sample
Returns a sampled subset of this DataFrame.
Syntax
sample(withReplacement: Optional[Union[float, bool]] = None, fraction: Optional[Union[int, float]] = None, seed: Optional[int] = None)
Parameters
Parameter | Type | Description |
|---|---|---|
| bool, optional | Sample with replacement or not (default |
| float, optional | Fraction of rows to generate, range [0.0, 1.0]. |
| int, optional | Seed for sampling (default a random seed). |
Returns
DataFrame: Sampled rows from given DataFrame.
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
Python
df = spark.range(0, 10, 1, 1)
df.sample(0.5, 3).count()
# 7
df.sample(fraction=0.5, seed=3).count()
# 4
df.sample(withReplacement=True, fraction=0.5, seed=3).count()
# 2
df.sample(1.0).count()
# 10
df.sample(fraction=1.0).count()
# 10
df.sample(False, fraction=1.0).count()
# 10