stplanr (version 0.1.4)

cents: SpatialPointsDataFrame of home locations for flow analysis.

Description

These points represent population-weighted centroids of Medium Super Output Area (MSOA) zones within a 1 mile radius of of my home when I was writing this package.

Usage

data(cents)

Format

A SpatialPoints with 8 rows and 5 variables

Details

• geo_code. the official code of the zone
• MSOA11NM. name zone name
• percent_fem. the percent female
• avslope. average gradient of the zone

Cents was generated from the data repository pct-data: https://github.com/npct/pct-data. This data was accessed from within the pct repo: https://github.com/npct/pct, using the following code:

Examples

## Not run: 
# cents <- rgdal::readOGR(dsn = "/home/robin/npct/pct-bigdata/cents.geojson", layer = "OGRGeoJSON")
# # library(geojsonio) # load with the ropensci package geojsonio if rgdal fails
# # cents <- geojsonio::geojson_read(x = "~/repos/pct/pct-data/national/cents.geojson")
# crs <- CRS("+init=epsg:4326")
# crsuk <- CRS("+init=epsg:27700")
# cents <- sp::spTransform(x = cents, CRSobj = crsuk)
# home <- rev(RgoogleMaps::getGeoCode("LS7 3HB"))
# home <- sp::SpatialPoints(matrix(home, ncol = 2), proj4string = crs)
# home <- sp::spTransform(x = home, CRSobj = crsuk)
# buf <- rgeos::gBuffer(home, width = 2000)
# # Check it saved the points OK
# cents <- cents[buf,]
# plot(buf)
# points(cents)
# cents <- sp::spTransform(x = cents, CRSobj = crs)
# cents$geo_code <- as.character(cents$geo_code)
# library(devtools)
# # use_data(cents, overwrite = TRUE)
# ## End(Not run)