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^renv$
^renv\.lock$
^data-raw$
^README\.Rmd$
^\.Renviron$
^.*\.Rproj$
^\.Rproj\.user$
^LICENSE\.md$
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Package: urbanindex
Title: Tract-Level Data for the 538 Urban Index
Version: 0.0.0.9000
Authors@R:
person(given = "David",
family = "Aja",
role = c("aut", "cre"),
email = "first.last@example.com")
Description: Tract-level data for the 538 urban index
License: CC0
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.1.0
Depends:
R (>= 2.10)
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## creative commons
# CC0 1.0 Universal
CREATIVE COMMONS CORPORATION IS NOT A LAW FIRM AND DOES NOT PROVIDE LEGAL SERVICES. DISTRIBUTION OF THIS DOCUMENT DOES NOT CREATE AN ATTORNEY-CLIENT RELATIONSHIP. CREATIVE COMMONS PROVIDES THIS INFORMATION ON AN "AS-IS" BASIS. CREATIVE COMMONS MAKES NO WARRANTIES REGARDING THE USE OF THIS DOCUMENT OR THE INFORMATION OR WORKS PROVIDED HEREUNDER, AND DISCLAIMS LIABILITY FOR DAMAGES RESULTING FROM THE USE OF THIS DOCUMENT OR THE INFORMATION OR WORKS PROVIDED HEREUNDER.
### Statement of Purpose
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NAMESPACE 0 → 100644
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# Generated by roxygen2: do not edit by hand
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#' population within five miles of each census tract
#'
#' A dataset containing the population within five miles of each census
#' tract, based on the latest American Community Survey Data
#'
#' @format a data frame with 74001 rows and three columns
#' \describe{
#' \item{GEOID}{an 11-character identifier for the tract}
#' \item{pop_within_5_mi}{the population within five miles of the tract}
#' \item{pop}{population of the tract}
#' }
#' @source \url{https://www.census.gov/programs-surveys/acs/news/data-releases.2018.html}
"pop_within_5_mi"
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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# urbanindex
<!-- badges: start -->
<!-- badges: end -->
calculating the [538 urbanization index](https://fivethirtyeight.com/features/how-urban-or-rural-is-your-state-and-what-does-that-mean-for-the-2020-election/) for each census tract
## inspiration
https://twitter.com/NateSilver538/status/1200498385125433344
## Installation
You can install urbanindex from [github](https://github.com/edavidaja/urbanindex) with:
```{r, eval=FALSE}
remotes::install.packages("edavidaja/urbanindex")
```
## Example
```{r example}
library(urbanindex)
head(pop_within_5_mi)
```
README.md 0 → 100644
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<!-- README.md is generated from README.Rmd. Please edit that file -->
# urbanindex
<!-- badges: start -->
<!-- badges: end -->
calculating the [538 urbanization
index](https://fivethirtyeight.com/features/how-urban-or-rural-is-your-state-and-what-does-that-mean-for-the-2020-election/)
for each census tract
## inspiration
<https://twitter.com/NateSilver538/status/1200498385125433344>
## Installation
You can install urbanindex from
[github](https://github.com/edavidaja/urbanindex) with:
``` r
remotes::install.packages("edavidaja/urbanindex")
```
## Example
``` r
library(urbanindex)
head(pop_within_5_mi)
#> GEOID pop_within_5_mi
#> 1 01001020100 3609.263
#> 2 01001020200 3518.769
#> 3 01001020300 3794.940
#> 4 01001020400 4051.639
#> 5 01001020500 4294.309
#> 6 01001020600 3183.779
```
data-raw/tracts.R 0 → 100644
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library(tidycensus)
library(sf)
library(dplyr)
library(stringr)
library(areal)
library(here)
options(tigris_use_cache = TRUE)
five_miles_in_meters <- 8046.72
tract_population <- get_acs(
geography = "tract",
variables = "B01003_001",
state = c(state.abb, "DC", "PR"),
geometry = TRUE
)
tract_population <-
st_transform(
tract_population,
crs = "+proj=aea +lat_1=29.5 +lat_2=45.5 +lat_0=37.5 +lon_0=-96 +x_0=0 +y_0=0 +ellps=GRS80 +datum=NAD83 +units=m +no_defs"
) %>%
mutate(
five_mile_buffer = st_buffer(geometry, five_miles_in_meters),
state = str_extract(NAME, ", [A-Za-z ]+$"),
state = str_remove(state, "^, ")
)
five_mi_buffers <- select(tract_population, GEOID, five_mile_buffer) %>%
st_drop_geometry() %>%
st_as_sf()
pop_within_5_mi <- aw_interpolate(
five_mi_buffers, tid = GEOID, source = tract_population, sid = GEOID,
weight = "sum", output = "tibble", extensive = "estimate"
) %>%
rename(pop_within_5_mi = estimate)
usethis::use_data(pop_within_5_mi, overwrite = TRUE)
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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/pop_within_5_mi.R
\docType{data}
\name{pop_within_5_mi}
\alias{pop_within_5_mi}
\title{population within five miles of each census tract}
\format{
a data frame with 74001 rows and three columns
\describe{
\item{GEOID}{an 11-character identifier for the tract}
\item{pop_within_5_mi}{the population within five miles of the tract}
\item{pop}{population of the tract}
}
}
\source{
\url{https://www.census.gov/programs-surveys/acs/news/data-releases.2018.html}
}
\usage{
pop_within_5_mi
}
\description{
A dataset containing the population within five miles of each census
tract, based on the latest American Community Survey Data
}
\keyword{datasets}
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