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How to create a Shapefile with the Percentage of Polish Americans from the US Census Bureau 🗺

How to create a Shapefile with the Percentage of Polish Americans from the US Census Bureau 🗺

Often you may want to make maps of Census Data. While you can certainly make good maps using ggplot in R, often using full GIS software like QGIS or ArcMap might be a better option. It is very easy to create shapefiles to use in your favorite GIS application using tidycensus. Changing the resolution setting can help if you are exporting to PDF or SVG from your GIS program to reduce file sizes.

library(tidycensus) # you will need a free Census API, see tidycensus docs
library(sf) # required for export

# Use this to find Census variables in RStudio. Browse and search the table for
# desired variables.
# load_variables(2020, “acs5”, cache = TRUE) %>% View()

# Get data. By setting geometry = TRUE,
pol <- get_acs(
  geography = “county subdivision”,
  variables = c(“B04006_061”, “B04006_001”),
  survey = “acs5”,
  state = “ny”,
  year = 2020,
  output = ‘wide’,
  resolution = ‘500k’,
  geometry = T,
)  

# calculate percent polish
pol$polish <- (pol$B04006_061E/pol$B04006_001E)*100

# use .gpkg extension for a geopackage, .kml for a KML file
# saves by default in your RStudio directory but change path to where you want
pol %>% write_sf(‘Polish_Americans.shp’)

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Manufactured Housing is very odd the state’s assessment records

Manufactured Housing is very odd the state’s assessment records. Some towns assessors don’t use that code at all, preferring to either leave the housing style field blank or describing such structures as Ranch style. For example, Coeymans doesn’t have a single building that is Manufactured Housing but Cario has several hundred. In some towns its inconsistent – varies widely by property – probably whoever was assessor at the time.

But then again, assessment records are riddled with errors. If you look at the City of Albany assessment records, only two buildings were built before 1850, a fact that doesn’t take long to disprove.

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