Class SamplingOptions (1.11.0)

Version 1.11.0

• 1.28.0 (latest)
• 1.27.0
• 1.26.0
• 1.25.0
• 1.24.0
• 1.22.0
• 1.21.0
• 1.20.0
• 1.19.0
• 1.18.0
• 1.17.0
• 1.16.0
• 1.15.0
• 1.14.0
• 1.13.0
• 1.12.0
• 1.11.1
• 1.10.0
• 1.9.0
• 1.8.0
• 1.7.0
• 1.6.0
• 1.5.0
• 1.4.0
• 1.3.0
• 1.2.0
• 1.1.0
• 1.0.0
• 0.26.0
• 0.25.0
• 0.24.0
• 0.23.0
• 0.22.0
• 0.21.0
• 0.20.1
• 0.19.2
• 0.18.0
• 0.17.0
• 0.16.0
• 0.15.0
• 0.14.1
• 0.13.0
• 0.12.0
• 0.11.0
• 0.10.0
• 0.9.0
• 0.8.0
• 0.7.0
• 0.6.0
• 0.5.0
• 0.4.0
• 0.3.0
• 0.2.0

SamplingOptions(
    max_download_size: typing.Optional[int] = 500,
    enable_downsampling: bool = False,
    sampling_method: typing.Literal["head", "uniform"] = "uniform",
    random_state: typing.Optional[int] = None,
)

Encapsulates the configuration for data sampling.

Attributes
Name	Description
max_download_size	int, default 500 Download size threshold in MB. If value set to None, the download size won't be checked.
enable_downsampling	bool, default False Whether to enable downsampling, If max_download_size is exceeded when downloading data (e.g., to_pandas()), the data will be downsampled if enable_downsampling is True, otherwise, an error will be raised.
sampling_method	str, default "uniform" Downsampling algorithms to be chosen from, the choices are: "head": This algorithm returns a portion of the data from the beginning. It is fast and requires minimal computations to perform the downsampling.; "uniform": This algorithm returns uniform random samples of the data.
random_state	int, default None The seed for the uniform downsampling algorithm. If provided, the uniform method may take longer to execute and require more computation.