DW Homework 4

Homework 4

# Install used packages
library(tidyverse)
library(knitr)
library(GGally)
library(gapminder)

Gapminder Dataset Analysis

str(gapminder)

## tibble [1,704 × 6] (S3: tbl_df/tbl/data.frame)
##  $ country  : Factor w/ 142 levels "Afghanistan",..: 1 1 1 1 1 1 1 1 1 1 ...
##  $ continent: Factor w/ 5 levels "Africa","Americas",..: 3 3 3 3 3 3 3 3 3 3 ...
##  $ year     : int [1:1704] 1952 1957 1962 1967 1972 1977 1982 1987 1992 1997 ...
##  $ lifeExp  : num [1:1704] 28.8 30.3 32 34 36.1 ...
##  $ pop      : int [1:1704] 8425333 9240934 10267083 11537966 13079460 14880372 12881816 13867957 16317921 22227415 ...
##  $ gdpPercap: num [1:1704] 779 821 853 836 740 ...

summary(gapminder)

##         country        continent        year         lifeExp     
##  Afghanistan:  12   Africa  :624   Min.   :1952   Min.   :23.60  
##  Albania    :  12   Americas:300   1st Qu.:1966   1st Qu.:48.20  
##  Algeria    :  12   Asia    :396   Median :1980   Median :60.71  
##  Angola     :  12   Europe  :360   Mean   :1980   Mean   :59.47  
##  Argentina  :  12   Oceania : 24   3rd Qu.:1993   3rd Qu.:70.85  
##  Australia  :  12                  Max.   :2007   Max.   :82.60  
##  (Other)    :1632                                                
##       pop              gdpPercap       
##  Min.   :6.001e+04   Min.   :   241.2  
##  1st Qu.:2.794e+06   1st Qu.:  1202.1  
##  Median :7.024e+06   Median :  3531.8  
##  Mean   :2.960e+07   Mean   :  7215.3  
##  3rd Qu.:1.959e+07   3rd Qu.:  9325.5  
##  Max.   :1.319e+09   Max.   :113523.1  
## 

Above is the detailed structure and summary of the dataset of life expectancy data over the years for various countries:

• Year: This column indicate the data that has been collected over the years from various countries all over the world.
• Country: This is a categorical variable cotains the list of countries that are part of this dataset.
• Continent : This is also a categorical variables which is used to identify the continents where the countries belong.
• lifeexp: This has the lifeexpectancy data based on the countries and year when its collected.
• gdppercap: This variable has the data of gdp per capita of the coutries at the respective years.
• pop: This variable has the population of the countries over the years.

Life Expectancy Ratio

ggplot(gapminder %>% 
         filter(year %in% c("1952", "2007")),
       aes(x = gdpPercap, y = lifeExp, color = year, size = pop)) +
  geom_point(alpha = 0.25) +
  labs(  title ="Scatter Plot between GDP Per Capita and Life Expectancy \nshowing the effect of population (1952-2007)", 
         y = "Life Expectancy", 
         x = "GDP Per Capita") +
  scale_x_log10() +
  guides(scale = FALSE)

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

The above plot between gdp per capita and the life expectancy can be read as per below:

• The blue color legend shows the increase of years from 1952 to early 2007,from darker blue to the lighter blue.
• The size of the dots shows the population of the country, the bigger the dot the higher is the population.
• We can see from the plot that GDP Per Capita has been increased gradually over the years for the world.
• The bigger dots indicated that the gdp percapita for the large population is always on the lower side.