Package 'PL94171'

Download Block Crosswalk Files

Description

Downloads crosswalks from https://www.census.gov/geographies/reference-files/time-series/geo/relationship-files.html. Adjusts land overlap area to ensure weights sum to 1.

Usage

pl_crosswalk(abbr, from_year = 2010L, to_year = from_year + 10L)

Arguments

abbr	the state to download the crosswalk for.
from_year	the year with the blocks that the data is currently tabulated with respect to.
to_year	the year with the blocks that the data should be tabulated into.

Value

A tibble, with two sets of GEOIDs and overlap information.

Examples

## Not run: 
# Takes a bit of time to run
pl_crosswalk("RI", 2010, 2020)

## End(Not run)

---

PL Example File

Description

This data contains a subset of the 2020 prototype PL data

Usage

data("pl_ex")

Format

list of tibbles containing the four PL files.

00001

Tables P1 and P2

00002

Tables P3, P4, and H1

00003

Table P5

geo

geographic header file

Examples

data(pl_ex)

---

List of Summary Levels and Official Descriptions

Description

This dataset is tibble version of the descriptions of (potentially) available summary levels within the P.L. 94-171 data, as described in the 2018 Redistricting Data Prototype (Public Law 94-171) Summary File documentation.

Usage

pl_geog_levels

Format

a tibble with two columns:

SUMLEV

The three character summary level code

SUMLEV_description

The summary level description

---

Download 2020 Block Assignment Files for a State

Description

From the Census: "The Block Assignment Files (BAFs) are among the geographic products that the Census Bureau provides to states and other data users containing the small area census data necessary for legislative redistricting. The BAFs contain Census tabulation block codes and geographic area codes for a specific geographic entity type."

Usage

pl_get_baf(abbr, geographies = NULL, cache_to = NULL, refresh = FALSE)

Arguments

abbr	the state abbreviation to get the BAF for
geographies	the geographies to get. Defaults to all available.
cache_to	the file name, if any, to cache the results to (as an RDS). If a file exists and refresh=FALSE, will read BAF from this file.
refresh	if TRUE, force a re-download of the BAF data.

Value

A list of tibbles, one for each available BAF geography.

Examples

pl_get_baf("RI")
pl_get_baf("RI", "VTD")

---

Download TIGER Prototype shapefiles

Description

These prototype shapefiles correspond to the Rhode Island end-to-end Census test and the accompanying prototype P.L. 94-171 data. This function is unlikely to be useful for working with any actual decennial Census data. The corresponding tinytiger or tigris functions should be used instead.

Usage

pl_get_prototype(
  geog,
  year = 2020,
  full_state = TRUE,
  cache_to = NULL,
  clean_names = TRUE,
  refresh = FALSE
)

Arguments

geog	Geography to download data for. See details for full list.
year	year, either 2010 or 2020
full_state	whether to return the full state (TRUE) or the single county subset (FALSE)
cache_to	the file name, if any, to cache the results to (as an RDS). If a file exists and refresh=FALSE, will read from this file.
clean_names	whether to clean and rename columns
refresh	if TRUE, force a re-download of the data.

Details

Current acceptable arguments to geog include:

• block: block

• block_group: block group

• tract: tract

• county: county

• state: state

• sld_low: state legislative district lower house

• sld_up: state legislative district upper house

• congressional_district: federal congressional district

• place: Census place

• voting_district: voting tabulation district

Value

An sf object containing the blocks.

Examples

shp <- pl_get_prototype("block")

---

Download 2020 Voting District Shapefiles

Description

A (likely temporary) function to download TIGER shapefiles for 2020 voting tabulation districts (VTDs).

Usage

pl_get_vtd(abbr, cache_to = NULL, refresh = FALSE)

Arguments

abbr	Geography to download data for. See details for full list.
cache_to	the file name, if any, to cache the results to (as an RDS). If a file exists and refresh=FALSE, will read from this file.
refresh	if TRUE, force a re-download of the data.

Value

An sf object containing the VTDs.

Examples

shp <- pl_get_vtd("RI")

---

Read a set of PL Files

Description

PL files come in one of four types and are pipe-delimited with no header row. This function speedily reads in the files and assigns the appropriate column names and types.

Usage

pl_read(path, ...)

read_pl(path, ...)

Arguments

path	a path to a folder containing PL files. Can also be path or a URL for a ZIP file, which will be downloaded and unzipped.
...	passed on to readr::read_delim()

Value

A list of data frames containing the four PL files.

