malcolmbarrett

# measure the average number of steps a random walker takes in two
# dimensions to return to origin for the first time by simulating
# the random walk multiple times.
library(tidyverse)

# walk through an integer grid one step at a time
# report the number of steps on first return to the origin
steps_on_first_return <- function(max_steps = 10000L) {
  x <- 0L
  y <- 0L

malcolmbarrett

plot_data <- data_observed |> 
  select(starts_with("y"), exposure) |> 
  mutate(id = row_number()) |> 
  pivot_longer(
    starts_with("y"),
    names_prefix = "y_",
    names_to = "potential_outcome",
    values_to = "happiness"
  ) |> 
  mutate(

malcolmbarrett

#set.seed(123) # Set seed for reproducibility

library(tidymodels)

fit_models <- function(n = 100) {
  # Step 2: Create 10 predictors, some of which are noisy or highly correlated
  x1 <- rnorm(n)
  x2 <- rnorm(n)
  x3 <- rnorm(n)
  x4 <- rnorm(n)

malcolmbarrett

---
title: "Untitled"
format: html
jupyter: python3
---

```{python}
#| label: setup
#| include: false
import pandas as pd

malcolmbarrett

# or use Posit Cloud https://posit.cloud/content/5749861
quarto.workshop::use_module("quarto_whole_game")

# or use Posit Cloud https://posit.cloud/content/5749854
quarto.workshop::use_module("quarto_basics")

# or use Posit Cloud https://posit.cloud/content/5890555
quarto.workshop::use_module("quarto_tables")

# or use Posit Cloud https://posit.cloud/content/5890550

malcolmbarrett

# `letters` contains the 26 letters of the English alphabet
# data.frames will recycle `letters` twice to match the length of `a` (52)
data.frame(
  a = 1:52,
  b = letters
)
#>     a b
#> 1   1 a
#> 2   2 b

malcolmbarrett

rhc <- readr::read_csv("https://biostat.app.vumc.org/wiki/pub/Main/DataSets/rhc.csv")
rhc$swang1 <- factor(rhc$swang1, levels = c("No RHC", "RHC"))

psModel <- glm(
  formula = swang1 ~ age + sex + race + edu + income + ninsclas +
    cat1 + das2d3pc + dnr1 + ca + surv2md1 + aps1 + scoma1 +
    wtkilo1 + temp1 + meanbp1 + resp1 + hrt1 + pafi1 +
    paco21 + ph1 + wblc1 + hema1 + sod1 + pot1 + crea1 +
    bili1 + alb1 + resp + card + neuro + gastr + renal +
    meta + hema + seps + trauma + ortho + cardiohx + chfhx +

malcolmbarrett

# Hello,
# Can anyone help me: I want just to have line plot but when I plot it looks like so as it is indicated in the picture. I am using the following code:

# Plot the 7th graph for Google mobility. Recreation & Retail
USAMobility <- USAMobility  %>% 
  dplyr::mutate(date=dmy(j))


PLOT7 <- USAMobility  %>%
  ggplot(aes(x=date, y=retail_and_recreation_percent_change_from_baseline)) +

malcolmbarrett

{
    "panes": {
        "quadrants": [
            "Source",
            "Console",
            "TabSet1",
            "TabSet2"
        ],
        "tabSet1": [
            "Environment",

malcolmbarrett

use_custom_build <- function(file) {
  stopifnot(file_exists(file))
  
  build_pane_active <- has_buildtype()
  bail_out <- check_buildtype()
  if (bail_out) {
    return(invisible(NULL))
  }
  
  file_chmod(file, "+x")