step_geodist() creates a specification of a recipe step that will
calculate the distance between points on a map to a reference location.
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")
)A recipe object. The step will be added to the sequence of operations for this recipe.
Selector functions to choose which variables are used by the
step. See selections() for more details.
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.
A logical to indicate if the quantities for preprocessing have been estimated.
Single numeric values for the location of the reference point.
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.
A logical: should the distance be transformed by the natural log function?
A single character value to use for the new predictor column. If a column exists with this name, an error is issued.
A character string of the selected variable names. This field
is a placeholder and will be populated once prep() is used.
A logical to keep the original variables in the
output. Defaults to TRUE.
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.
A character string that is unique to this step to identify it.
An updated version of recipe with the new step added to the
sequence of any existing operations.
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.
When you tidy() this step, a tibble is returned with
columns latitude, longitude, ref_latitude, ref_longitude,
is_lat_lon, name , and id:
character, name of latitude variable
character, name of longitude variable
numeric, location of latitude reference point
numeric, location of longitude reference point
character, the summary function name
character, name of resulting variable
character, id of this step
The underlying operation does not allow for case weights.
https://en.wikipedia.org/wiki/Haversine_formula
Other multivariate transformation steps:
step_classdist(),
step_classdist_shrunken(),
step_depth(),
step_ica(),
step_isomap(),
step_kpca(),
step_kpca_poly(),
step_kpca_rbf(),
step_mutate_at(),
step_nnmf(),
step_nnmf_sparse(),
step_pca(),
step_pls(),
step_ratio(),
step_spatialsign()
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)
#> # A tibble: 20 × 4
#> name latitude longitude geo_dist
#> <chr> <dbl> <dbl> <dbl>
#> 1 National Postal Museum 38.9 -77.0 367.
#> 2 Renwick Gallery 38.9 -77.0 932.
#> 3 National Museum of the American Indian 38.9 -77.0 1571.
#> 4 Smithsonian American Art Museum 38.9 -77.0 1636.
#> 5 National Portrait Gallery 38.9 -77.0 1646.
#> 6 National Air and Space Museum 38.9 -77.0 1796.
#> 7 Hirshhorn Museum and Sculpture Garden 38.9 -77.0 2008.
#> 8 National Museum of Natural History 38.9 -77.0 2073.
#> 9 Arthur M. Sackler Gallery 38.9 -77.0 2108.
#> 10 Arts and Industries Building 38.9 -77.0 2124.
#> 11 Smithsonian Institution Building 38.9 -77.0 2193.
#> 12 National Museum of African Art 38.9 -77.0 2202.
#> 13 Freer Gallery of Art 38.9 -77.0 2266.
#> 14 National Museum of American History 38.9 -77.0 2393.
#> 15 National Museum of African American History and … 38.9 -77.0 2611.
#> 16 National Zoological Park 38.9 -77.1 5246.
#> 17 Anacostia Community Museum 38.9 -77.0 5332.
#> 18 Steven F. Udvar-Hazy Center 38.9 -77.4 38111.
#> 19 George Gustav Heye Center 40.7 -74.0 324871.
#> 20 Cooper Hewitt, Smithsonian Design Museum 40.8 -74.0 334041.
tidy(near_station, number = 1)
#> # A tibble: 1 × 7
#> latitude longitude ref_latitude ref_longitude is_lat_lon name id
#> <chr> <chr> <dbl> <dbl> <lgl> <chr> <chr>
#> 1 latitude longitude 38.9 -77.0 TRUE geo_dist geodist_GL4…