changed default score_colname arg value of splink_score_histogram() from None to match_weight
@@ -122,7 +122,7 @@ def splink_score_histogram(
df_e: DataFrame,
spark: SparkSession,
buckets=None,
- score_colname=None,
+ score_colname=match_weight,
symmetric=True,
):
@@ -134,7 +134,7 @@ def splink_score_histogram(
df_e (DataFrame): A dataframe of record comparisons containing a splink score,
e.g. as produced by the `get_scored_comparisons` function
spark (SparkSession): SparkSession object
- score_colname : is the score in another column? defaults to None
+ score_colname : is the score in another column? defaults to match_weight. also try match_probability
buckets : accepts either a list of split points or an integer number that is used to
create equally spaced split points. It defaults to 100 equally spaced split points from 0.0 to 1.0
symmetric : if True then the histogram is symmetric
