This is a title I added
This section shows how to format text I AM BOLD HERE and some in and ITALIC HERE.
Unordered and Numbered Lists are here
Load the gapminder package
library(tidyverse)
library(gapminder)
head(gapminder)
# A tibble: 6 × 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.
Here is an unordered (bulleted) list:
Here is a numbered list (1, 2, 3):
- First
- Second
- Third
Here is an alphabetic list (A, B, C):
A. Alpha
B. Bravo
C. Charlie
Average Life Expectancy per Country
Calculate average life expectancy for each country (across all years)
avg_lifeexp <- gapminder %>%
group_by(country) %>%
summarise(avg_lifeExp = mean(lifeExp))
Show the top 5 countries with highest average life expectancy
avg_lifeexp %>%
arrange(desc(avg_lifeExp)) %>%
head(5)
# A tibble: 5 × 2
country avg_lifeExp
<fct> <dbl>
1 Iceland 76.5
2 Sweden 76.2
3 Norway 75.8
4 Netherlands 75.6
5 Switzerland 75.6
Show the bottom 5 countries with lowest average life expectancy
avg_lifeexp %>%
arrange(avg_lifeExp) %>%
head(5)
# A tibble: 5 × 2
country avg_lifeExp
<fct> <dbl>
1 Sierra Leone 36.8
2 Afghanistan 37.5
3 Angola 37.9
4 Guinea-Bissau 39.2
5 Mozambique 40.4
Life Expectancy Over Time: Afghanistan, Mexico, Sweden
countries <- c("Afghanistan", "Mexico", "Sweden")
Filter and plot
gapminder %>%
filter(country %in% countries) %>%
ggplot(aes(x = year, y = lifeExp, color = country)) +
geom_line(size = 1.2) +
geom_point(size = 2) +
labs(
title = "Life Expectancy Over Time: Afghanistan, Mexico, and Sweden",
x = "Year",
y = "Life Expectancy (years)",
color = "Country"
) +
theme_minimal()
GDP per Capita vs Life Expectancy by Continent
gapminder %>%
ggplot(aes(x = gdpPercap, y = lifeExp, color = continent)) +
geom_point(alpha = 0.6, size = 2) +
scale_x_log10() +
labs(
title = "GDP per Capita vs Life Expectancy by Continent (Minimal Theme)",
x = "GDP per Capita (log scale)",
y = "Life Expectancy (years)",
color = "Continent"
) +
theme_minimal()
gapminder %>%
ggplot(aes(x = gdpPercap, y = lifeExp, color = continent)) +
geom_point(alpha = 0.6, size = 2) +
scale_x_log10() +
labs(
title = "GDP per Capita vs Life Expectancy by Continent (Classic Theme)",
x = "GDP per Capita (log scale)",
y = "Life Expectancy (years)",
color = "Continent"
) +
theme_classic()
Ranking Continents by Life Expectancy: year 1952 vs year 2007
lifeexp_1952 <- gapminder %>%
filter(year == 1952) %>%
group_by(continent) %>%
summarise(mean_lifeExp = mean(lifeExp)) %>%
arrange(desc(mean_lifeExp))
SRanking for 1952
# A tibble: 5 × 2
continent mean_lifeExp
<fct> <dbl>
1 Oceania 69.3
2 Europe 64.4
3 Americas 53.3
4 Asia 46.3
5 Africa 39.1
Average life expectancy per continent for 2007
lifeexp_2007 <- gapminder %>%
filter(year == 2007) %>%
group_by(continent) %>%
summarise(mean_lifeExp = mean(lifeExp)) %>%
arrange(desc(mean_lifeExp))
Ranking for 2007
# A tibble: 5 × 2
continent mean_lifeExp
<fct> <dbl>
1 Oceania 80.7
2 Europe 77.6
3 Americas 73.6
4 Asia 70.7
5 Africa 54.8
