Africas GDP over time

Author

Kieran Mace

Published

February 20, 2018

Code

library(tidyverse)
library(countrycode)
library(WDI)
library(magick)
library(tidyverse)
library(ggmap)
library(maps)
library(mapdata)
library(magrittr)
library(gganimate)
library(viridis)

Getting the contries in Africa

We also need to fix some of the names slightly

Code

countries = countrycode::codelist_panel
africa_countries = countries %>% 
  filter(continent == 'Africa') %>% 
  select(country.name.en, iso2c) %>%
  unique.data.frame() %>%
  rename(Country_Name = country.name.en,
         Country_Code = iso2c) %>%
  mutate(Country_Name = if_else(Country_Name == "Congo - Brazzaville", 'Republic of the Congo', Country_Name),
         Country_Name = if_else(Country_Name == "Congo - Kinshasa",'Democratic Republic of the Congo', Country_Name),
         Country_Name = if_else(Country_Name == "Côte d'Ivoire",'Ivory Coast', Country_Name),
         Country_Name = if_else(Country_Name == "Réunion",'Reunion', Country_Name),
         Country_Name = if_else(Country_Name == "St. Helena",'Saint Helena', Country_Name),
         Country_Name = if_else(Country_Name ==  "São Tomé & Príncipe",'Sao Tome and Principe', Country_Name))

Pulling the GDP info

Code

africa_gdp = WDI(indicator='NY.GDP.PCAP.KD', 
                 country=africa_countries$Country_Code, 
                 start=1960, 
                 end=2018) %>%
  rename(Country_Code = iso2c,
         GDP = NY.GDP.PCAP.KD) %>%
  select(Country_Code, GDP, year)

Let’s look at the GDP as a function of time

Code

ggplot(africa_gdp, aes(year, GDP, color=Country_Code)) + geom_line() + 
    xlab('Year') + ylab('GDP per capita')

Lets get the map of africa.

Join it all together

Code

africa = africa_map %>% left_join(africa_countries) %>% left_join(africa_gdp)

Putting it all together, a movie of africas GDP over the last 80 years.

Code

p = africa %>%
 ggplot(aes(x = long, 
            y = lat, 
            group = group, 
            fill = log10(GDP))) +
  coord_fixed(1.3) +
  geom_polygon() + 
  theme_minimal() + 
  scale_fill_viridis() +
  transition_time(year) +
  labs(title = 'Year: {frame_time}')

anim <- animate(p)
anim_save("africa.gif", animation = anim)

# for(year in unique(sort(africa$year))){
# p = africa %>% filter(year == year) %>%
#  ggplot(aes(x = long, y = lat, group = group, fill = log10(GDP))) +
#   coord_fixed(1.3) +
#   geom_polygon() + 
#   theme_minimal() + 
#   scale_fill_viridis()
#   print(p)
# }

--- title: "Africas GDP over time" author: "Kieran Mace" date: "2018-02-20" categories: [R] format: html: code-fold: true --- ```{r setup, include=FALSE} knitr::opts_chunk$set(echo = TRUE, warning = FALSE) ``` ```{r message=FALSE, warning=FALSE} library(tidyverse) library(countrycode) library(WDI) library(magick) library(tidyverse) library(ggmap) library(maps) library(mapdata) library(magrittr) library(gganimate) library(viridis) ``` ## Getting the contries in Africa We also need to fix some of the names slightly ```{r} countries = countrycode::codelist_panel africa_countries = countries %>% filter(continent == 'Africa') %>% select(country.name.en, iso2c) %>% unique.data.frame() %>% rename(Country_Name = country.name.en, Country_Code = iso2c) %>% mutate(Country_Name = if_else(Country_Name == "Congo - Brazzaville", 'Republic of the Congo', Country_Name), Country_Name = if_else(Country_Name == "Congo - Kinshasa",'Democratic Republic of the Congo', Country_Name), Country_Name = if_else(Country_Name == "Côte d'Ivoire",'Ivory Coast', Country_Name), Country_Name = if_else(Country_Name == "Réunion",'Reunion', Country_Name), Country_Name = if_else(Country_Name == "St. Helena",'Saint Helena', Country_Name), Country_Name = if_else(Country_Name == "São Tomé & Príncipe",'Sao Tome and Principe', Country_Name)) ``` ## Pulling the GDP info ```{r} africa_gdp = WDI(indicator='NY.GDP.PCAP.KD', country=africa_countries$Country_Code, start=1960, end=2018) %>% rename(Country_Code = iso2c, GDP = NY.GDP.PCAP.KD) %>% select(Country_Code, GDP, year) ``` Let's look at the GDP as a function of time ```{r} ggplot(africa_gdp, aes(year, GDP, color=Country_Code)) + geom_line() + xlab('Year') + ylab('GDP per capita') ``` Lets get the map of africa. ```{r map, echo=FALSE} world_map = map_data("world") africa_map = world_map %>% filter(region %in% africa_countries$Country_Name) %>% rename(Country_Name = region) ``` Join it all together ```{r} africa = africa_map %>% left_join(africa_countries) %>% left_join(africa_gdp) ``` ## Putting it all together, a movie of africas GDP over the last 80 years. ```{r} p = africa %>% ggplot(aes(x = long, y = lat, group = group, fill = log10(GDP))) + coord_fixed(1.3) + geom_polygon() + theme_minimal() + scale_fill_viridis() + transition_time(year) + labs(title = 'Year: {frame_time}') anim <- animate(p) anim_save("africa.gif", animation = anim) # for(year in unique(sort(africa$year))){ # p = africa %>% filter(year == year) %>% # ggplot(aes(x = long, y = lat, group = group, fill = log10(GDP))) + # coord_fixed(1.3) + # geom_polygon() + # theme_minimal() + # scale_fill_viridis() # print(p) # } ``` ![Image](africa.gif)