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

import numpy as np
from woodwork.column_schema import ColumnSchema

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



[docs]class Min(AggregationPrimitive):
    """Calculates the smallest value, ignoring `NaN` values.

    Examples:
        >>> min = Min()
        >>> min([1, 2, 3, 4, 5, None])
        1.0
    """

    name = "min"
    input_types = [ColumnSchema(semantic_tags={"numeric"})]
    return_type = ColumnSchema(semantic_tags={"numeric"})
    stack_on_self = False
    compatibility = [Library.PANDAS, Library.DASK, Library.SPARK]
    description_template = "the minimum of {}"

    def get_function(self, agg_type=Library.PANDAS):
        if agg_type in [Library.DASK, Library.SPARK]:
            return "min"

        return np.min