parameters: (
          self, n: int = 2, delimiter: str = " ", separator: str = "_"
      )
return_statement: return self._return_or_inplace(
              libstrings.ngrams_tokenize(self._column, n, delimiter, separator),
              retain_index=False,
          )
docstring: Generate the n-grams using tokens from each string.
          This will tokenize each string and then generate ngrams for each
          string.
  
          Parameters
          ----------
          n : int, Default 2.
              The degree of the n-gram (number of consecutive tokens).
          delimiter : str, Default is white-space.
              The character used to locate the split points of each string.
          sep : str, Default is '_'.
              The separator to use between tokens within an n-gram.
  
          Returns
          -------
          Series or Index of object.
  
          Examples
          --------
          >>> import cudf
          >>> ser = cudf.Series(['this is the', 'best book'])
          >>> ser.str.ngrams_tokenize(n=2, sep='_')
          0      this_is
          1       is_the
          2    best_book
          dtype: object
docstring_summary: Generate the n-grams using tokens from each string.
          This will tokenize each string and then generate ngrams for each
          string.
docstring_tokens: Generate the n - grams using tokens from each string . This will tokenize each string and then generate ngrams for each string .
function: def ngrams_tokenize(
          self, n: int = 2, delimiter: str = " ", separator: str = "_"
      ) -> SeriesOrIndex:
          """
          Generate the n-grams using tokens from each string.
          This will tokenize each string and then generate ngrams for each
          string.
  
          Parameters
          ----------
          n : int, Default 2.
              The degree of the n-gram (number of consecutive tokens).
          delimiter : str, Default is white-space.
              The character used to locate the split points of each string.
          sep : str, Default is '_'.
              The separator to use between tokens within an n-gram.
  
          Returns
          -------
          Series or Index of object.
  
          Examples
          --------
          >>> import cudf
          >>> ser = cudf.Series(['this is the', 'best book'])
          >>> ser.str.ngrams_tokenize(n=2, sep='_')
          0      this_is
          1       is_the
          2    best_book
          dtype: object
          """
          delimiter = _massage_string_arg(delimiter, "delimiter")
          separator = _massage_string_arg(separator, "separator")
          return self._return_or_inplace(
              libstrings.ngrams_tokenize(self._column, n, delimiter, separator),
              retain_index=False,
          )
function_tokens: def ngrams_tokenize ( self , n : int = 2 , delimiter : str = " " , separator : str = "_" ) -> SeriesOrIndex : delimiter = _massage_string_arg ( delimiter , "delimiter" ) separator = _massage_string_arg ( separator , "separator" ) return self . _return_or_inplace ( libstrings . ngrams_tokenize ( self . _column , n , delimiter , separator ) , retain_index = False , )