featuretools.primitives.Haversine

class featuretools.primitives.Haversine(unit='miles')

Calculates the approximate haversine distance between two LatLong columns.

Parameters:

unit (str) – Determines the unit value to output. Could be miles or kilometers. Default is miles.

Examples

>>> haversine = Haversine()
>>> distances = haversine([(42.4, -71.1), (40.0, -122.4)],
...                       [(40.0, -122.4), (41.2, -96.75)])
>>> np.round(distances, 3).tolist()
[2631.231, 1343.289]

Output units can be specified

>>> haversine_km = Haversine(unit='kilometers')
>>> distances_km = haversine_km([(42.4, -71.1), (40.0, -122.4)],
...                             [(40.0, -122.4), (41.2, -96.75)])
>>> np.round(distances_km, 3).tolist()
[4234.555, 2161.814]

__init__(unit='miles')

Methods

__init__([unit])
flatten_nested_input_types(input_types)	Flattens nested column schema inputs into a single list.
generate_name(base_feature_names)
generate_names(base_feature_names)
get_args_string()
get_arguments()
get_description(input_column_descriptions[, ...])
get_filepath(filename)
get_function()

Attributes

base_of
base_of_exclude
commutative
default_value	Default value this feature returns if no data found.
description_template
input_types	woodwork.ColumnSchema types of inputs
max_stack_depth
name	Name of the primitive
number_output_features	Number of columns in feature matrix associated with this feature
return_type	ColumnSchema type of return
stack_on
stack_on_exclude
stack_on_self
uses_calc_time
uses_full_dataframe