SOC 252 HW 1 Updated

# List of packages
packages <- c("tidyverse", "gapminder", "fst", "viridis", "ggridges", "modelsummary")

# Install packages if they aren't installed already
new_packages <- packages[!(packages %in% installed.packages()[,"Package"])]
if(length(new_packages)) install.packages(new_packages)

# Load the packages
lapply(packages, library, character.only = TRUE)

## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
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## ✔ forcats   1.0.0     ✔ stringr   1.5.1
## ✔ ggplot2   3.5.1     ✔ tibble    3.2.1
## ✔ lubridate 1.9.3     ✔ tidyr     1.3.1
## ✔ purrr     1.0.2     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
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## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
## 载入需要的程序包：viridisLite
## 
## `modelsummary` 2.0.0 now uses `tinytable` as its default table-drawing
##   backend. Learn more at: https://vincentarelbundock.github.io/tinytable/
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## Revert to `kableExtra` for one session:
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##   options(modelsummary_factory_default = 'kableExtra')
##   options(modelsummary_factory_latex = 'kableExtra')
##   options(modelsummary_factory_html = 'kableExtra')
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##   config_modelsummary(startup_message = FALSE)

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## [11] "purrr"        "readr"        "tidyr"        "tibble"       "ggplot2"     
## [16] "tidyverse"    "stats"        "graphics"     "grDevices"    "utils"       
## [21] "datasets"     "methods"      "base"

my_variable <- 10
print(my_variable)

## [1] 10

data(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.

gapminder_subset <- gapminder %>% select(country, year, lifeExp, gdpPercap)
head(gapminder_subset)

## # A tibble: 6 × 4
##   country      year lifeExp gdpPercap
##   <fct>       <int>   <dbl>     <dbl>
## 1 Afghanistan  1952    28.8      779.
## 2 Afghanistan  1957    30.3      821.
## 3 Afghanistan  1962    32.0      853.
## 4 Afghanistan  1967    34.0      836.
## 5 Afghanistan  1972    36.1      740.
## 6 Afghanistan  1977    38.4      786.

# Create box plots for life expectancy by continent
ggplot(gapminder, aes(x = continent, y = gdpPercap, fill = continent)) +
  geom_boxplot() + # Create boxplot, fill colors by continent
  labs(title = "GDP by Continent",
       x = "Continent", y = "gdpPercap") + # Add labels and title
  theme_minimal() # Use a minimal theme for a clean look

This visualization presents theGDP per Capita across different continents, illustrating that Africa records the lowest GDP whereas Oceania achieves the highest. The box plot effectively captures these variations, with Asia demonstrating the highest number of outliers in this context.

print('I did it!')

## [1] "I did it!"