url <- "https://geodata.md.gov/imap/rest/services/Transportation/MD_Transit/FeatureServer/9"
meta <- esri2sf::esrimeta(url)
meta_comparison <- arcgislayers::arc_open(url) |>
unclass()
length(meta)
#> [1] 55
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library(dplyr) | |
library(rlang) | |
library(purrr) | |
# library(d2r) | |
library(minixcali) | |
path <- "Untitled-2024-03-28-1327.excalidraw" | |
file <- xkd_read(path, simplifyVector = TRUE) |
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@prefix owl: <http://www.w3.org/2002/07/owl#> . | |
@prefix terms: <http://sample-site/politicalgeography/vocabularies/terms#> . | |
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> . | |
@prefix sharepoint-taxonomy: <http://aka.ms/sp-taxonomy-syntax/> . | |
<http://sample-site/politicalgeography/vocabularies/terms> a owl:Ontology . | |
terms:politicalgeography a sharepoint-taxonomy:TermSet; | |
sharepoint-taxonomy:description "A sample term set, describing a simple political geography."@en-us; | |
sharepoint-taxonomy:termSetName "Political Geography"@en-us; |
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library(marylandedu) | |
library(baltimoreplanning) | |
library(bcpss) | |
library(ggplot2) | |
program_enrollment <- get_md_enrollment( | |
c(164, 159), | |
grade_range = "All Grades", | |
race = "All") |
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--- | |
format: typst | |
--- | |
```{r} | |
library(tinytable) | |
x <- mtcars[1:4, 1:5] | |
``` | |
```{r} |
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vague_dt_interval <- function(start, | |
end = NULL, | |
use_now = TRUE, | |
unit = "second", | |
format = c("default", "short", "terse")) { | |
if (!is.interval(start)) { | |
if (use_now) { | |
end <- end %||% lubridate::now() | |
} |
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library(sf) | |
library(tidyverse) | |
# 2023-12-15 | |
# Notes to add to https://geocompr.r-universe.dev/articles/geocompkg/tidyverse-pitfalls.html | |
nc = st_read(system.file("shape/nc.shp", package="sf")) | |
nc_modified = nc |> | |
mutate( |
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--- | |
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 |
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library(getACS) | |
library(tidycensus) | |
commute_time <- tidycensus::get_acs( | |
geography = "county", | |
table = "B08136", | |
year = 2021, | |
survey = "acs5", | |
state = "MD", | |
cache = TRUE | |
) |
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--- | |
title: "gt table list multi-format knit" | |
format: | |
html: default | |
pdf: default | |
--- | |
```{r} | |
library(gt) | |
nested_mtcars <- dplyr::nest_by(mtcars, cyl, .keep = TRUE) |
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