class_docstr: Model fitted by FPGrowth.
  
  .. versionadded:: 2.2.0
class_docstr_tok: ["Model","fitted","by","FPGrowth",".","..","versionadded",":",":","2.2.0"]
docstr: DataFrame with two columns:
  * `items` - Itemset of the same type as the input column.
  * `freq`  - Frequency of the itemset (`LongType`).
docstr_tok: ["DataFrame","with","two","columns",":","*","`","items","`","-","Itemset","of","the","same","type","as","the","input","column",".","*","`","freq","`","-","Frequency","of","the","itemset","(","`","LongType","`",")","."]
code: def freqItemsets(self) -> DataFrame:
      """
      DataFrame with two columns:
      * `items` - Itemset of the same type as the input column.
      * `freq`  - Frequency of the itemset (`LongType`).
      """
      return self._call_java("freqItemsets")
  
imports: import sys
  from typing import Any, Dict, Optional, TYPE_CHECKING
  from pyspark import keyword_only, since
  from pyspark.sql import DataFrame
  from pyspark.ml.util import JavaMLWritable, JavaMLReadable
  from pyspark.ml.wrapper import JavaEstimator, JavaModel, JavaParams
  from pyspark.ml.param.shared import HasPredictionCol, Param, TypeConverters, Params
label_desc: Use image node_id 4 for calling the FPGrowthModel obj's underlying member method code with example usage: obj.freqItemsets() and returns: self