TimTeaFan

reveal_door <- function(doors) {

  if ("car" %in% names(doors)) {
    return(doors[names(doors) != "car"])
  }

  sample(doors, size = 1)
}

play_monty_hall <- function(switch_doors = FALSE) {

TimTeaFan

``` r
library(tidyverse)

indep_vars <- c("vs", "am", "gear", "carb")

dep_vars <- c("mpg", "disp", "hp")

init_grid <- tibble(dep_var = dep_vars,
               indep_vars = list(indep_vars))

TimTeaFan

library(dplyr)

mtcars %>% 
  nest_by(gear) %>% 
  mutate(freq = rlang::list2(
    "gear_{gear}_carb" := table(data$carb)
  )) %>% 
  pull(freq)

#> $gear_3_carb

TimTeaFan

library(tidyverse)

set.seed(123)

# some random dataa
my_dat <- tibble(
  y = rbinom(300, 1, 0.5), # outcome 1
  z = rbinom(300, 1, 0.5), # outcome 2
  t = rbinom(300, 1, 0.5), # outcome 3
  indep_var = runif(300), # this is our independet variable

TimTeaFan

library(tidyverse)
library(gapminder)

# lists of independent variables
indep_var_country <- list(
  "gdp_only" = "gdpPercap",
  "gdp_and_pop"  = c("pop", "gdpPercap")
  )

indep_var_continent <- append(

TimTeaFan

# this reduce() and done() combo mimics a while loop
# coming from this tweet
# https://twitter.com/norimitsunishi1/status/1554353454360932353?s=21&t=lopKMBKt-SKQfOlrM5B_Iw
# of course this is NOT a good solution, since the input to reduce has a limited length, ...
# ... whereas the while loop will just go on forever until it breaks.

library(purrr)

f <- function(char, char2) {
  

TimTeaFan

library(dplyr)

# Add Total Mean for numeric variables
iris %>%
  add_row(
    summarise(.,
      Species = "Total mean",
      across(where(is.numeric), mean))
  ) %>%
  tail() # for printing

TimTeaFan

seq_sum <- function(from, to, .sum, exact = FALSE) {
  
  a <- from + to
  m <- a/2
  d <- .sum - a 
  if (exact && (d %% m !=0)) {
    stop("sequence didn't converge.")
  }
  i <- (d / m) + 2

TimTeaFan

library(dplyr)

set.seed(123)

dat <- tibble(main_grp = rep(c("a", "b"), each = 4),
              sub_grp = rep(c("x", "y"), 4),
              value = rnorm(8))

dat %>% 
  bind_rows(., mutate(dat, sub_grp = "subtotal")) %>%

TimTeaFan

library(tidyverse)

contains_comma <- function(x) {
  if (is.character(x) || is.factor(x)) {
    any(str_detect(x, ","))  
  } else {FALSE}
}

gss_cat %>%
  select(where(contains_comma))