Midterm 2 Codes

Core Tidyverse Packages

readr, dplyr, ggplot2, tidyr, lubridate: The primary collection of packages for importing, transforming, and visualizing tidy data.

| > and %>%

|> (Native Pipe) or %>% (Magrittr Pipe): Used to chain commands by inserting the left-hand object as the first argument of the right-hand function.

Tibble

A modern data frame that features enhanced printing and stricter behavior.

filter()

Selects rows based on specific conditions.

select()

Extracts specific columns or variables.

contains()

A helper for select() to find columns matching specific text.

mutate()

Creates new columns that are functions of existing ones.

arrange()

Sorts rows, often paired with desc() for descending order.

group_by()

Groups data for pooled calculations.

summarize()

Aggregates many rows into a single summary value.

ggplot()

Initializes a plot using the Grammar of Graphics.

aes()

Maps data variables to visual properties like color, size, or shape.

geom_point()

Layer for creating scatterplots.

geom_line()

Layer for creating line plots.

geom_histogram()

Layer for creating histograms.

geom_density()

Layer for creating density plots.

facet_wrap()

Creates side-by-side graphs for easier categorical comparison.

scale_x_continuous()

Customizes axes, e.g., applying a log transformation.

data.frame()

Creates a standard data structure in Base R.

nrow()

Counts the number of rows in a dataset.

mean()

Calculates the average of a numeric vector.

lm()

Fits linear regression models using the syntax Response ~ Predictor.

cor()

Calculates correlation coefficients ($r$).

plot()

The standard base function for creating scatterplots.

logit()

Specialized transformation for percentages/proportions.

options(scipen = 999)

Disables scientific notation for p-values.