Alias to create feature. Infers the feature type based on init parameters.

Feature for dataframe that is equivalent to underlying column

Stores all actual data and typing information for an entityset Attributes: id dataframe_dict relationships t

Automatically produce features for a target dataframe in an Entityset. Args: target_dataframe_name (str): Name of dataframe for which to

Feature for child dataframe that inherits a feature value from a parent dataframe

Represents an immutable set of features to be calculated for a single dataframe, and their dependencies.

Represents differences in time. Timedeltas can be defined in multiple units. Supported units: - "ms" : milliseconds - "s" : seconds

Calculates the values of a set of features for given instance ids.

Determines the `n` most common elements. Description: Given a list of values, return the `n` values which appear the most frequen

Class to represent a relationship between dataframes See Also: :class:`.EntitySet`

A trie (prefix tree) where the keys are sequences of hashable objects. It behaves similarly to a dictionary, except that the keys can be lis

Determines the number of values that fall outside a certain range. Args: lower (float): Lower boundary of range (exclusive). Default is 0

Shifts an array of values by a specified number of periods. Args: periods (int): The number of periods by which to shift the input.

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

Performs element-wise addition of two lists. Description: Given a list of values X and a list of values Y, determine the sum of e

Transforms time of an instance into the holiday name, if there is one. Description: If there is no holiday, it returns `NaN`. Currently o

Calculates the highest value, ignoring `NaN` values. Examples: >>> max = Max() >>> max([1, 2, 3, 4, 5, None]) 5.0

Calculates the absolute difference from the previous element in a list of numbers. Description: The absolute difference from the p

Determines if a given datetime is a federal holiday. Description: This primtive currently only works for the United States and Ca

Computes the number of days before or after a given holiday. Description: For a list of dates, return the distance from the nearest

Determines the domain of an email Description: EmailAddress input should be a string. Will return Nan if an invalid email address

Determines if an email address is from a free email domain. Description: EmailAddress input should be a string. Will return Nan i

Determines the maximum number of consecutive negative values in the input Args: skipna (bool): Ignore any `NaN` values in the input. Defa

Determines the maximum number of consecutive positive values in the input Args: skipna (bool): Ignore any `NaN` values in the input. Defa

Determines the maximum number of consecutive zero values in the input Args: skipna (bool): Ignore any `NaN` values in the input. Default

Computes the average for a list of values. Args: skipna (bool): Determines if to use NA/null values. Defaults to True to skip

Calculates time from a value to a specified cutoff datetime. Args: unit (str): Defines the unit of time to count from. Defaul

Computes the exponentially weighted moving average for a series of numbers Description: Returns the exponentially weighted moving average

Computes the exponentially weighted moving standard deviation for a series of numbers Description: Returns the exponentially weighted

Computes the exponentially weighted moving variance for a series of numbers Description: Returns the exponentially weighted moving varian

Determines the quarter a datetime column falls into (1, 2, 3, 4) Examples: >>> from datetime import datetime >>> dates = [datetim

Determines the total number of values, excluding `NaN`. Examples: >>> count = Count() >>> count([1, 2, 3, 4, 5, None]) 5

Class to access specific multi output feature column

Determines whether a value is present in a provided list. Examples: >>> items = ['string', 10.3, False] >>> is_in = IsIn(list_of_

Multiplies each element in the list by a scalar. Description: Given a list of numeric values and a scalar, multiply each value in

Computes the absolute value of a number. Examples: >>> absolute = Absolute() >>> absolute([3.0, -5.0, -2.4]).tolist() [3.

Calculates the age in years as a floating point number given a date of birth. Description: Age in years is computed by calculating

Determines the average count across all unique value. Args: skipna (bool): Determines if to use NA/null values. Defaults to T

Calculates the distance between points in a city road grid. Description: This distance is calculated using the haversine formula, which

Determines the timezone of a datetime. Description: Given a list of datetimes, extract the timezone from each one. Looks for the

Determines the geographic center of two coordinates. Examples: >>> geomidpoint = GeoMidpoint() >>> geomidpoint([(42.4, -71.1)], [

Determines if values are greater than a given scalar. Description: Given a list of values and a constant scalar, determine whethe

Determines a rolling count of events over a given window. Description: Given a list of datetimes, return a rolling count starting

A primitive that should currently exist for testing.

