Common Code 01 — Libraries
Every package used in this course, grouped by purpose
packages
setup
Every R package used in the course, grouped by purpose, with a one-time install script so you never re-run install.packages() by accident.
Package Reference
This page lists every R package used in this course, organised from beginner essentials through to advanced methods. Install each group once using the code blocks below — you only ever need to run install.packages() one time per machine. After that, load only the packages you need for a given session with library().
⬇️ Download the full install script — copy it into your
scripts/folder and run it once:install_packages.R
⚠️ Watch out! Never put
install.packages()inside a script you run regularly. Installation only needs to happen once. Putting it in a regular script re-downloads the package every time, which is slow and can break things.
1 · Core Workflow
These are the packages you will load in almost every analysis. Install them first.
install.packages("tidyverse") # dplyr, ggplot2, tidyr, purrr,
# readr, stringr, forcats
install.packages("lubridate") # working with dates and times
install.packages("readxl") # read Excel (.xlsx /
# .xls) files into R
install.packages("writexl") # write data frames
# back out to Excel
install.packages("janitor") # clean messy column
# names and tabulate data
install.packages("skimr") # quick, readable
# summary statistics
install.packages("glue") # paste strings together cleanly
# with {variable} syntax
install.packages("devtools") # install packages from
# GitHub and other sources
install.packages("remotes") # lighter alternative to
# devtools for GitHub installsWhat you load each session
library(tidyverse) # loads dplyr, ggplot2, tidyr,
# readr, purrr, stringr, forcats
library(lubridate) # date / time helpers
library(readxl) # read Excel files
library(janitor) # clean_names() and tabyl()
library(skimr) # skim() for quick summaries2 · Plotting
Core plotting extensions
ggplot2 is already part of tidyverse. These packages add to it.
install.packages("patchwork") # combine multiple ggplot
# panels into one figure
install.packages("scales") # fine-grained control of axis
# breaks, labels, and colours
install.packages("ggthemes") # extra complete themes
# (Economist,
# FiveThirtyEight, etc.)
install.packages("ggridges") # ridge / joy plots for
# overlapping distributions
install.packages("ggpubr") # publication-ready figures;
# add p-value brackets to plotsColour and style
install.packages("viridis") # perceptually uniform,
# colour-blind-safe palettes
install.packages("ggtext") # render markdown / HTML
# inside plot text and labels
install.packages("showtext") # use Google Fonts and
# custom fonts in ggplot
install.packages("ragg") # fast, high-quality
# PNG/TIFF rendering deviceInteractive and animated plots
install.packages("plotly") # turn any ggplot into an
# interactive HTML figure
install.packages("ggiraph") # add tooltips and click
# interactions to ggplot geoms
install.packages("gganimate") # animate ggplots (requires
# gifski or av for output)
install.packages("gifski") # render gganimate output as GIF
install.packages("av") # render gganimate
# output as MP4 videoSaving and previewing
install.packages("ggview") # preview a plot at exact export
# dimensions before saving3 · Tables
For getting results out of R and into Word documents or HTML pages.
install.packages("flextable") # publication tables that export
# cleanly to Word and PowerPoint
install.packages("gt") # grammar-of-tables: highly
# customisable HTML/PDF tables
install.packages("knitr") # kable() for simple tables
# inside Quarto documents
install.packages("kableExtra") # extend kable() with styling,
# spanning headers, and more
install.packages("tinytable") # minimal, fast tables
# designed for Quarto
install.packages("huxtable") # tables that export to
# Word, LaTeX, and HTML
install.packages("officer") # read and write Word and
# PowerPoint files from R
install.packages("webshot2") # screenshot HTML widgets
# to PNG (required by
# some table packages)
install.packages("pandoc") # R interface to the pandoc
# document converter4 · Data Import and Export
install.packages("readxl") # (already in Core — listed
# again for reference)
install.packages("writexl") # write to Excel without
# Java or other dependencies
install.packages("arrow") # read/write Parquet and Feather
# files; very fast large data
install.packages("duckdb") # run SQL queries on data
# frames and Parquet
# files directly in R5 · Descriptive Statistics
First steps when you have data in hand.
