gapminder_analysis.R

download.file("https://raw.githubusercontent.com/swcarpentry/r-novice-gapminder/gh-pages/_episodes_rmd/data/gapminder-FiveYearData.csv", destfile = "data/gapminder-FiveYearData.csv")

gapminder <- read.csv("data/gapminder-FiveYearData.csv")

mean(gapminder$lifeExp)

max(gapminder$year)
gapminder$year == 2007

gapminder2007 <- gapminder[gapminder$year == 2007,]
mean(gapminder2007$lifeExp)
mean(gapminder$lifeExp)

plot(gapminder$lifeExp,gapminder$gdpPercap) 

# start of ggplot2 section
library(tidyverse)
ggplot(data=gapminder,aes(x=gdpPercap,y=lifeExp)) +
    geom_point()
ggplot(data=gapminder,aes(x=year,y=lifeExp)) +
    geom_point()


ggplot(data=gapminder,aes(x=year,y=lifeExp,by=country,color=continent)) +
    geom_point()+
    geom_line()


ggplot(data=gapminder,aes(x=gdpPercap,y=lifeExp, color=continent)) +
    geom_point() +
    scale_x_log10()+
    geom_smooth(method="lm")



ggplot(data=gapminder[gapminder$continent=="Americas",],aes(x=gdpPercap,y=lifeExp, color=continent, by=country)) +
    geom_point() +
    scale_x_log10()+
    geom_smooth(method="lm")+
    facet_wrap( ~ country)


ggplot(data=gapminder[gapminder$continent=="Americas",],aes(x=gdpPercap,y=lifeExp, color=continent, by=country)) +
    geom_point() +
    scale_x_log10()+
    geom_smooth(method="lm")+
    facet_wrap( ~ country)

# interactive plotting with plotly
if(!require("plotly")){install.packages("plotly")}
library(plotly)

p <- ggplot(data=gapminder[gapminder$continent=="Americas",],aes(x=gdpPercap,y=lifeExp, color=continent, by=country)) +
    geom_point() +
    scale_x_log10()+
    geom_smooth(method="lm")+
    facet_wrap( ~ country)

p
ggplotly(p)

# making nice labels
p + labs(x="GDP per Capita", y="Life Expectancy (y)",
         title="Figure 1") +
    scale_color_discrete(name="Continent")