jnolis

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```{r setup, include=FALSE}
knitr::opts_chunk$set(include = FALSE)
library(gt)

jnolis

# This code generates however many bingo sheets you need
# It requires you to have "squares.csv", a single column csv file with
# name "square" and a row for the text in each square.
#
# You also need to install wkhtmltopdf https://wkhtmltopdf.org/ and
# add it to your system path. This converts the html to a pdf page
# libraries: tidyverse, glue, rmarkdown
#
# Also make a folder "output" to store them to

jnolis

library(ggplot2)
library(ggirl)

# create the plot

plot <- ggplot() +
  geom_polygon( data=map_data("state"), aes(x=long, y=lat, group=group),
                fill="#cdddee", color="#7296bc" )+
  geom_point(data = data.frame(long = -77.01728, lat = 38.78125),
             aes(x=long, y=lat),

jnolis

{
    "name": "usage-reporting-prod",
    "image_uri": "saturncloud/saturn-rstudio:2022.01.06",
    "description": "API endpoint for Saturn Cloud usage hosted with R and plumber",
    "working_directory": "/home/jovyan/usage-reporting",
    "start_script": "Rscript startup.R",
    "git_repositories": [
      {
        "url": "git@github.com:saturncloud/usage-reporting.git",
        "location": "/home/jovyan/usage-reporting",

jnolis

{
  "name": "nvidia-usage-alerting",
  "image_uri": "saturncloud/saturn-r:2021.11.10-2",
  "description": "",
  "environment_variables": {},
  "working_directory": "/home/jovyan/git-repos/nvidia-reporting",
  "start_script": "Rscript reports/alerts.R",
  "git_repositories": [
    {
      "url": "git@github.com:saturncloud/nvidia-reporting.git",

jnolis

{
  "name": "nvidia-reporting-test",
  "image_uri": "saturncloud/saturn-r:2021.11.10-2",
  "description": "",
  "environment_variables": {},
  "working_directory": "/home/jovyan/git-repos/nvidia-reporting",
  "extra_packages": {
    "apt": "unixodbc unixodbc-dev",
    "conda": "",
    "pip": "",

jnolis

library(tidyverse)

data <-
  read_lines("07/input.txt") %>%
  str_split(",") %>%
  .[[1]] %>%
  as.integer()

# part 1
# the optimal location to meet is exactly the median (think L1 space if you're mathy)

jnolis

{
  "name": "embed-recipe-site",
  "image_uri": "saturncloud/saturn-r:2021.11.10-2",
  "description": "A simple website with R and Shiny for embedding recipe links",
  "environment_variables": {},
  "working_directory": "/home/jovyan/git-repos/embed-recipes-site",
  "extra_packages": {
    "use_mamba": true,
    "conda": "",
    "apt": "libv8-dev",

jnolis

library(furrr)
library(dplyr)

future::plan(future::multisession()) # This is for windows, might want something else for Linux

data <- data.frame(letter = sample(letters,num_samples, replace = TRUE),
           value = runif(num_samples))

data %>%
  group_by(letter) %>%

jnolis

library(tidyverse)
library(jsonlite)

x <- tribble(
  ~name, ~city, ~age,
  "Heather", "Renton", 31,
  "Jacqueline", "Issaquah", 34
)

# BAD WAY