Map a panel column, an area-level estimate or a synthetic control's donors

Draws a choropleth of the areas in a panel. The geometry comes from lamp_boundaries() or lamp_sample_boundaries(); the fill comes from a panel column, from the per-area slopes of a mean-group elasticity, or from the donor weights of a synthetic control.

Usage

lamp_map(x, ...)

# S3 method for class 'lamp_panel'
lamp_map(
  x,
  column = "crime_total",
  boundaries,
  month = NULL,
  statistic = c("mean", "total", "rate"),
  per = 1000,
  border = NA,
  extent = c("panel", "all"),
  ...
)

# S3 method for class 'lamp_elasticity'
lamp_map(x, boundaries, border = NA, extent = c("panel", "all"), ...)

# S3 method for class 'lamp_synth'
lamp_map(x, boundaries, border = NA, extent = c("panel", "all"), ...)

# S3 method for class 'lamp_estimate'
lamp_map(x, ...)

Arguments

x: A lamp_panel, a lamp_elasticity fitted with method = "cce_mg", or a lamp_synth fit.
...: Passed to the method.
column: The panel column to map.
boundaries: An sf object with an area column, from lamp_boundaries() or lamp_sample_boundaries().
month: A single month to map, as a date or "YYYY-MM". NULL, the default, aggregates every month in the panel.
statistic: How to combine months when month is NULL: the area's "mean" per month, its "total" over the period, or "rate", the total per per residents per month.
per: Denominator for statistic = "rate".
border: Colour for area borders, or NA for none. At lower-layer geography the borders swamp the fill, so the default is none.
extent: "panel", the default, draws only the areas the data covers. "all" keeps every boundary supplied, and the caption then counts the areas outside the panel separately from those whose data is missing.

Value

A ggplot.

Missing is not zero

An area whose value cannot be computed, because every month of it was a force-month with no file or because it is absent from the panel, is filled with the missing colour from lamp_colours() and given its own legend entry. It is never shaded as a low value. The caption counts those areas, and counts areas present in one of the panel and the boundaries but not the other, so that a map with a hole in it says why.

Examples

panel <- lamp_sample_panel()
boundaries <- lamp_sample_boundaries()
# one local authority, so that the example draws quickly; a whole force is
# a few seconds and a national panel a few minutes
leeds <- boundaries$area[grepl("^Leeds", boundaries$name)]
lamp_map(panel[panel$area %in% leeds, ], "stop_rate", boundaries)