psyteachr_ads Ch. 03

geom_point()

{ggplot2}

add layer of points to plot

scale_x_continuous()

{ggplot2}

scale x axis to be continuous

theme()

{ggplot2}

customize non-data components of plot

stat_summary()

{ggplot2}

summarize y values for each x value

geom_smooth()

{ggplot2}

create smoothed lines to plot

lm()

{stats}

fit linear model

geom_col()

{ggplot2}

create bar chart based on values in data

geom_jitter()

{ggplot2}

add layer of jittered points to plot

labs()

{ggplot2}

modify axis, legend, and plot labels

aes()

{ggplot2}

create aesthetic mappings between data and plot

loess()

{stats}

apply local polynomial regression fitting

geom_violin()

{ggplot2}

create violin plot

geom_freqpoly()

{ggplot2}

create frequency polygon

c()

{base}

create vector of numbers, characters, etc.

scale_x_date()

{ggplot2}

scale x axis to be date

as.numeric()

{base}

coerce object to numeric

geom_boxplot()

{ggplot2}

add layer of boxplots to plot

mean()

{base}

calculate mean of elements of vector

factor()

{base}

encode vector as factor

geom_histogram()

{ggplot2}

create histogram of counts as bars

guides()

{ggplot2}

set guides for scale

scale_y_continuous()

{ggplot2}

scale y axis to be continuous

coord_cartesian()

{ggplot2}

use Cartesian coordinates

seq()

{base}

create sequences of numbers

facet_wrap()

{ggplot2}

create subplots from one variable

geom_bar()

{ggplot2}

create bar chart based on counts in data

ggplot()

{ggplot2}

create a plotting area

today()

{lubridate}

return the current date

read_csv()

{readr}

read comma delimited files

n()

{dplyr}

return current group size

now()

{lubridate}

return current date and time

count()

{dplyr}

count unique values of variables

library()

{base}

load R packages

The end!