3.1 - ggplot Introduction

package skimr to quickly view data: skim(data.name)


3 Components of Graphic

  • data: dataset containing variables of interest

  • geom: geometric object in question (what we can observe in plot - points, lines, bars)

  • aes: aesthetic attributes (x/y position, color, shape, size) which are mapped to variables in dataset


Mapping argument defines how variables are mapped to aesthetics of the plot. It is always defined in aes(), and x and y arguments of aes() specify which variables to map to x/y axes


define geom: geometrical object that plot uses to represent data starts with geom_ 

  • geom_bar(), geom_line(), geom_point(), geom_boxplot, geom_violin()

  • ggplot(data = DATA, mapping = aes(global mappings)) + geom_TYPE(args) 


Adding Color and Linear Regression

geom_smooth(method = “lm”, se = FALSE) 

lm is for linear regression 

se = FALSE removes banded confidence interval around line of best fit 


Global and Local Mappings

ggplot(data = DATA, mapping = aes(global mappings)) + geom_()

vs 

ggplot(data = DATA, mapping = aes(global mappings)) + geom_(mapping = aes(local mappings))
which is helpful when adding colors, shapes, lines to graph


Labels (within labs() layer) 

  • title = “main" title”

  • subtitle = “sub text” 

  • x = “x label”

  • y = “y label” 


Themes

r + theme_classic()