Tools, Shapefiles & Data to Work with an ‘AlbersUSA’ Composite Projection
The following functions are implemented:
counties_sf
: Retreive a U.S. county composite map, optionally with a projection, as a simplefeatureusa_sf
: Retreive a U.S. state composite map, optionally with a projection, as a simplefeature
New ones:
points_elided
: Shift points around Alaska and Hawaii to the elided area (by @rdinter)
Some legacy ones:
usa_composite
: Retreive a U.S. composite map, optionally with a projectioncounties_composite
: Retreive a U.S. county composite map, optionally with a projection
Pre-canned projection strings:
us_aeqd_proj
: Oblique azimuthal equidistant convenience projectionus_eqdc_proj
: Equidistant conic convenience projectionus_laea_proj
: Albers equal-area conic convenience projectionus_lcc_proj
: Lambert conformal conic convenience projectionus_longlat_proj
: Generic long/lat convenience projection
The following data sets are included:
system.file("extdata/composite_us_states.geojson.gz", package="albersusa")
system.file("extdata/composite_us_counties.geojson.gz", package="albersusa")
Also, the simplefeatures coluns and @data
slot of each
SpatialPolygonsDataFrame
has some handy data you can use (like FIPS
codes and state/county population information).
devtools::install_github("hrbrmstr/albersusa")
library(albersusa)
library(sf)
library(sp)
library(rgeos)
library(maptools)
library(ggplot2)
library(ggalt)
library(ggthemes)
library(viridis)
library(scales)
# current verison
packageVersion("albersusa")
## [1] '0.3.0'
par(mar=c(0,0,1,0))
us_sf <- usa_sf("laea")
plot(us_sf["pop_2012"])
cty_sf <- counties_sf("aeqd")
plot(cty_sf["census_area"])
us <- usa_composite()
dplyr::glimpse(us@data)
## Observations: 51
## Variables: 13
## $ geo_id <chr> "0400000US04", "0400000US05", "0400000US06", "0400000US08", "0400000US09", "0400000US11...
## $ fips_state <chr> "04", "05", "06", "08", "09", "11", "13", "17", "18", "22", "27", "28", "30", "35", "38...
## $ name <chr> "Arizona", "Arkansas", "California", "Colorado", "Connecticut", "District of Columbia",...
## $ lsad <chr> "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "",...
## $ census_area <dbl> 113594.084, 52035.477, 155779.220, 103641.888, 4842.355, 61.048, 57513.485, 55518.930, ...
## $ iso_3166_2 <chr> "AZ", "AR", "CA", "CO", "CT", "DC", "GA", "IL", "IN", "LA", "MN", "MS", "MT", "NM", "ND...
## $ census <int> 6392017, 2915918, 37253956, 5029196, 3574097, 601723, 9687653, 12830632, 6483802, 45333...
## $ pop_estimataes_base <int> 6392310, 2915958, 37254503, 5029324, 3574096, 601767, 9688681, 12831587, 6484192, 45334...
