ggplot2: Aesthetics

gg_aesthetics.R

# install
install.packages('ggplot2')
install.packages('dplyr')
install.packages('tidyr')
install.packages('readr')

# library
library(ggplot2)
library(dplyr)
library(tidyr)
library(readr)

# read data
ecom <- readr::read_csv('https://raw.githubusercontent.com/rsquaredacademy/datasets/master/web.csv')
ecom

# Map Color to Variable
ggplot(mtcars, aes(x = disp, y = mpg, color = factor(cyl))) +
  geom_point()

# Map Color to Variable
ggplot(mtcars, aes(x = disp, y = mpg)) +
  geom_point(aes(color = factor(cyl)))

# Color: Specify Value
ggplot(mtcars, aes(x = disp, y = mpg)) +
  geom_point(color = 'blue')

# Map Shape to Variable
ggplot(mtcars, aes(x = disp, y = mpg, shape = factor(cyl))) +
  geom_point()

# Map Shape to Variable
ggplot(mtcars, aes(x = disp, y = mpg)) +
  geom_point(aes(shape = factor(cyl)))

# Shape: Specify Value
ggplot(mtcars, aes(x = disp, y = mpg)) +
  geom_point(shape = 5)

# Shape & Color
ggplot(mtcars, aes(x = disp, y = mpg)) +
  geom_point(shape = 5, color = 'blue')

# Fill
ggplot(mtcars, aes(x = disp, y = mpg)) +
  geom_point(shape = 5, fill = 'blue')

# Fill: Specify Value
ggplot(mtcars, aes(x = disp, y = mpg)) +
  geom_point(shape = 22, fill = 'blue')

# Geom Border Color
ggplot(mtcars, aes(x = disp, y = mpg)) +
  geom_point(shape = 22, color = 'blue')

# Map Size to Variable (Continuous)
ggplot(mtcars, aes(x = disp, y = mpg, size = disp)) +
  geom_point()

# Specify Size Value
ggplot(mtcars, aes(x = disp, y = mpg)) +
  geom_point(size = 4)

# Map Alpha to Variable
ggplot(mtcars, aes(x = disp, y = mpg)) +
  geom_point(aes(alpha = factor(cyl)), color = 'blue')

# data
gdp <- readr::read_csv('https://raw.githubusercontent.com/rsquaredacademy/datasets/master/gdp.csv')
gdp

# Line Color
ggplot(gdp, aes(year, india)) +
  geom_line(color = 'blue')

# Line Type
ggplot(gdp, aes(year, india)) +
  geom_line(linetype = 2)

# Line Type
ggplot(gdp, aes(year, india)) +
  geom_line(linetype = 'dashed')

# Line Width
ggplot(gdp, aes(year, india)) +
  geom_line(size = 2)

# data
gdp2 <- gdp %>% 
  select(year, growth, india, china) %>% 
  gather(key = country, value = gdp, -year)

gdp2

# Grouped Line Chart
ggplot(gdp2, aes(year, gdp, group = country)) +
  geom_line()

# Map Line Color to Country
ggplot(gdp2, aes(year, gdp, group = country)) +
  geom_line(aes(color = country))

# Map Line Type to Country
ggplot(gdp2, aes(year, gdp, group = country)) +
  geom_line(aes(linetype = country))

# Map Line Width to Country
ggplot(gdp2, aes(year, gdp, group = country)) +
  geom_line(aes(size = country))

# Map Bar Color to Purchase
ggplot(ecom, aes(device, fill = purchase)) +
  geom_bar()

# Map Histogram Color to Purchase
ggplot(ecom) +
  geom_histogram(aes(duration, fill = purchase), bins = 10)

# Map Box Plot Color to Purchase
ggplot(ecom) +
  geom_boxplot(aes(device, duration, fill = purchase))