install.packages("skimr") # (already in Core) skim() gives
# a fast distributional overview
install.packages("psych") # describe(), pairs.panels(),
# alpha() for scale reliability
install.packages("Hmisc") # rcorr(), and a
# large collection of
# utility functions
install.packages("moments") # skewness() and kurtosis()
install.packages("FSA") # Dunn test, length-frequency
# analysis, age-bias plots6 · Statistical Tests
General tests
install.packages("car") # Anova() with Type II/III
# SS; leveneTest(); vif()
install.packages("broom") # tidy(), glance(), augment()
# — model output as tibbles
install.packages("emmeans") # estimated marginal means
# and pairwise contrasts
install.packages("multcompView") # compact letter display
# for pairwise comparisons
# NOTE: can mask some dplyr
# functions — load with care
install.packages("Rmisc") # summarySE() for
# mean ± SE tables
install.packages("coin") # exact and permutation-based
# versions of common tests
install.packages("rcompanion") # effect sizes and
# non-parametric summaries
install.packages("pwr") # power analysis for t-tests,
# ANOVA, correlation, chi-square
install.packages("perm") # exact permutation tests7 · ANOVA and Linear Models
install.packages("car") # (already listed) Type II/III
# ANOVA; assumption checks
install.packages("afex") # aov_ez() for factorial
# ANOVA; handles repeated
# measures cleanly
install.packages("emmeans") # (already listed) pairwise
# comparisons after ANOVA
install.packages("multcompView") # (already listed) letter
# displays for post-hoc tests
install.packages("relaimpo") # relative importance
# of predictors in
# multiple regression
install.packages("broom") # (already listed)
# tidy model output8 · Mixed-Effects Models
For nested, repeated-measures, or hierarchical data structures.
install.packages("lme4") # lmer() and glmer() — the
# core mixed-model engine in R
install.packages("lmerTest") # adds p-values to lmer()
# output (Satterthwaite
# degrees of freedom)
install.packages("broom.mixed") # tidy() and glance() for
# lme4 and nlme model objects
install.packages("afex") # (already listed)
# mixed_() wrapper for
# factorial mixed models
install.packages("emmeans") # (already listed)
# contrasts and marginal
# means for mixed models
install.packages("performance") # R², ICC, and check_model()
# diagnostic plots
install.packages("see") # visualisation companion
# to performance
install.packages("sjPlot") # plot_model() for fixed/random
# effects; tab_model() tables9 · Generalised Linear Models
For count data, proportions, binary outcomes, and zero-inflated responses.
install.packages("car") # (already listed) Anova()
# works for GLMs too
install.packages("broom") # (already listed)
# tidy GLM output
install.packages("emmeans") # (already listed) marginal
# means on the response scale
install.packages("pscl") # zero-inflated Poisson and
# negative-binomial GLMs
install.packages("DHARMa") # residual diagnostics for GLMs
# and GLMMs via simulation
install.packages("ResourceSelection") # Hosmer-Lemeshow
# goodness-of-fit for
# logistic regression
install.packages("faraway") # datasets and functions from
# Faraway's GLM textbook10 · Model Visualisation and Comparison
install.packages("dotwhisker") # dot-and-whisker coefficient
# plots for regression models
install.packages("ggfortify") # autoplot() for lm, glm,
# PCA, time-series objects
install.packages("interactions") # interact_plot() and cat_plot()
# for interaction effects
install.packages("performance") # (already listed) compare
# model fit, check assumptions
install.packages("see") # (already listed) plots
# for performance outputs
install.packages("sensemakr") # sensitivity analysis for
# unmeasured confounding11 · Correlation and Multivariate
install.packages("corrplot") # visualise correlation matrices
# as coloured grids or circles
install.packages("GGally") # ggpairs() scatterplot matrix;
# ggcoef() coefficient plots
install.packages("psych") # (already listed) polychoric
# / tetrachoric correlations
install.packages("FactoMineR") # PCA, CA, MCA — full-featured
# multivariate methods
install.packages("factoextra") # ggplot-based biplots and scree
# plots for FactoMineR / prcomp12 · Community Ecology and Multivariate Ordination
install.packages("vegan") # NMDS, PERMANOVA (adonis2),
# diversity indices, ordination
install.packages("RVAideMemoire") # pairwise PERMANOVA and
# other ecology helpers
install.packages("pairwiseAdonis") # pairwise adonis2
# (CRAN version)The GitHub development version of pairwiseAdonis is more up to date:
devtools::install_github(
"pmartinezarbizu/pairwiseAdonis/pairwiseAdonis")13 · Maps and Spatial Data
install.packages("sf") # simple features: the standard
# for vector spatial data in R
install.packages("tigris") # download US Census TIGER
# shapefiles (states,
# counties, roads)
install.packages("rnaturalearth") # world country, coastline,
# and graticule shapefiles
install.packages("osmdata") # download OpenStreetMap
# features (roads,
# buildings, waterways)
install.packages("ggfx") # blur, shadow, and glow
# effects on ggplot layersFor 3D terrain rendering:
install.packages(c("rayshader", "elevatr", "raster"))
# rayshader — render elevation data
# as 3D maps and raytraced scenes
# elevatr — download elevation
# rasters from AWS or OpenTopography
# raster — raster grid operations (legacy
# package; terra is the modern replacement)14 · Teaching Datasets
Clean, well-documented datasets used in examples throughout the course.