## $ pop_2010 <int> 6411999, 2922297, 37336011, 5048575, 3579345, 605210, 9714464, 12840097, 6490308, 45455...
## $ pop_2011 <int> 6472867, 2938430, 37701901, 5119661, 3590537, 620427, 9813201, 12858725, 6516560, 45759...
## $ pop_2012 <int> 6556236, 2949300, 38062780, 5191709, 3594362, 635040, 9919000, 12873763, 6537632, 46047...
## $ pop_2013 <int> 6634997, 2958765, 38431393, 5272086, 3599341, 649111, 9994759, 12890552, 6570713, 46292...
## $ pop_2014 <int> 6731484, 2966369, 38802500, 5355866, 3596677, 658893, 10097343, 12880580, 6596855, 4649...
plot(us, lwd=0.25)
us <- usa_composite("laea")
plot(us, lwd=0.25)
us <- usa_composite()
us_map <- fortify(us, region="name")
gg <- ggplot()
gg <- gg + geom_map(data=us_map, map=us_map,
aes(x=long, y=lat, map_id=id),
color="#2b2b2b", size=0.1, fill=NA)
gg <- gg + theme_map()
gg + coord_map()
gg + coord_map("polyconic")
gg + coord_proj()
gg + coord_proj(us_laea_proj)
gg + coord_proj(us_aeqd_proj)
gg + coord_proj(us_eqdc_proj)
gg + coord_proj(us_lcc_proj)
gg +
geom_map(data=us@data, map=us_map,
aes(fill=pop_2014, map_id=name),
color="white", size=0.1) +
coord_proj(us_laea_proj) +
scale_fill_viridis(name="2014 Populaton Estimates", labels=comma) +
theme(legend.position="top",
legend.key.width=unit(3, "lines"))
us <- counties_composite()
dplyr::glimpse(us@data)
## Observations: 3,143
## Variables: 8
## $ fips <chr> "01001", "01009", "01017", "01021", "01033", "01045", "01051", "01065", "01079", "01083", "0109...
## $ state_fips <chr> "01", "01", "01", "01", "01", "01", "01", "01", "01", "01", "01", "01", "01", "05", "05", "06",...
## $ county_fips <chr> "001", "009", "017", "021", "033", "045", "051", "065", "079", "083", "099", "107", "121", "141...
## $ name <chr> "Autauga", "Blount", "Chambers", "Chilton", "Colbert", "Dale", "Elmore", "Hale", "Lawrence", "L...
## $ lsad <chr> "County", "County", "County", "County", "County", "County", "County", "County", "County", "Coun...
## $ census_area <dbl> 594.436, 644.776, 596.531, 692.854, 592.619, 561.150, 618.485, 643.943, 690.678, 559.936, 1025....
## $ state <chr> "Alabama", "Alabama", "Alabama", "Alabama", "Alabama", "Alabama", "Alabama", "Alabama", "Alabam...
## $ iso_3166_2 <chr> "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AR", "AR", "CA",...
plot(us, lwd=0.25)
us <- counties_composite("laea")
plot(us, lwd=0.25)
us <- counties_composite()
us_map <- fortify(us, region="fips")
gg <- ggplot()
gg <- gg + geom_map(data=us_map, map=us_map,
aes(x=long, y=lat, map_id=id),
color="#2b2b2b", size=0.1, fill=NA)
gg <- gg + theme_map()
gg + coord_map()
gg + coord_map("polyconic")
gg + coord_proj()
gg + coord_proj(us_laea_proj)
gg + coord_proj(us_aeqd_proj)
gg + coord_proj(us_eqdc_proj)
gg + coord_proj(us_lcc_proj)
devtools::session_info()
