TJ Mahr tjmahr

print.file_check_log <- function(x, ...) str(x, ...)
as_file_check_log <- function(x) UseMethod("as_file_check_log")
as_file_check_log.default <- function(x) {
  structure(list(x = x, notes = list()), class = "file_check_log")
}

apply_to_file_check_log <- function(x, fn, ...) {
  results <- fn(x$x, ...)
  l <- list(results)

# Make a csv to read in
db1 <- DBI::dbConnect(duckdb::duckdb())
f <- tempfile("mtcars", fileext = ".csv")
write.csv(mtcars, f)

library(tidyverse)

# Read in the csv.
# Here two column types are hard-coded using a struct

writeLines(
"a\tb\tc\td\te\tf
1\t2\t3\t4\t5\t6\t
1\t2\t3\t4\t5\t6\t7\t
1\t2\t3\t4\t5\t6\t7\t8
1\t2\t3\t4\t5\t6\t7\t8\t9\t10\t11
1\t2\t3\t4\t5\t6

library(faux)
#> 
#> ************
#> Welcome to faux. For support and examples visit:
#> https://debruine.github.io/faux/
#> - Get and set global package options with: faux_options()
#> ************

library(splines)
model <- lm(mpg ~ ns(wt, df = 3), mtcars)

# make and plot a basis
basis <- ns(sort(mtcars$wt), df = 3)
matplot(basis, type = "l")

library(tidyverse)

if (FALSE) {
  # Read in the models and make the tribbles for the demo
  draws_epred_means <- targets::tar_read("draws_epred_means")

x <- rnorm(250, 5, 2)
i <- sample.int(250, 20)

ranks <- rank(x)[i]
percentiles <- ppoints(250)[ranks]
points <- x[i]

f <- function(args, points, percentiles) {
  test_quantiles <- qnorm(percentiles, args[1], args[2])

data <- mtcars
m <- lm(mpg ~ wt, data)

data <- mtcars[-c(1:10), ]
m_update <- update(m, . ~ . + disp)

nobs(m)
#> [1] 32