Examples

pl_ex_path <- system.file('extdata/ri2018_2020Style.pl', package = 'PL94171')
pl <- pl_read(pl_ex_path)

# or try `pl_read(pl_url("RI", 2010))`

---

Approximately re-tally Census data under new block boundaries

Description

Applies a block crosswalk to a table of block data using areal interpolation. That is, the fraction of land area in the overlapping region between old and new blocks is used to divide the population of the old blocks into the new.

Usage

pl_retally(d_from, crosswalk)

Arguments

d_from	The data frame to process. All numeric columns will be re-tallied. Integer columns will be re-tallied with rounding. Character columns will be preserved if constant across new block geometries.
crosswalk	The crosswalk data frame, from pl_crosswalk()

Details

All numeric columns will be re-tallied. Integer columns will be re-tallied with rounding. Character columns will be preserved if constant across new block geometries.

Blocks from other states will be ignored.

Value

A new data frame, like d_from, except with the geometry column dropped, if one exists. New geometry should be loaded, perhaps with tinytiger::tt_blocks().

Examples

crosswalk = pl_crosswalk("RI", 2010, 2020)
RI_2010 = pl_tidy_shp("RI", pl_url("RI", 2010), 2010)
pl_retally(RI_2010, crosswalk)

---

Select the Standard Redistricting Columns

Description

Selects the standard set of basic population groups and VAP groups. Optionally renames them from the PXXXYYYY naming convention (where XXX is the table and YYYY is the variable) to more human readable names. pop_* is the total population, from tables 1 and 2, while vap_* is the 18+ population (voting age population).

Usage

pl_select_standard(pl, clean_names = TRUE)

Arguments

pl	A list of PL tables, as read in by pl_read()
clean_names	whether to clean names

Details

If ⁠clean names=TRUE⁠, then the variables extracted are as follows:

• ⁠\*_hisp⁠: Hispanic or Latino (of any race)

• ⁠\*_white⁠: White alone, not Hispanic or Latino

• ⁠\*_black⁠: Black or African American alone, not Hispanic or Latino

• ⁠\*_aian⁠: American Indian and Alaska Native alone, not Hispanic or Latino

• ⁠\*_asian⁠: Asian alone, not Hispanic or Latino

• ⁠\*_nhpi⁠: Native Hawaiian and Other Pacific Islander alone, not Hispanic or Latino

• ⁠\*_other⁠: Some Other Race alone, not Hispanic or Latino

• ⁠\*_two⁠: Population of two or more races, not Hispanic or Latino

where \* is pop or vap.

Value

A tibble with the selected and optionally renamed columns

Examples

pl_ex_path <- system.file('extdata/ri2018_2020Style.pl', package = 'PL94171')
pl <- pl_read(pl_ex_path)
pl <- pl_select_standard(pl)

---

Subset to a Summary Level

Description

This subsets a pl table to a desired summary level. Typical choices include:

• '750': block

• '150': block group

• '630': voting district

• '050': county

Usage

pl_subset(pl, sumlev = "750")

Arguments

pl	A list of PL tables, as read in by pl_read()
sumlev	the summary level to filter to. A 3 character SUMLEV code. Default is '750' for blocks.

Details

All summary levels are listed in pl_geog_levels.

Value

tibble

Examples

pl_ex_path <- system.file('extdata/ri2018_2020Style.pl', package = 'PL94171')
pl <- pl_read(pl_ex_path)
pl <- pl_subset(pl)

---

All-in-one Shapefile Function

Description

Downloads block geography and merges with the cleaned PL 94-171 file.

Usage

pl_tidy_shp(abbr, path, year = 2020, type = c("blocks", "vtds"), ...)

Arguments

abbr	The state to make the shapefile for
path	The path to the PL files, as in pl_read()
year	The year to download the block geography for. Should match the year of the PL files.
type	If "blocks", make a Census block shapefile; if "vtds" make a VTD shapefile.
...	passed on to dplyr::filter(); use to subset to a certain county, for example.

Value

an sf object with demographic and shapefile information for the state.

Examples

pl_ex_path <- system.file("extdata/ri2018_2020Style.pl", package = "PL94171")
pl_tidy_shp("RI", pl_ex_path)

---

Get the URL for PL files for a particular state and year

Description

Get the URL for PL files for a particular state and year

Usage

pl_url(abbr, year = 2010)

Arguments

abbr	The state to download the PL files for
year	The year of PL file to download. Supported years: 2000, 2010, 2020 (after release). 2000 files are in a different format. Earlier years available on tape or CD-ROM only.

Value

a character vector containing the URL to a ZIP containing the PL files.

Examples

pl_url("RI", 2010)

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