## Session info ----------------------------------------------------------------------------------------------------------
## setting value
## version R version 3.5.0 RC (2018-04-15 r74605)
## system x86_64, darwin15.6.0
## ui X11
## language (EN)
## collate en_US.UTF-8
## tz America/New_York
## date 2018-05-09
## Packages --------------------------------------------------------------------------------------------------------------
## package * version date source
## albersusa * 0.3.0 2018-05-09 local
## ash 1.0-15 2015-09-01 cran (@1.0-15)
## assertthat 0.2.0 2017-04-11 CRAN (R 3.5.0)
## backports 1.1.2 2017-12-13 CRAN (R 3.5.0)
## base * 3.5.0 2018-04-16 local
## bindr 0.1.1 2018-03-13 CRAN (R 3.5.0)
## bindrcpp 0.2.2 2018-03-29 CRAN (R 3.5.0)
## class 7.3-14 2015-08-30 CRAN (R 3.5.0)
## classInt 0.2-3 2018-04-16 CRAN (R 3.5.0)
## colorspace 1.3-2 2016-12-14 CRAN (R 3.5.0)
## compiler 3.5.0 2018-04-16 local
## datasets * 3.5.0 2018-04-16 local
## DBI 0.8 2018-03-02 CRAN (R 3.5.0)
## devtools 1.13.5 2018-02-18 CRAN (R 3.5.0)
## digest 0.6.15 2018-01-28 CRAN (R 3.5.0)
## dplyr 0.7.4 2017-09-28 CRAN (R 3.5.0)
## e1071 1.6-8 2017-02-02 cran (@1.6-8)
## evaluate 0.10.1 2017-06-24 CRAN (R 3.5.0)
## extrafont 0.17 2014-12-08 cran (@0.17)
## extrafontdb 1.0 2012-06-11 cran (@1.0)
## foreign 0.8-70 2017-11-28 CRAN (R 3.5.0)
## ggalt * 0.6.0 2018-04-17 Github (hrbrmstr/ggalt@9ad95ba)
## ggplot2 * 2.2.1.9000 2018-05-03 Github (tidyverse/ggplot2@6a261a2)
## ggthemes * 3.4.2 2018-04-03 CRAN (R 3.5.0)
## glue 1.2.0 2017-10-29 CRAN (R 3.5.0)
## graphics * 3.5.0 2018-04-16 local
## grDevices * 3.5.0 2018-04-16 local
## grid 3.5.0 2018-04-16 local
## gridExtra 2.3 2017-09-09 CRAN (R 3.5.0)
## gtable 0.2.0 2016-02-26 CRAN (R 3.5.0)
## htmltools 0.3.6 2017-04-28 CRAN (R 3.5.0)
## KernSmooth 2.23-15 2015-06-29 CRAN (R 3.5.0)
## knitr 1.20 2018-02-20 CRAN (R 3.5.0)
## labeling 0.3 2014-08-23 CRAN (R 3.5.0)
## lattice 0.20-35 2017-03-25 CRAN (R 3.5.0)
## lazyeval 0.2.1 2017-10-29 CRAN (R 3.5.0)
## magrittr 1.5 2014-11-22 CRAN (R 3.5.0)
## mapproj 1.2.6 2018-03-29 CRAN (R 3.5.0)
## maps 3.3.0 2018-04-03 cran (@3.3.0)
## maptools * 0.9-2 2017-03-25 CRAN (R 3.5.0)
## MASS 7.3-50 2018-04-30 CRAN (R 3.5.0)
## memoise 1.1.0 2017-04-21 CRAN (R 3.5.0)
## methods * 3.5.0 2018-04-16 local
## munsell 0.4.3 2016-02-13 CRAN (R 3.5.0)
## pillar 1.2.2 2018-04-26 CRAN (R 3.5.0)
## pkgconfig 2.0.1 2017-03-21 CRAN (R 3.5.0)
## plyr 1.8.4 2016-06-08 CRAN (R 3.5.0)
## proj4 1.0-8 2012-08-05 cran (@1.0-8)
## R6 2.2.2 2017-06-17 CRAN (R 3.5.0)
## RColorBrewer 1.1-2 2014-12-07 CRAN (R 3.5.0)
## Rcpp 0.12.16 2018-03-13 CRAN (R 3.5.0)
## rgdal 1.2-18 2018-03-17 CRAN (R 3.5.0)
## rgeos * 0.3-26 2017-10-31 CRAN (R 3.5.0)
## rlang 0.2.0.9001 2018-05-03 Github (r-lib/rlang@4803704)
## rmarkdown 1.9 2018-03-01 CRAN (R 3.5.0)
## RPostgreSQL 0.6-2 2017-06-24 CRAN (R 3.5.0)
## rprojroot 1.3-2 2018-01-03 CRAN (R 3.5.0)
## Rttf2pt1 1.3.6 2018-02-22 cran (@1.3.6)
## scales * 0.5.0.9000 2018-05-04 Github (hadley/scales@d767915)
## sf * 0.6-2 2018-04-25 CRAN (R 3.5.0)
## sp * 1.2-7 2018-01-19 CRAN (R 3.5.0)
## spData 0.2.8.3 2018-03-25 CRAN (R 3.5.0)
## stats * 3.5.0 2018-04-16 local
## stringi 1.2.2 2018-05-02 cran (@1.2.2)
## stringr 1.3.0 2018-02-19 CRAN (R 3.5.0)
## tibble 1.4.2 2018-01-22 CRAN (R 3.5.0)
## tools 3.5.0 2018-04-16 local
## udunits2 0.13 2016-11-17 cran (@0.13)
## units 0.5-1 2018-01-08 cran (@0.5-1)
## utils * 3.5.0 2018-04-16 local
## viridis * 0.5.1 2018-03-29 CRAN (R 3.5.0)
## viridisLite * 0.3.0 2018-02-01 CRAN (R 3.5.0)
## withr 2.1.2 2018-05-03 Github (jimhester/withr@79d7b0d)
## yaml 2.1.19 2018-05-01 CRAN (R 3.5.0)
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