Shoeboxam · August 19, 2024 15:13
diff --git a/0.11.py b/0.11.py
 import polars as pl
 import opendp.prelude as dp
 dp.enable_features("contrib")

 # set up your analysis
 context = dp.Context.compositor(
    data=pl.scan_csv("pet_species.csv"),
    privacy_unit=dp.unit_of(contributions=1),
    privacy_loss=dp.loss_of(epsilon=1., delta=1e-7),
    split_evenly_over=2)

 # release counts of the number of pets per-species
 query = context.query().group_by("species").agg(
    pl.len().dp.noise()
 )

 # view calibrated scale parameters per-query, accuracy estimate and censoring threshold
 print(query.summarize(alpha=0.05))
 # ┌────────┬───────────┬─────────────────┬───────┬──────────┬───────────┐
 # │ column ┆ aggregate ┆ distribution    ┆ scale ┆ accuracy ┆ threshold │
 # │ ---    ┆ ---       ┆ ---             ┆ ---   ┆ ---      ┆ ---       │
 # │ str    ┆ str       ┆ str             ┆ f64   ┆ f64      ┆ u32       │
 # ╞════════╪═══════════╪═════════════════╪═══════╪══════════╪═══════════╡
 # │ len    ┆ Len       ┆ Integer Laplace ┆ 2.0   ┆ 6.429605 ┆ 33        │
 # └────────┴───────────┴─────────────────┴───────┴──────────┴───────────┘

 print(query.release().collect())
 # ┌─────────┬─────┐
 # │ species ┆ len │
 # │ ---     ┆ --- │
 # │ str     ┆ u32 │
 # ╞═════════╪═════╡
 # │ cat     ┆ 112 │
 # │ dog     ┆ 142 │
 # │ mouse   ┆  45 │
 # └─────────┴─────┘
	import polars as pl
	import opendp.prelude as dp
	dp.enable_features("contrib")

	# set up your analysis
	context = dp.Context.compositor(
	data=pl.scan_csv("pet_species.csv"),
	privacy_unit=dp.unit_of(contributions=1),
	privacy_loss=dp.loss_of(epsilon=1., delta=1e-7),
	split_evenly_over=2)

	# release counts of the number of pets per-species
	query = context.query().group_by("species").agg(
	pl.len().dp.noise()
	)

	# view calibrated scale parameters per-query, accuracy estimate and censoring threshold
	print(query.summarize(alpha=0.05))
	# ┌────────┬───────────┬─────────────────┬───────┬──────────┬───────────┐
	# │ column ┆ aggregate ┆ distribution ┆ scale ┆ accuracy ┆ threshold │
	# │ --- ┆ --- ┆ --- ┆ --- ┆ --- ┆ --- │
	# │ str ┆ str ┆ str ┆ f64 ┆ f64 ┆ u32 │
	# ╞════════╪═══════════╪═════════════════╪═══════╪══════════╪═══════════╡
	# │ len ┆ Len ┆ Integer Laplace ┆ 2.0 ┆ 6.429605 ┆ 33 │
	# └────────┴───────────┴─────────────────┴───────┴──────────┴───────────┘

	print(query.release().collect())
	# ┌─────────┬─────┐
	# │ species ┆ len │
	# │ --- ┆ --- │
	# │ str ┆ u32 │
	# ╞═════════╪═════╡
	# │ cat ┆ 112 │
	# │ dog ┆ 142 │
	# │ mouse ┆ 45 │
	# └─────────┴─────┘