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()