elipousson

#' Documentation of sf and tidyverse compatibility
#'
#' date-created: 2023-12-15
#' date-modified: 2024-10-30
# Notes to add to https://geocompr.r-universe.dev/articles/geocompkg/tidyverse-pitfalls.html

library(sf)
library(tidyverse)

nc = st_read(system.file("shape/nc.shp", package="sf"))

elipousson

---
title: "GES668: Your Project Title"
author: "Your Name"
format: revealjs
---

## Using this template

:::{.callout-tip collapse=false appearance='default' icon=true}
## How to use this template

elipousson

library(getACS)
library(tidycensus)
commute_time <- tidycensus::get_acs(
  geography = "county",
  table = "B08136",
  year = 2021,
  survey = "acs5",
  state = "MD",
  cache = TRUE
)

elipousson

---
title: "gt table list multi-format knit"
format: 
  html: default
  pdf: default
---

```{r}
library(gt)
nested_mtcars <- dplyr::nest_by(mtcars, cyl, .keep = TRUE)

elipousson

`%||%` <- function(x, y) {
  if (rlang::is_null(x)) {
    y
  } else {
    x
  }
}

# Quarto extension functions are based on the quartools package:
# https://github.com/ElianHugh/quartools/

elipousson

# title: R script for validating Baltimore city bike facility data, updating the
# schema to match new BMC standard, and adding new attributes for responsible
# agency and other characteristics
#
# author: Eli Pousson
# date: 2023-09-07
# last-modified: 2023-11-16

# Set up ----

elipousson

library(getACS)
library(tidyverse)

vehicle_access_acs <- get_acs_tables(
  "tract",
  table = "B08201",
  county = "Baltimore city",
  state = "MD"
)

elipousson

# Get zoning metadata from {mapmaryland}
baltimore_zoning_info <- dplyr::filter(
  mapmaryland::md_zoning_info,
  county == stringr::str_remove(map_params$county_name, ", Maryland$")
)


# Create format function with custom colors ----

zoning_colors <- tibble::tribble(

elipousson

# Install packages if needed
# install.packages(c("skimr", "spData", "tidyverse", "sf", "gt"))

# Load packages
library(spData)
library(tidyverse)
library(sf)
library(gt)

# Set a default ggplot2 theme

elipousson

# This is a cleaned up version of your original function
area_square_km <- function(data, ...) {
  data |> 
  dplyr::mutate(
    dplyr::across(
      dplyr::all_of(...),
      ~ .x / 1000000
    )
  )
}