Each groups distribution of distances

SLOW / needs to be optimized. CDF Line Plots of cumulative share of each residential population group, within each distance

This plots the cumulative share of residents found within each distance, for a single population group.

This function, distance_cdf_by_group_plot(), is based on ejamit()$results_bybg_people, which provides only block group resolution information about distance. For block resolution analysis of distance by group, see plot_distance_by_pctd().

Usage

distance_by_group_plot(
  results_bybg_people = NULL,
  radius_miles = NULL,
  subgroups_type = NULL,
  demogvarname = NULL,
  demoglabel = NULL,
  colorlist = colorspace::diverging_hcl(length(demogvarname)),
  coloroverall = "black",
  returnwhat = "table",
  ...
)

distance_cdf_by_group_plot(
  results_bybg_people,
  radius_miles = NULL,
  demogvarname = "Demog.Index",
  demoglabel = demogvarname,
  color1 = "red",
  color2 = "black"
)

plot_distance_cdf_by_group(
  results_bybg_people = NULL,
  radius_miles = NULL,
  subgroups_type = NULL,
  demogvarname = NULL,
  demoglabel = NULL,
  colorlist = colorspace::diverging_hcl(length(demogvarname)),
  coloroverall = "black",
  returnwhat = "table",
  ...
)

Arguments

results_bybg_people

data.table from doaggregate()$results_bybg_people

radius_miles

miles radius that was max distance analyzed

subgroups_type

optional, can be set to "nh" or "alone". Specifies types of race ethnicity subgroups to use for demogvarname but only if demogvarname is not specified as a parameter.

demogvarname

name of column in results_bybg_people, e.g., "pctlowinc"

demoglabel

friendly text name for labelling graphic, like "Low income residents"

colorlist

colors like "red" etc. for the residential population groups of interest

coloroverall

color like "gray" for everyone as a whole

returnwhat

If returnwhat is "table", invisibly returns a full table of sorted distances of blockgroups, cumulative count of demog groups at that block group's distance. If returnwhat is "plotfilename" then it returns the full path including filename of a .png in a tempdir If returnwhat is "plot" then it returns the plot object as needed for table_xls_format()

...

other parameters passed through to points()

color1

color like "red" for residential population group of interest

color2

color like "gray" for everyone else

Value

see returnwhat parameter

invisibly returns full table of sorted distances of blockgroups, cumulative count of demog group at that block group's distance, and cumulative count of everyone else in that block group

see distance_by_group_plot()

Details

The function distance_cdf_by_group_plot is SLOW - ***needs to be optimized

See also

distance_by_group() ejamit() for examples

distance_by_group() getblocksnearbyviaQuadTree() for examples

Examples

 y <- ejamit(testpoints_100, radius = 3)
 
 # see barplot and table comparing groups to see which are closer to sites analyzed
 plot_distance_mean_by_group(y$results_bybg_people) # or distance_mean_by_group() synonym
 
 # table - proximity of sites for just one demog group vs rest of population
 print(distance_by_group(y$results_bybg_people,
   demogvarname = 'pctlowinc'))
   
 # plot cumulative share of group by distance vs overall population
  distance_by_group_plot(y$results_bybg_people,
     demogvarname = 'pctlowinc' )
     
 # plot cum. shares for two groups  
 # about 14% of black and 12% of asian residents have a site within 1 mile. 
 # 29% vs 21% have a site within 1.5 miles.
 round(xyz[findInterval(c(1, 1.5),  xyz$dist), ], 3) 
 
 # plot is too busy for all groups at once so this is a way to tap through them 1 by 1
 these = c(names_d, names_d_subgroups)
 for (i in 1:length(these)) {
   readline("press any key to see the next plot")
   print(distance_by_group_plot(y$results_bybg_people, demogvarname = these[i]) )
 }