CountBaselineRows#

from tmlt.tune import CountBaselineRows
class tmlt.tune.CountBaselineRows(*, name=None, description=None, baseline=None, output=None, grouping_columns=None)#

Bases: SingleOutputMetric

Computes the number of rows in the baseline 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 = CountBaselineRows()
>>> metric(dp_outputs, baseline_outputs).value
4
count_baseline_rows(dp_output, baseline_output, result_column_name)#

Counts the number of baseline rows.