Sean Jewell

STAT 545A Homework 2

This is an example R Markdown file to illustrate my competency with Markdown. We will be looking at the Gapminder dataset at a very basic level. We plan to:

• Import the data
• Describe a few summary statistics
• Create a few figures to illustrate the power of ggplot2 while examining the data

Import data

Here we will import the data and also bring in the (beautiful) ggplot2 library

gDat <- read.delim("gapminderDataFiveYear.txt")
library(ggplot2)

Summary statistics

str(gDat)

## '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(gDat)

##         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  
## 

Markdown also allows for inline code: There are 1704 rows of data.

A few figures always makes for easier reading

• Here we look at how life expectancy has changed over time

qplot(year, lifeExp, data = gDat)

• What does this look like on a country by country basis?

ggplot(gDat, aes(x = gdpPercap, y = lifeExp, color = continent)) + geom_point()

*Now, on a continent basis

p <- ggplot(gDat, aes(x = gdpPercap, y = lifeExp)) + geom_point(data = subset(gDat, 
    year == 2007))
p + facet_grid(. ~ continent)