BDSI GGPlot Workshop

Load in packages and data

library(paletteer)
library(ggplot2)
library(gapminder)
library(tidyverse)

Example 1

gapminder %>% 
  filter(
    year %in% c(1952, 2007)
  ) %>% 
  ggplot() +
  aes(x = gdpPercap) +
  aes(y = lifeExp) +
  geom_point() +
  aes(color = continent) +
  aes(size = pop) +
  facet_wrap(vars(year),
             nrow = 2)

Example 2

gapminder %>% 
  filter(year == 2007) %>% 
ggplot()+
  aes(x=gdpPercap,
      y=lifeExp,
      shape=continent)+
  geom_point()

Geom_histogram

gapminder %>% 
  filter(year == 1952) %>% 
  ggplot()+
  aes(x=lifeExp,
      fill=continent)+
  geom_histogram(alpha=0.5)

## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

geom_boxplot

gapminder %>% 
  filter(year == 1952,
         continent !='Oceania') %>% 
  ggplot()+
  aes(x=lifeExp,
      fill=continent)+
  geom_boxplot(alpha=0.2)

geom_contour

gapminder %>% 
  ggplot()+
  aes(x=year,
      y=lifeExp,
      group=country)+
  geom_smooth(
    method = 'lm',
    se = FALSE
  )

## `geom_smooth()` using formula = 'y ~ x'

Change across time

compere trends in per capita GDP over time by continent

gapminder %>% 
  ggplot()+
  aes(x=year,
      y=gdpPercap,
      color=continent)+
  geom_smooth(se=FALSE)

## `geom_smooth()` using method = 'loess' and formula = 'y ~ x'

gapminder %>% 
  filter(year==2007) %>% 
  group_by(continent) %>%
  summarise(count=n()) %>% 
  ggplot()+
  aes(x=continent,
      y=count,
      fill=continent)+
  geom_col()

Column Charts for Multiple Groups

Life exp for each continent for years 1952-2007

gapminder %>% 
  filter(year %in% c(1957,2007)) %>% 
  group_by(continent,year) %>% 
  summarise(avgLife = mean(lifeExp)) %>% 
  ggplot()+
  aes(x=continent,
      y=avgLife,
      fill=factor(year))+
  geom_col(position='dodge')

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

Customizing Colors

p = gapminder %>% 
  filter(country == 'United States', year > 1990) %>% 
  ggplot()+
  aes(gdpPercap, lifeExp)+
  geom_point()

p=p+aes(color=factor(year))

p=p+scale_color_manual(
  values = 
    c('1992'='blue',
      '1997'='red',
      '2002'='orange',
      '2007'='yellow')
  )+
  theme_minimal()
p

Palatteer

# scale_colour_paletteer_d("nationalparkcolors::Acadia")
# scale_color_paletteer_d("nationalparkcolors::Acadia")
# scale_fill_paletteer_d("nationalparkcolors::Acadia")
# paletteer_d("nationalparkcolors::Acadia")

gapminder %>%
 filter(year==2007) %>%
 group_by(continent) %>%
 summarise(count=n()) %>%
 ggplot()+
 aes(x=continent,
     y=count,
     fill=continent)+
 geom_col()+
 scale_fill_paletteer_d("nationalparkcolors::Acadia") +
 labs(x = NULL, y = NULL) +
 theme_minimal()