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.
  
  
• 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")
>>> historical_feature_table.sample()