STAT 545 - HW #2

Mina Park

In this exercise, we are writing an R Markdown file for an exploration and initial analysis of some Gapminder data.

1.) Load + explore features of the Gapminder dataset

data <- read.delim("gapminderDataFiveYear.txt")
str(data)

## 'data.frame':    1704 obs. of  6 variables:
##  $ country  : Factor w/ 142 levels "Afghanistan",..: 1 1 1 1 1 1 1 1 1 1 ...
##  $ year     : int  1952 1957 1962 1967 1972 1977 1982 1987 1992 1997 ...
##  $ pop      : num  8425333 9240934 10267083 11537966 13079460 ...
##  $ continent: Factor w/ 5 levels "Africa","Americas",..: 3 3 3 3 3 3 3 3 3 3 ...
##  $ lifeExp  : num  28.8 30.3 32 34 36.1 ...
##  $ gdpPercap: num  779 821 853 836 740 ...

summary(data)

##         country          year           pop              continent  
##  Afghanistan:  12   Min.   :1952   Min.   :6.00e+04   Africa  :624  
##  Albania    :  12   1st Qu.:1966   1st Qu.:2.79e+06   Americas:300  
##  Algeria    :  12   Median :1980   Median :7.02e+06   Asia    :396  
##  Angola     :  12   Mean   :1980   Mean   :2.96e+07   Europe  :360  
##  Argentina  :  12   3rd Qu.:1993   3rd Qu.:1.96e+07   Oceania : 24  
##  Australia  :  12   Max.   :2007   Max.   :1.32e+09                 
##  (Other)    :1632                                                   
##     lifeExp       gdpPercap     
##  Min.   :23.6   Min.   :   241  
##  1st Qu.:48.2   1st Qu.:  1202  
##  Median :60.7   Median :  3532  
##  Mean   :59.5   Mean   :  7215  
##  3rd Qu.:70.8   3rd Qu.:  9325  
##  Max.   :82.6   Max.   :113523  
##

Note the variables and other observations in the data
Note that data is in “data frame” mode

2.) Plot relationship between gdp and life expectancy in Canada and the US

library(lattice)
library(latticeExtra)

## Loading required package: RColorBrewer

plotCan <- xyplot(lifeExp ~ gdpPercap, data, subset = country == "Canada", type = c("p", 
    "smooth"), main = "Life Expectancy per GDP in Canada and the US")

plotUSA <- xyplot(lifeExp ~ gdpPercap, data, subset = country == "United States", 
    type = c("p", "smooth"))

doubleYScale(plotCan, plotUSA, add.axis = FALSE, text = c("Canada", "USA"))

plot of chunk unnamed-chunk-2

Canada has greater life exp than US across income

There are other ways to do this, for example:

xyplot(lifeExp ~ gdpPercap, data, subset = country == "Canada", type = c("p", 
    "smooth"), col = "red", main = "Life Expectancy per GDP in Canada and the US") + 
    as.layer(xyplot(lifeExp ~ gdpPercap, data, subset = country == "United States", 
        type = c("p", "smooth"), col = "blue"))

plot of chunk unnamed-chunk-3

# can't figure out how to add a legend using this method, however