Visualization of East African Countries’ performance since 1960 up to 2020

Data analysis with Gapminder dataset

gapminder_unfiltered %>%
        filter(country %in% c("Rwanda","Uganda", "Kenya","Burundi","Tanzania")) %>%
ggplot(aes(gdpPercap, lifeExp, size = pop, colour = country)) +
        geom_point(alpha = 0.7, show.legend = TRUE) +
        scale_size(range = c(2, 12)) +
        scale_x_log10() +
        facet_wrap(~continent) +
        # Here comes the gganimate specific bits
        labs(title = 'Year: {frame_time}', subtitle = "East African countries", x = 'GDP per capita', y = 'life expectancy') +
        transition_time(year) +
        ease_aes('linear')+
        geom_text(aes(label = country), hjust = 1.1)

Importing the data downloaded from Gapminder

World_population<-read_csv("C:/Users/user/Downloads/population_total.csv")
world_gdp_percapita<-read_csv("C:/Users/user/Downloads/ny_gdp_pcap_cd.csv")
world_life_expectancy<-read_csv("C:/Users/user/Downloads/life_expectancy_years.csv")

east_africa_population<-World_population %>%
        pivot_longer(names_to = "year", values_to = "population",cols = -country) %>%
        filter(year %in% c(1960:2020)) %>%
        filter(country %in% c("Rwanda","Uganda", "Kenya","Burundi","Tanzania"))

east_africa_GDP_per_capita<-world_gdp_percapita %>%
        pivot_longer(names_to = "year", values_to = "GDP",cols = -country)%>%
        filter(year %in% c(1960:2020)) %>%
        filter(country %in% c("Rwanda","Uganda", "Kenya","Burundi","Tanzania"))

east_africa_life_expectancy<-world_life_expectancy %>%
        pivot_longer(names_to = "year", values_to = "life_exp",cols = -country)%>%
        filter(year %in% c(1960:2020)) %>%
        filter(country %in% c("Rwanda","Uganda", "Kenya","Burundi","Tanzania"))

East_african_data<-full_join(east_africa_population,east_africa_life_expectancy, by = c("country","year"))%>%
        full_join(east_africa_GDP_per_capita,by = c("country","year") )

plot<-East_african_data %>%
        mutate(year = as.Date(year,"%Y")) %>%
        ggplot( aes(GDP, life_exp, size = population, colour = country)) +
        geom_point(show.legend = FALSE) +
        theme(legend.position = "none")+
        scale_size(range = c(2, 12)) +
        scale_x_log10() +
        # Here comes the gganimate specific bits
        labs(title = 'Year: {frame_time}', subtitle = "Comparison of East African countries since 1960 until 2020, in terms of GDP per Capita, \n Life Expectancy and population. Data source: Gapminder.org", x = 'GDP per capita (in Current US$) \n \n pplotted by Birasafab', y = 'life expectancy (in years)') +
        transition_time(year) +
        ease_aes('linear')+
        enter_fade() +
        exit_fade()+
        theme_light()+
        geom_text(aes(label = country), hjust = 1.1)
#+        shadow_wake(wake_length = 0.1, alpha = FALSE)

plot