snowflake.snowpark.DataFrameStatFunctions.sample_by

DataFrameStatFunctions.sample_by(col: Union[Column, str], fractions: Dict[Union[None, bool, int, float, str, bytearray, Decimal, date, datetime, time, bytes, NaTType, float64, list, tuple, dict], float], seed: Optional[int] = None) → 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.

  • seed – Specifies a seed value to make the sampling deterministic. Can be any integer between 0 and 2147483647 inclusive. Default value is None. This parameter is only supported for Table, and it will be ignored if it is specified for :class`DataFrame`.

言語: 日本語