pyspark.sql.DataFrame.sample¶
-
DataFrame.sample(withReplacement: Union[float, bool, None] = None, fraction: Union[int, float, None] = None, seed: Optional[int] = None) → pyspark.sql.dataframe.DataFrame¶ Returns a sampled subset of this
DataFrame.- Parameters
- withReplacementbool, optional
Sample with replacement or not (default
False).- fractionfloat, optional
Fraction of rows to generate, range [0.0, 1.0].
- seedint, optional
Seed for sampling (default a random seed).
Notes
This is not guaranteed to provide exactly the fraction specified of the total count of the given
DataFrame.fraction is required and, withReplacement and seed are optional.
Examples
>>> df = spark.range(10) >>> df.sample(0.5, 3).count() 7 >>> df.sample(fraction=0.5, seed=3).count() 7 >>> df.sample(withReplacement=True, fraction=0.5, seed=3).count() 1 >>> df.sample(1.0).count() 10 >>> df.sample(fraction=1.0).count() 10 >>> df.sample(False, fraction=1.0).count() 10