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snowflake.snowpark.DataFrameStatFunctions.sampleBy¶

DataFrameStatFunctions.sampleBy(col: ColumnOrName, fractions: Dict[LiteralType, float]) → DataFrame[source]¶

Returns a DataFrame containing a stratified sample without replacement, based on a dict that specifies the fraction for each stratum.

Example:

>>> df = session.create_dataframe([("Bob", 17), ("Alice", 10), ("Nico", 8), ("Bob", 12)], schema=["name", "age"])
>>> fractions = {"Bob": 0.5, "Nico": 1.0}
>>> sample_df = df.stat.sample_by("name", fractions)  # non-deterministic result
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Parameters:
  • col – The name of the column that defines the strata.

  • fractions – A dict that specifies the fraction to use for the sample for each stratum. If a stratum is not specified in the dict, the method uses 0 as the fraction.