyr   1.2.1      ✔ stringr 1.4.1 
## ✔ readr   2.1.2      ✔ forcats 0.5.2 
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()

library(WDI)
library(wbstats)

Extraccion de datos de la bd del Banco Mundial

Informacion de 1 pais

gdp_data <- wb_data(country="MX", indicator = "NY.GDP.PCAP.CD",start_date = 1973,end_date = 2020)
"Cantidad de procedimientos quirúrgicos (por cada 100 000 habitantes)"

## [1] "Cantidad de procedimientos quirúrgicos (por cada 100 000 habitantes)"

Resumen de la información extraída

Resumen de data

summary(gdp_data)

##     iso2c              iso3c             country               date     
##  Length:48          Length:48          Length:48          Min.   :1973  
##  Class :character   Class :character   Class :character   1st Qu.:1985  
##  Mode  :character   Mode  :character   Mode  :character   Median :1996  
##                                                           Mean   :1996  
##                                                           3rd Qu.:2008  
##                                                           Max.   :2020  
##  NY.GDP.PCAP.CD        unit            obs_status          footnote        
##  Min.   :  981.5   Length:48          Length:48          Length:48         
##  1st Qu.: 2546.5   Class :character   Class :character   Class :character  
##  Median : 5565.6   Mode  :character   Mode  :character   Mode  :character  
##  Mean   : 5664.7                                                           
##  3rd Qu.: 8825.5                                                           
##  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

Datos(5) iniciales y finales

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   2015          9617. <NA>  <NA>       <NA>     2022-09-16 
## 2 MX    MEX   Mexico   2016          8745. <NA>  <NA>       <NA>     2022-09-16 
## 3 MX    MEX   Mexico   2017          9288. <NA>  <NA>       <NA>     2022-09-16 
## 4 MX    MEX   Mexico   2018          9687. <NA>  <NA>       <NA>     2022-09-16 
## 5 MX    MEX   Mexico   2019          9950. <NA>  <NA>       <NA>     2022-09-16 
## 6 MX    MEX   Mexico   2020          8432. <NA>  <NA>       <NA>     2022-09-16 
## # … with abbreviated variable name ¹​last_updated

Grafica de datos obtenidos

Ggplot y analisis

Grafica dispersión

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

## Grafica dispersión rellena

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

## Distinción por color

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

Analisis y extraccion de mas data

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()