CountDPRows

from tmlt.tune import CountDPRows

class tmlt.tune.CountDPRows(*, name=None, description=None, baseline=None, output=None, grouping_columns=None)

Bases: SingleOutputMetric

Computes the number of rows in the DP output.

If grouped, will return a count for every group that appears in either the DP or baseline output.

Example

>>> dp_df = spark.createDataFrame(
...     pd.DataFrame(
...         {
...             "A": ["a1", "a2", "a3"],
...             "X": [50, 110, 100]
...         }
...     )
... )
>>> dp_outputs = {"O": dp_df}
>>> baseline_df = spark.createDataFrame(
...     pd.DataFrame(
...         {
...             "A": ["a1", "a2", "a3", "b"],
...             "X": [100, 100, 100, 50]
...         }
...     )
... )
>>> baseline_outputs = {"default": {"O": baseline_df}}

>>> metric = CountDPRows()
>>> metric(dp_outputs, baseline_outputs).value
3

count_dp_rows(dp_output, baseline_output, result_column_name)

Counts the number of DP rows.