featuretools.primitives.SameAsPrevious#
- class featuretools.primitives.SameAsPrevious(fill_method='pad', limit=None)[source]#
Determines if a value is equal to the previous value in a list.
- Description:
Compares a value in a list to the previous value and returns True if the value is equal to the previous value or False otherwise. The first item in the output will always be False, since there is no previous element for the first element comparison.
Any nan values in the input will be filled using either a forward-fill or backward-fill method, specified by the fill_method argument. The number of consecutive nan values that get filled can be limited with the limit argument. Any nan values left after filling will result in False being returned for any comparison involving the nan value.
- Parameters:
fill_method (str) – Method for filling gaps in series. Valid
backfill (options are) –
bfill (backfill /) –
pad –
ffill. –
ffill (pad /) – fill gap with last valid observation.
bfill – fill gap with next valid observation.
pad. (Default is) –
limit (int) – The max number of consecutive NaN values in a gap that can be filled. Default is None.
Examples
>>> same_as_previous = SameAsPrevious() >>> same_as_previous([1, 2, 2, 4]).tolist() [False, False, True, False]
The fill method for nan values can be specified
>>> same_as_previous_fillna = SameAsPrevious(fill_method="bfill") >>> same_as_previous_fillna([1, None, 2, 4]).tolist() [False, False, True, False]
The number of nan values that are filled can be limited
>>> same_as_previous_limitfill = SameAsPrevious(limit=2) >>> same_as_previous_limitfill([1, None, None, None, 2, 3]).tolist() [False, True, True, False, False, False]
Methods
__init__
([fill_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
compatibility
Additional compatible libraries
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
series_library
stack_on
stack_on_exclude
stack_on_self
uses_calc_time
uses_full_dataframe