featuretools.primitives.AbsoluteDiff

class featuretools.primitives.AbsoluteDiff(method='ffill', limit=None)

Calculates the absolute difference from the previous element

in a list of numbers.

Description:

The absolute difference from the previous element is computed for all elements in the input. The first item in the output will always be nan, since there is no previous element for the first element. Elements in the input containing nan will be filled using either a forward-fill or backward-fill method, specified by the method argument.

Parameters:

• method (str) –

  Method to use for filling nan values in reindexed Series. Possible values are [‘pad’, ‘ffill’, ‘backfill’, ‘bfill’]. Default is ‘ffill’.

  pad / ffill: propagate last valid observation forward

  to fill gap

  backfill / bfill: propagate next valid observation backward

  to fill gap

• limit (int) – The max number of consecutive NaN values in a gap that can be filled. Default is None.

Examples

>>> absolute_diff = AbsoluteDiff()
>>> absolute_diff([2, 5, 15, 3]).tolist()
[nan, 3.0, 10.0, 12.0]

Forward filling of input elements using the ‘ffill’ argument

>>> absolute_diff_ffill = AbsoluteDiff(method="ffill")
>>> absolute_diff_ffill([None, 5, 10, 20, None, 10, None]).tolist()
[nan, nan, 5.0, 10.0, 0.0, 10.0, 0.0]

Backward filling of input element using the ‘bfill’ argument

>>> absolute_diff_bfill = AbsoluteDiff(method="bfill")
>>> absolute_diff_bfill([None, 5, 10, 20, None, 10, None]).tolist()
[nan, 0.0, 5.0, 10.0, 10.0, 0.0, nan]

The number of nan values that are filled can be limited

>>> absolute_diff_limitfill = AbsoluteDiff(limit=2)
>>> absolute_diff_limitfill([2, None, None, None, 3, 1]).tolist()
[nan, 0.0, 0.0, nan, nan, 2.0]

__init__(method='ffill', limit=None)

Methods

__init__([method, limit])
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