step_geodist: Distance between two locations
In recipes: Preprocessing and Feature Engineering Steps for Modeling

step_geodist

R Documentation

Distance between two locations

Description

step_geodist() creates a specification of a recipe step that will calculate the distance between points on a map to a reference location.

Usage

step_geodist(
  recipe,
  lat = NULL,
  lon = NULL,
  role = "predictor",
  trained = FALSE,
  ref_lat = NULL,
  ref_lon = NULL,
  is_lat_lon = TRUE,
  log = FALSE,
  name = "geo_dist",
  columns = NULL,
  keep_original_cols = TRUE,
  skip = FALSE,
  id = rand_id("geodist")
)

Arguments

`recipe`	A recipe object. The step will be added to the sequence of operations for this recipe.
`lon`, `lat`	Selector functions to choose which variables are used by the step. See `selections()` for more details.
`role`	For model terms created by this step, what analysis role should they be assigned? By default, the new columns created by this step from the original variables will be used as predictors in a model.
`trained`	A logical to indicate if the quantities for preprocessing have been estimated.
`ref_lon`, `ref_lat`	Single numeric values for the location of the reference point.
`is_lat_lon`	A logical: Are coordinates in latitude and longitude? If `TRUE` the Haversine formula is used and the returned result is meters. If `FALSE` the Pythagorean formula is used. Default is `TRUE` and for recipes created from previous versions of recipes, a value of `FALSE` is used.
`log`	A logical: should the distance be transformed by the natural log function?
`name`	A single character value to use for the new predictor column. If a column exists with this name, an error is issued.
`columns`	A character string of the selected variable names. This field is a placeholder and will be populated once `prep()` is used.
`keep_original_cols`	A logical to keep the original variables in the output. Defaults to `TRUE`.
`skip`	A logical. Should the step be skipped when the recipe is baked by `bake()`? While all operations are baked when `prep()` is run, some operations may not be able to be conducted on new data (e.g. processing the outcome variable(s)). Care should be taken when using `skip = TRUE` as it may affect the computations for subsequent operations.
`id`	A character string that is unique to this step to identify it.

Details

step_geodist uses the Pythagorean theorem to calculate Euclidean distances if is_lat_lon is FALSE. If is_lat_lon is TRUE, the Haversine formula is used to calculate the great-circle distance in meters.

Value

An updated version of recipe with the new step added to the sequence of any existing operations.

Tidying

When you tidy() this step, a tibble is returned with columns latitude, longitude, ref_latitude, ref_longitude, is_lat_lon, name , and id:

latitude: character, name of latitude variable
longitude: character, name of longitude variable
ref_latitude: numeric, location of latitude reference point
ref_longitude: numeric, location of longitude reference point
is_lat_lon: character, the summary function name
name: character, name of resulting variable
id: character, id of this step

Case weights

The underlying operation does not allow for case weights.

References

https://en.wikipedia.org/wiki/Haversine_formula

Examples


data(Smithsonian, package = "modeldata")

# How close are the museums to Union Station?
near_station <- recipe(~., data = Smithsonian) %>%
  update_role(name, new_role = "location") %>%
  step_geodist(
    lat = latitude, lon = longitude, log = FALSE,
    ref_lat = 38.8986312, ref_lon = -77.0062457,
    is_lat_lon = TRUE
  ) %>%
  prep(training = Smithsonian)

bake(near_station, new_data = NULL) %>%
  arrange(geo_dist)

tidy(near_station, number = 1)

recipes documentation built on July 4, 2024, 9:06 a.m.