Lab-03 Identifying Neighborhood Clusters
Packages
library( geojsonio ) # read shapefiles
library( sp ) # work with shapefiles
library( sf ) # work with shapefiles - simple features format
library( mclust ) # cluster analysis
library( tmap ) # theme maps
library( ggplot2 ) # graphing
library( ggthemes )
library( dplyr )
library( pander )Data Source
This exercise uses Census data from the 2012 American Communities Survey made available through the Diversity and Disparities Project.
DATA DICTIONARY
| LABEL | VARIABLE |
|---|---|
| tractid | GEOID |
| pnhwht12 | Percent white, non-Hispanic |
| pnhblk12 | Percent black, non-Hispanic |
| phisp12 | Percent Hispanic |
| pntv12 | Percent Native American race |
| pfb12 | Percent foreign born |
| polang12 | Percent speaking other language at home, age 5 plus |
| phs12 | Percent with high school degree or less |
| pcol12 | Percent with 4-year college degree or more |
| punemp12 | Percent unemployed |
| pflabf12 | Percent female labor force participation |
| pprof12 | Percent professional employees |
| pmanuf12 | Percent manufacturing employees |
| pvet12 | Percent veteran |
| psemp12 | Percent self-employed |
| hinc12 | Median HH income, total |
| incpc12 | Per capita income |
| ppov12 | Percent in poverty, total |
| pown12 | Percent owner-occupied units |
| pvac12 | Percent vacant units |
| pmulti12 | Percent multi-family units |
| mrent12 | Median rent |
| mhmval12 | Median home value |
| p30old12 | Percent structures more than 30 years old |
| p10yrs12 | Percent HH in neighborhood 10 years or less |
| p18und12 | Percent 17 and under, total |
| p60up12 | Percent 60 and older, total |
| p75up12 | Percent 75 and older, total |
| pmar12 | Percent currently married, not separated |
| pwds12 | Percent widowed, divorced and separated |
| pfhh12 | Percent female-headed families with children |
Load Phoenix Shapefile
We are using a Dorling Cartogram representation of Census tracts to remove bias.
The steps to create the cartogram are described HERE.
# dorling cartogram of Phoenix Census Tracts
github.url <- "https://raw.githubusercontent.com/DS4PS/cpp-529-master/master/data/phx_dorling.geojson"
phx <- geojson_read( x=github.url, what="sp" )
plot( phx )
We can do better than that. Let’s take a look at the tmap package in R.
# library( tmap )
phx <- spTransform( phx, CRS("+init=epsg:3395") )
bb <- st_bbox( c( xmin = -12519146, xmax = -12421368,
ymax = 3965924, ymin = 3899074 ),
crs = st_crs("+init=epsg:3395"))
tm_shape( phx, bbox=bb ) +
tm_polygons( col="MHHI", n=10, style="quantile", palette="Spectral" ) +
tm_layout( "PHX Dorling Cartogram", title.position=c("right","top") )