Calculates the approximate haversine distance between two LatLong columns. Args: unit (str): Determines the unit value to output. Could

Determines the maximum number of consecutive False values in the input Examples: >>> max_consecutive_false = MaxConsecutiveFalse()

Determines the maximum number of consecutive True values in the input Examples: >>> max_consecutive_true = MaxConsecutiveTrue() >

Performs element-wise multiplication of a numeric list with a boolean list. Description: Given a list of numeric values X and a list of

This class wraps a cache and a generator which iterates over all primitive classes. When deserializing a primitive if it is not in the cache

Computes the rate of change of a value per second. Examples: >>> import pandas as pd >>> rate_of_change = RateOfChange()

Calculates the trend of a given window of entries of a column over time. Description: Given a list of numbers and a corresponding list of

Determines the season of a given datetime. Returns winter, spring, summer, or fall. This only works for northern hemisphere. Desc

Determines the domain of a url. Description: Calculates the label to identify the network domain of a URL. Supports urls with or

Determines the protocol (http or https) of a url. Description: Extract the protocol of a url using regex. It will be either https

Determines the top level domain of a url. Description: Extract the top level domain of a url, using regex, and a list of common t

Calculates the cumulative sum. Description: Given a list of values, return the cumulative sum (or running total). There is no set

Divides a scalar by each value in the list. Description: Given a list of numeric values and a scalar, divide the scalar by each v

Performs element-wise division of two lists. Description: Given a list of values X and a list of values Y, determine the quotient

Divides each element in the list by a scalar. Description: Given a list of numeric values and a scalar, divide each value in the

Computes the expanding count of events over a given window. Description: Given a list of datetimes, returns an expanding count starting

Determines the extension of a filepath. Description: Given a list of filepaths, return the extension suffix of each one. If the f

Determines if coordinates are inside a box defined by two corner coordinate points. Description: Coordinate values should be specifie

Determines if a datetime falls during configurable lunch hour, on a 24-hour clock. Args: lunch_hour (int): Hour when lunch is taken. Must

Determines if a datetime falls during working hours on a 24-hour clock. Can configure start_hour and end_hour. Args: start_hour (int): St

Negates a numeric value. Examples: >>> negate = Negate() >>> negate([1.0, 23.2, -7.0]).tolist() [-1.0, -23.2, 7.0]

Determines the number of distinct values, ignoring `NaN` values. Args: use_string_for_pd_calc (bool): Determines if the string 'nunique'

Determines the number of common words in a string. Description: Given string, determine the number of words that appear in a supplied wor

Shifts an array of values by a specified number of periods. Args: periods (int): The number of periods by which to shift the input.

Calculates the standard deviation of entries over a given window. Description: Given a list of numbers and a corresponding list of

Calculates the time elapsed since the last datetime (default in seconds). Description: Given a list of datetimes, calculate the t

Calculates the trend of a column over time. Description: Given a list of values and a corresponding list of datetimes, calculate

Determines the day of the month from a datetime. Examples: >>> from datetime import datetime >>> dates = [datetime(2019, 3, 1),

Determines the ordinal day of the year from the given datetime Description: For a list of dates, return the ordinal day of the year

Determines the number of days in the month of given datetime. Examples: >>> from datetime import datetime >>> dates = [datetime(2

Computes the difference between the value in a list and the previous value in that list. Args: periods (int): The number of periods b

Computes the timedelta between a datetime in a list and the previous datetime in that list. Args: periods (int): The number of period

Determines if values in a list are equal to a given scalar. Description: Given a list of values and a constant scalar, determine

Computes the expanding maximum of events over a given window. Description: Given a list of datetimes, returns an expanding maximum starti

Computes the expanding mean of events over a given window. Description: Given a list of datetimes, returns an expanding mean starting

Computes the expanding minimum of events over a given window. Description: Given a list of datetimes, returns an expanding minimum starti