Chapter 2 EDA Lecture 1-2 R Examples

2.1 Example 2 - Gapminder

#install.packages("gapminder")
library(gapminder)

## Warning: package 'gapminder' was built under R version 4.0.4

gapminder

## # A tibble: 1,704 x 6
##    country     continent  year lifeExp      pop gdpPercap
##    <fct>       <fct>     <int>   <dbl>    <int>     <dbl>
##  1 Afghanistan Asia       1952    28.8  8425333      779.
##  2 Afghanistan Asia       1957    30.3  9240934      821.
##  3 Afghanistan Asia       1962    32.0 10267083      853.
##  4 Afghanistan Asia       1967    34.0 11537966      836.
##  5 Afghanistan Asia       1972    36.1 13079460      740.
##  6 Afghanistan Asia       1977    38.4 14880372      786.
##  7 Afghanistan Asia       1982    39.9 12881816      978.
##  8 Afghanistan Asia       1987    40.8 13867957      852.
##  9 Afghanistan Asia       1992    41.7 16317921      649.
## 10 Afghanistan Asia       1997    41.8 22227415      635.
## # ... with 1,694 more rows

2.2 Frequency Distribution

library(ggplot2)
table(gapminder$continent)

## 
##   Africa Americas     Asia   Europe  Oceania 
##      624      300      396      360       24

2.3 Bar Plot

library(ggplot2)
plot1 <- ggplot(gapminder, aes(x=continent)) + geom_bar()
plot1

2.4 Pie Chart

plot1 + coord_polar()

If you would like to have a regular pie chart, then you need to provide the frequency distribution.

2.5 Histogram

2.5.1 A Simple Histogram

library(ggplot2)
plot2 <- ggplot(gapminder,
                aes(x = gdpPercap))
plot2 + geom_histogram(binwidth = 1000)

2.5.2 Histogram With a Title

plot2 + 
  geom_histogram(binwidth = 1000) +
  labs(title = "Histogram of GDP per Capita for All Years")

2.5.3 Histogram with Different Color Schemes:

plot2 + 
  geom_histogram(binwidth = 1000, color="black", fill="white") +
  labs(title = "Histogram of GDP per Capita for All Years")

2.5.4 Histogram of Log Transformed Variable:

plot3 <- ggplot(gapminder,
                aes(x = log10(gdpPercap)))
plot3 + 
  geom_histogram(binwidth = .2, color="black", fill="white") +
  labs(title = "Histogram of  Log Transformed GDP per Capita for All Years")

2.5.5 Determine the Binwidth

How do we determine the binwidth?

So we can create our own function for the binwidth:

width_bin = function(x) (max(x)-min(x)) / sqrt(length(x))
manualbin = width_bin(log10(gapminder$gdpPercap))

plot3 + 
  geom_histogram(binwidth = manualbin, color="black", fill="white")

or simply

plot3 + 
  geom_histogram(binwidth = function(x) (max(x)-min(x)) / sqrt(length(x)), color="black", fill="white") +
    labs(title = "Histogram of  Log Transformed GDP per Capita for All Years (Genstat Binwidth)")

But you will notice that Gdp per capita variable includes all years, all continents, all countries!!!

2.5.6 Histogram for a Subset of Data

Log Transformed GDP per Capita for 2007:

plot4 <- ggplot(subset(gapminder, year == 2007),
                aes(x = log10(gdpPercap)))
plot4 + 
   geom_histogram(binwidth = function(x) (max(x)-min(x)) / sqrt(length(x)), color="black", fill="white") +
  labs(title = "Histogram of  Log Transformed GDP per Capita for 2007 (Genstat Binwidth)")

2.5.7 Histogram with Overall Mean Line

Log Transformed GDP per Capita for 2007 with the Overall Mean Line

# Histogram with mean of log10(gdpPercap) on the plot
plot4 + 
  geom_histogram(binwidth = function(x) (max(x)-min(x)) / sqrt(length(x)), color="black", fill="white") +
  geom_vline(aes(xintercept=mean(log10(gdpPercap))),
            color="blue", linetype="dashed", size=1) +
  labs(title = "Histogram of  Log Transformed GDP per Capita for 2007 (Genstat Binwidth)")

2.5.8 Histogram with Density plot

# Histogram with density plot
ggplot(subset(gapminder, year == 2007),
                aes(x = log10(gdpPercap))) +  
  geom_histogram(aes(y=..density..), binwidth = function(x) (max(x)-min(x)) / sqrt(length(x)),colour="black", fill="white")+
  geom_density(alpha=0, fill="#FF6666") #alpha for transparency, if alpha = 0, no fill

2.5.9 Histogram with Facets

How about looking at the differences among different continents?

# Histogram with mean of log10(gdpPercap) on the plot
plot4 + 
  geom_histogram(binwidth = function(x) (max(x)-min(x)) / sqrt(length(x)), color="black", fill="white") +
  geom_vline(aes(xintercept=mean(log10(gdpPercap))),
            color="blue", linetype="dashed", size=1) +
  facet_grid(continent ~ .)

2.6 Boxplots

# Histogram with mean of log10(gdpPercap) on the plot
plot5 <- ggplot(subset(gapminder, year == 2007),
                aes(x = year, y = log10(gdpPercap))) 
# if x axis variable is numeric, then one single boxplot
# if x axis variable is categorical, then works like facets

plot5 + 
  geom_boxplot() #+ coord_flip()

Try with ``continent" variable.

2.7 Scatter Plots

2.7.1 A Simple Scatter Plot

plot6 <- ggplot(subset(gapminder, year == 2007),
                aes(x = lifeExp, y = log10(gdpPercap)))
plot6 +
  geom_point()

2.7.2 Scatter Plot with Labellings

plot6 +
  geom_point(aes(colour = factor(continent)))

2.7.3 Scatter Plot with Linear Lines for Different Groups

plot6 +
  geom_point(aes(colour = factor(continent))) +
  geom_smooth(aes(group = continent, colour = factor(continent)), lwd = 1, se = FALSE, method = "lm")

## `geom_smooth()` using formula 'y ~ x'

plot7 <- ggplot(gapminder,
                aes(x = lifeExp, y = log10(gdpPercap)))
plot7 +
  geom_point(aes(colour = factor(continent))) +
  facet_wrap(~ year) # scales = "free_x"

For more check ``ggplot2: Elegant Graphics for Data Analysis (Use R!)" by (Hadley Wickham)