nxcals.api.extraction.data.builders.DataFrame.freqItems
- DataFrame.freqItems(cols: List[str] | Tuple[str], support: float | None = None) DataFrame
Finding frequent items for columns, possibly with false positives. Using the frequent element count algorithm described in “https://doi.org/10.1145/762471.762473, proposed by Karp, Schenker, and Papadimitriou”.
DataFrame.freqItems()andDataFrameStatFunctions.freqItems()are aliases.Added in version 1.4.0.
Changed in version 3.4.0: Supports Spark Connect.
- Parameters:
cols (list or tuple) – Names of the columns to calculate frequent items for as a list or tuple of strings.
support (float, optional) – The frequency with which to consider an item ‘frequent’. Default is 1%. The support must be greater than 1e-4.
- Returns:
DataFrame with frequent items.
- Return type:
Notes
This function is meant for exploratory data analysis, as we make no guarantee about the backward compatibility of the schema of the resulting
DataFrame.Examples
>>> df = spark.createDataFrame([(1, 11), (1, 11), (3, 10), (4, 8), (4, 8)], ["c1", "c2"]) >>> df.freqItems(["c1", "c2"]).show() +------------+------------+ |c1_freqItems|c2_freqItems| +------------+------------+ | [4, 1, 3]| [8, 11, 10]| +------------+------------+