In BAREJAA/reactivity: This package provides a way to generate introductory dplyr and ggplot2 presentations using user-supplied tidy datasets

library(tidyverse)
library(patchwork)

#Load datasets we will use for the lecture
source(here::here("code", "healthcare.R")) #loads dataset-specific variables

Lets take a glimpse at our dataset called heart

Basics of a ggplot code

Below is an example of the most basic form of the ggplot code

ggplot(data)+ #this will generate a blank plot for your data. At this point, ggplot knows what to plot, but not how.
  geom(mapping=aes(x, y)) #adding a geom tells ggplot how you would like to map your data

Take a moment to use this template to make a simple ggplot. The data heart is defined, but you can choose the variables you want to map to x and y. I would recommend using geom_point.

Put your code in the code chunk here, run it by clicking the green arrow.

Compare the code for these two plots

plot1 <- ggplot(heart) +
  geom_point(aes(x = age, y = chol), color = "blue")

plot2 <- ggplot(heart) +
  geom_point(aes(x = age, y = chol, color = sex))

plot1 + plot2

Of the 5 basic aesthetics, 4 can be mapped to variables in your data 1. Color- changes the outline color of your datapoints
2. Size - choose the size of the datapoint
3. Shape - choose a pre-defined shape
4. Alpha- cCANNOT BE MAPPED TO A VARIABLE. 5. Fill- changes the fill color of your points

In this code chunk, take either your plot from above, or the example I provided, and map your variables to the aesthetics. Make sure you map the variable inside the aes().

Curious for more? Map more than two variables to two distinct aesthetics

BAREJAA/reactivity documentation built on April 16, 2020, 6:57 p.m.