Python API: sampling

tabalyst.sample_csv() samples one CSV file and tabalyst.generate_samples() several. Sampling reads CSV files only. The command is tabalyst sample.

import tabalyst

sample = tabalyst.sample_csv(
    "customers.csv", method="random", rows=1000, seed=42
)
print(sample.output, sample.sample_rows)
batch = tabalyst.generate_samples(
    ["*.csv"], method="first", rows=100, output_dir="samples"
)

tabalyst.sample_csv()

tabalyst.sample_csv(
    source,
    *,
    method,
    rows=None,
    percent=None,
    field=None,
    seed=None,
    output=None,
    delimiter=",",
    encoding="utf-8-sig",
    force=False,
)

Returns a tabalyst.SampleResult with source, output, method, source_rows, sample_rows, sample_rate, field, seed, encoding and delimiter.

• source: the CSV file.
• method: "first", "last", "random" or "stratified", or a tabalyst.SampleMethod.
• rows, percent: the size of the sample, as a number of data rows or a percentage rounded up to a whole row. Give exactly one.
• field: the field that defines the strata; required by "stratified".
• seed: makes a random or stratified selection reproducible.
• output: the output filename; by default <stem>.sample.csv beside the source.
• delimiter, encoding: how the CSV file is read and written.
• force: replace an existing sample file. A source is never replaced.

tabalyst.generate_samples()

tabalyst.generate_samples(
    input_specs,
    *,
    method,
    rows=None,
    percent=None,
    field=None,
    seed=None,
    output=None,
    output_dir=None,
    delimiter=None,
    encoding=None,
    config_path=None,
    force=False,
)

Returns a batch result whose successes hold a SampleResult each. input_specs are CSV files or non-recursive glob patterns, output names the file of a single source and output_dir the folder of the samples, named <stem>.sample.csv. delimiter and encoding default to the configuration files in config_path, then to the built-in defaults. The other parameters are those of sample_csv().