andrewheiss

library(tidyverse)
library(marginaleffects)
library(gapminder)

gapminder_2007 <- gapminder |> 
  filter(year == 2007)

# Use log() in the model formula
model <- lm(lifeExp ~ log(gdpPercap), data = gapminder_2007)

andrewheiss

library(tidyverse)
library(mlogit)
library(dfidx)
library(marginaleffects)

chocolate <- read_csv("https://www.andrewheiss.com/blog/2023/08/12/conjoint-multilevel-multinomial-guide/data/choco_candy.csv") %>% 
  mutate(
    dark = case_match(dark, 0 ~ "Milk", 1 ~ "Dark"),
    dark = factor(dark, levels = c("Milk", "Dark")),

andrewheiss

library(tidyverse)
library(palmerpenguins)

penguins <- penguins |> drop_na()

# This splits the dataset into three smaller datasets behind the scenes, but
# then doesn't do anything with them. But secretly it's waiting to do things
# within the three groups (hence the "Groups: species [3]") note
penguins |> 

andrewheiss

library(tidyverse)
library(tinytable)

inline_listify <- function(x) {
  numbers <- seq_along(x)
  prefixed <- paste0("(", numbers, ") ", x)
  collapsed <- paste(prefixed, collapse = "; ")
  return(collapsed)
}

andrewheiss

library(tidyverse)
library(broom)

model1 <- lm(hwy ~ displ + cyl, data = mpg)
model2 <- lm(hwy ~ displ + cyl + drv, data = mpg)

plot_data <- bind_rows(
  tidy(model1, conf.int = TRUE) |> mutate(model = "Model 1"),
 tidy(model2, conf.int = TRUE) |&gt; mutate(model = "Model 2")

andrewheiss

library(tidyverse)
library(gapminder)

# ifelse() will happily work and coerce your numbers into text
gapminder1 <- gapminder |> 
  mutate(life_cat = ifelse(lifeExp > 75, "High", lifeExp))

# if_else() will yell at you
gapminder1 <- gapminder |> 
  mutate(life_cat = if_else(lifeExp > 75, "High", lifeExp))

andrewheiss

---
- hosts: ubuntu
  become: yes
  tasks:
    - name: Add a new user named 'yourname'
      user:
        name: yourname
        state: present

    - name: Add 'yourname' to sudo group

andrewheiss

library(tidyverse)

example_draws <- tribble(
  ~category, ~shapes,
  FALSE,     c(10, 10, 13),
  TRUE,      c(7, 7, 8)
) |> 
  mutate(draws = map(shapes, ~{
    withr::with_seed(1234, {

andrewheiss

library(tidyverse)
library(broom)
library(marginaleffects)
library(palmerpenguins)

penguins <- penguins %>% drop_na(sex)

model1 <- lm(body_mass_g ~ flipper_length_mm + species, data = penguins)

andrewheiss

library(tidyverse)
library(lme4)
library(marginaleffects)

# ?ChickWeight
# weight = body weight in grams
# Time = days since birth
# Chick = chick ID
# Diet = one of 4 possible diets