Programming homework 2

Insert a code block and then answer each question below. If your code returns something less than a specific answer (e.g. if the question asks for a country but your code returns a table), then include a sentence or two below that gives a precise answer to the question.

library(tidyverse)

## Warning: package 'ggplot2' was built under R version 4.4.3

## Warning: package 'tibble' was built under R version 4.4.3

## Warning: package 'tidyr' was built under R version 4.4.3

## Warning: package 'readr' was built under R version 4.4.3

## Warning: package 'purrr' was built under R version 4.4.3

## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.4     ✔ readr     2.1.6
## ✔ forcats   1.0.1     ✔ stringr   1.6.0
## ✔ ggplot2   4.0.1     ✔ tibble    3.3.1
## ✔ lubridate 1.9.4     ✔ tidyr     1.3.2
## ✔ purrr     1.2.1     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(gapminder)
gapminder

Which Asian country had the lowest life expectancy in 1952?

gapminder %>%
  filter(year == 1952) %>%
  filter(continent == "Asia") %>%
  arrange(lifeExp)

Afghanistan had the lowest life expectancy of the Asian countries in 1952.

Using the mutate() function, make a new variable that is 1 if life expectancy is higher than 60 and 0 otherwise. Save the results into a new tibble.

gapminder %>%
  mutate(life60 = lifeExp > 60) %>%
  mutate(life60 = life60 * 1)

What fraction of countries had a life expectancy over 60 in 1992?

gapminder %>%
  filter(year == 1992) %>%
  summarise(total_countries = n(), countries_above_60 = sum(lifeExp > 60),fraction = countries_above_60 / total_countries)

What fraction of all countries had a life expectancy over 60 in each continent in each of the time periods? Note that you can group_by() more than one variable at a time. Save the results into a new tibble.

lifeover60 <- gapminder %>%
  group_by(continent, year) %>%
  summarise(total_countries = n(), countries_above_60 = sum(lifeExp > 60),fraction = countries_above_60 / total_countries)

## `summarise()` has grouped output by 'continent'. You can override using the
## `.groups` argument.

Using the new tibble you saved in question 4 and ggplot(), make a line plot that shows fraction of countries with a life expectancy over 60 in each continent over time. Try to make the graph look good (proper axis labels, perhaps a different theme).

lifeover60 %>%
  ggplot(aes(x = year, y = countries_above_60, colour = continent, size = countries_above_60)) +
  geom_point()+
  labs(x = "Years", y = "# of Countries With LifeExp > 60" )

Programming homework 2

IDEV 3400

Ryan Briggs