class_docstr: This transformer parses text into tabular representation. The input consists of DOCUMENT annotations and the
  output are TABLE annotations. The source format can be either JSON or CSV. The CSV format support alternative
  delimiters (e.g. tab), as well as escaping delimiters by surrounding cell values with double quotes.
  
  The transformer stores tabular data internally as JSON. The default input format is also JSON.
  
  ====================== ======================
  Input Annotation types Output Annotation type
  ====================== ======================
  ``DOCUMENT``           ``TABLE``
  ====================== ======================
  
  Parameters
  ----------
      inputFormat
          The format of the source representation of the table ('json' or 'csv')
  
      csvDelimiter
          The delimiter used for parsing CSV files (defailt is comma)
  
      escapeCsvDelimiter
          Whether to escape Csv delimiter by surrounding values with double quotes
  
  Examples
  --------
  >>> import sparknlp
  >>> from sparknlp.base import *
  >>> from sparknlp.annotator import *
  >>> from pyspark.ml import Pipeline
  >>>
  >>> document_assembler = DocumentAssembler() \
  ...     .setInputCol("table_csv") \
  ...     .setOutputCol("document_table")
  >>> table_assembler = TableAssembler()\
  >>>     .setInputFormat("csv")\
  >>>     .setInputCols(["document_table"])\
  >>>     .setOutputCol("table")
  >>>
  >>> csv_data = "\n".join([
  >>> "name, money, age",
  >>> "Donald Trump, "100,000,000", 75",
  >>> "Elon Musk, "20,000,000,000,000", 55"])
  >>> data = spark.createDataFrame([[csv_data]]) \
  ...    .toDF("table_csv")
  >>> pipeline = Pipeline().setStages([
  ...     document_assembler,
   ...     table_assembler
  ... ]).fit(data)
  >>> result = pipeline.transform(data)
  >>> result.select("table").show(truncate=False)
  +-----------------------------------------------+
  |table                                          |
  +-----------------------------------------------+
  |[[table, 0, 118, {                             |
  |   "header":["name","money","age"],            |
  |   "rows":[                                    |
  |    ["Donald Trump","100,000,000","75"],       |
  |    ["Elon Musk","20,000,000,000,000","55"]]   |
  | },                                            |
  | [sentence -> 0, input_format -> csv], []]]    |
  +-----------------------------------------------+
docstr: Sets the CSV delimiter.
  
  Parameters
  ----------
  value : str
      CSV delimiter
docstr_tok: ["Sets","the","CSV","delimiter",".","Parameters","--","--","--","--","--","value",":","str","CSV","delimiter"]
code: def setCsvDelimiter(self, value):
      """Sets the CSV delimiter.
  
      Parameters
      ----------
      value : str
          CSV delimiter
      """
      return self._set(csvDelimiter=value)
  
imports: from sparknlp.common import *
label_desc: Use image node_id 2 for calling the TableAssembler obj's underlying member method code with example usage: obj.setCsvDelimiter(value) and returns: self