Source code for featuretools.primitives.standard.aggregation.time_since_last

from woodwork.column_schema import ColumnSchema
from woodwork.logical_types import Datetime, Double

from featuretools.primitives.base.aggregation_primitive_base import AggregationPrimitive
from featuretools.utils import convert_time_units
from featuretools.utils.gen_utils import Library


[docs]class TimeSinceLast(AggregationPrimitive): """Calculates the time elapsed since the last datetime (default in seconds). Description: Given a list of datetimes, calculate the time elapsed since the last datetime (default in seconds). Uses the instance's cutoff time. Args: unit (str): Defines the unit of time to count from. Defaults to seconds. Acceptable values: years, months, days, hours, minutes, seconds, milliseconds, nanoseconds Examples: >>> from datetime import datetime >>> time_since_last = TimeSinceLast() >>> cutoff_time = datetime(2010, 1, 1, 12, 0, 0) >>> times = [datetime(2010, 1, 1, 11, 45, 0), ... datetime(2010, 1, 1, 11, 55, 15), ... datetime(2010, 1, 1, 11, 57, 30)] >>> time_since_last(times, time=cutoff_time) 150.0 >>> from datetime import datetime >>> time_since_last = TimeSinceLast(unit = "minutes") >>> cutoff_time = datetime(2010, 1, 1, 12, 0, 0) >>> times = [datetime(2010, 1, 1, 11, 45, 0), ... datetime(2010, 1, 1, 11, 55, 15), ... datetime(2010, 1, 1, 11, 57, 30)] >>> time_since_last(times, time=cutoff_time) 2.5 """ name = "time_since_last" input_types = [ColumnSchema(logical_type=Datetime, semantic_tags={"time_index"})] return_type = ColumnSchema(logical_type=Double, semantic_tags={"numeric"}) uses_calc_time = True description_template = "the time since the last {}"
[docs] def __init__(self, unit="seconds"): self.unit = unit.lower()
def get_function(self, agg_type=Library.PANDAS): def time_since_last(values, time=None): time_since = time - values.iloc[-1] return convert_time_units(time_since.total_seconds(), self.unit) return time_since_last