def __init__(self, input_col: str, partition_key: str, output_col: str, vocab_df: DataFrame): super().__init__() ExplainBuilder.build(self, inputCol=input_col, partitionKey=partition_key, outputCol=output_col) self._vocab_df = vocab_df
def __init__(self, input_col: str, partition_key: str, output_col: str, reset_per_partition: bool): super().__init__() ExplainBuilder.build(self, inputCol=input_col, partitionKey=partition_key, outputCol=output_col, resetPerPartition=reset_per_partition)
def __init__(self, partition_key: Optional[str], indexed_col_names_arr: List[str], complementset_factor: int): super().__init__() # we assume here that all indices of the columns are continuous within their partition_key ExplainBuilder.build(self, partitionKey=partition_key, indexedColNamesArr=indexed_col_names_arr, complementsetFactor=complementset_factor)
def __init__(self, input_col: str, partition_key: Optional[str], output_col: str, use_pandas: bool = True): super().__init__() ExplainBuilder.build(self, inputCol=input_col, partitionKey=partition_key, outputCol=output_col) self._use_pandas = use_pandas
def __init__(self, input_col: str, partition_key: Optional[str], output_col: str, per_group_stats: Union[DataFrame, Dict[str, float]], use_pandas: bool = True): super().__init__() ExplainBuilder.build(self, inputCol=input_col, partitionKey=partition_key, outputCol=output_col) self._per_group_stats = per_group_stats self._use_pandas = use_pandas
def __init__(self): super().__init__() ExplainBuilder.build(self, inputCol='input', partitionKey=1) self.setSecondPartitionKey(2) self.setOutputCol('output')