install.packages("palmerpenguins") # Palmer Archipelago
# penguin data — a tidy
# alternative to iris
install.packages("nycflights13") # 336,776 flights departing
# New York City in 2013
install.packages("Lahman") # Sean Lahman's complete
# baseball statistics database
install.packages("babynames") # US baby name counts and
# proportions, 1880–2017
install.packages("repurrrsive") # nested list datasets for
# learning purrr and iteration15 · Reporting and Workflow
install.packages("htmlwidgets") # embed interactive HTML
# widgets in Quarto documents
install.packages("htmltools") # build and manipulate
# HTML output from RFull install script
The block below installs everything in one go. Paste it into the Console (not a script) and run it once. Expect this to take 10–20 minutes the first time.
# ── CORE ───────────────────────────────────────────────────────
install.packages(c(
"tidyverse", "lubridate", "readxl", "writexl",
"janitor", "skimr", "glue", "devtools", "remotes"
))
# ── PLOTTING ───────────────────────────────────────────────────
install.packages(c(
"patchwork", "scales", "ggthemes", "ggridges", "ggpubr",
"viridis", "ggtext", "showtext", "ragg",
"plotly", "ggiraph", "gganimate", "gifski", "av",
"ggview", "camcorder", "ggThemeAssist", "styler"
))
# ── TABLES ─────────────────────────────────────────────────────
install.packages(c(
"flextable", "gt", "knitr", "kableExtra",
"tinytable", "huxtable", "officer", "webshot2", "pandoc"
))
# ── DATA ───────────────────────────────────────────────────────
install.packages(c("arrow", "duckdb"))
# ── DESCRIPTIVE STATS ──────────────────────────────────────────
install.packages(c("psych", "Hmisc", "moments", "FSA"))
# ── STATISTICAL TESTS ──────────────────────────────────────────
install.packages(c(
"car", "broom", "emmeans", "multcompView",
"Rmisc", "coin", "rcompanion", "pwr", "perm"
))
# ── ANOVA & LINEAR MODELS ──────────────────────────────────────
install.packages(c("afex", "relaimpo"))
# ── MIXED MODELS ───────────────────────────────────────────────
install.packages(c(
"lme4", "lmerTest", "broom.mixed",
"performance", "see", "sjPlot"
))
# ── GLMS ───────────────────────────────────────────────────────
install.packages(c(
"pscl", "DHARMa", "ResourceSelection", "faraway"
))
# ── MODEL VISUALISATION ────────────────────────────────────────
install.packages(c(
"dotwhisker", "ggfortify", "interactions", "sensemakr"
))
# ── MULTIVARIATE ───────────────────────────────────────────────
install.packages(c(
"corrplot", "GGally", "FactoMineR", "factoextra",
"vegan", "RVAideMemoire", "pairwiseAdonis"
))
devtools::install_github(
"pmartinezarbizu/pairwiseAdonis/pairwiseAdonis")
# ── MAPS ───────────────────────────────────────────────────────
install.packages(c(
"sf", "tigris", "rnaturalearth", "osmdata", "ggfx",
"rayshader", "elevatr", "raster"
))
# ── TEACHING DATASETS ──────────────────────────────────────────
install.packages(c(
"palmerpenguins", "nycflights13", "Lahman", "babynames",
"repurrrsive"
))
# ── REPORTING ──────────────────────────────────────────────────
install.packages(c("htmlwidgets", "htmltools"))End of Common Code 01 — Libraries.
Next: Common Code 02 — Reading and writing files.