# 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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## ✖ 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
## Loading required package: viridisLite
## 
## `modelsummary` 2.0.0 now uses `tinytable` as its default table-drawing
##   backend. Learn more at: https://vincentarelbundock.github.io/tinytable/
## 
## Revert to `kableExtra` for one session:
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##   options(modelsummary_factory_latex = 'kableExtra')
##   options(modelsummary_factory_html = 'kableExtra')
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##   config_modelsummary(startup_message = FALSE)
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View(gapminder)
gapminder_Austria <- gapminder %>% filter(country == 'Austria')
head(gapminder_Austria)
## # A tibble: 6 × 6
##   country continent  year lifeExp     pop gdpPercap
##   <fct>   <fct>     <int>   <dbl>   <int>     <dbl>
## 1 Austria Europe     1952    66.8 6927772     6137.
## 2 Austria Europe     1957    67.5 6965860     8843.
## 3 Austria Europe     1962    69.5 7129864    10751.
## 4 Austria Europe     1967    70.1 7376998    12835.
## 5 Austria Europe     1972    70.6 7544201    16662.
## 6 Austria Europe     1977    72.2 7568430    19749.
ggplot(gapminder_Austria, aes(x = year, y = gdpPercap)) + geom_point(aes(color = 'maroon'), alpha = 1) + labs(title = 'GPD per capita vs. Year, Austria', x = 'Year', y = 'GDP per capita')

# Positive correlation between GDP per capita and years for Austria

print('i did it?')
## [1] "i did it?"