pyspark.sql.DataFrame.freqItems¶
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DataFrame.freqItems(cols, support=None)[source]¶
- 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()and- DataFrameStatFunctions.freqItems()are aliases.- New in version 1.4.0. - Parameters
- colslist or tuple
- Names of the columns to calculate frequent items for as a list or tuple of strings. 
- supportfloat, optional
- The frequency with which to consider an item ‘frequent’. Default is 1%. The support must be greater than 1e-4. 
 
 - 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.