Source code for featuretools.primitives.standard.transform.cumulative.cum_mean

import numpy as np
from woodwork.column_schema import ColumnSchema

from featuretools.primitives.base import TransformPrimitive

[docs]class CumMean(TransformPrimitive): """Calculates the cumulative mean. Description: Given a list of values, return the cumulative mean (or running mean). There is no set window, so the mean at each point is calculated over all prior values. `NaN` values will return `NaN`, but in the window of a cumulative caluclation, they're treated as 0. Examples: >>> cum_mean = CumMean() >>> cum_mean([1, 2, 3, 4, None, 5]).tolist() [1.0, 1.5, 2.0, 2.5, nan, 2.5] """ name = "cum_mean" input_types = [ColumnSchema(semantic_tags={"numeric"})] return_type = ColumnSchema(semantic_tags={"numeric"}) uses_full_dataframe = True description_template = "the cumulative mean of {}" def get_function(self): def cum_mean(values): return values.cumsum() / np.arange(1, len(values) + 1) return cum_mean