featuretools.primitives.Haversine#

class featuretools.primitives.Haversine(unit='miles')[source]#

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')[source]#

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