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featurebyte.HistoricalFeatureTable.sample

sample(
size: int=10,
seed: int=1234
) -> DataFrame

Description

Returns a DataFrame that contains a random selection of rows of the historical feature table based on a specified size and seed for sampling control.

Parameters

  • size: int
    default: 10
    Maximum number of rows to sample, with an upper bound of 10,000 rows.

  • seed: int
    default: 1234
    Seed to use for random sampling.

Returns

  • DataFrame
    Sampled rows from the table.

Examples

>>> historical_feature_table = catalog.get_historical_feature_table(
...     "historical_feature_table_name"
... )  # doctest: +SKIP
>>> historical_feature_table.sample()