class_docstr: Class which stores vertex and edge properties that can be used to construct
  Graphs from individual property selections and used later to annotate graph
  algorithm results with corresponding properties.
class_docstr_tok: ["Class","which","stores","vertex","and","edge","properties","that","can","be","used","to","construct","Graphs","from","individual","property","selections","and","used","later","to","annotate","graph","algorithm","results","with","corresponding","properties","."]
docstr: Convert a known vertex vector property in a DataFrame to an array.
  
  Parameters
  ----------
  df : cudf.DataFrame or pandas.DataFrame
      If cudf.DataFrame, the result will be a cupy.ndarray.
      If pandas.DataFrame, the result will be a numpy.ndarray.
  col_name : str
      The column name in the DataFrame to convert to an array.
      This vector property should have been created by PropertyGraph.
  fillvalue : scalar or list, optional (default None)
      Fill value for rows with missing vector data.  If it is a list,
      it must be the correct size of the vector property.  If fillvalue is None,
      then behavior if missing data is controlled by ``missing`` keyword.
      Leave this as None for better performance if all rows should have data.
  missing : {"ignore", "error"}
      If "ignore", empty or null rows without vector data will be skipped
      when creating the array, so output array shape will be
      [# of non-empty rows] by [size of vector property].
      When "error", RuntimeError will be raised if there are any empty rows.
      Ignored if fillvalue is given.
  
  Returns
  -------
  cupy.ndarray or numpy.ndarray
code: def vertex_vector_property_to_array(
      self, df, col_name, fillvalue=None, *, missing="ignore"
  ):
      """Convert a known vertex vector property in a DataFrame to an array.
  
      Parameters
      ----------
      df : cudf.DataFrame or pandas.DataFrame
          If cudf.DataFrame, the result will be a cupy.ndarray.
          If pandas.DataFrame, the result will be a numpy.ndarray.
      col_name : str
          The column name in the DataFrame to convert to an array.
          This vector property should have been created by PropertyGraph.
      fillvalue : scalar or list, optional (default None)
          Fill value for rows with missing vector data.  If it is a list,
          it must be the correct size of the vector property.  If fillvalue is None,
          then behavior if missing data is controlled by ``missing`` keyword.
          Leave this as None for better performance if all rows should have data.
      missing : {"ignore", "error"}
          If "ignore", empty or null rows without vector data will be skipped
          when creating the array, so output array shape will be
          [# of non-empty rows] by [size of vector property].
          When "error", RuntimeError will be raised if there are any empty rows.
          Ignored if fillvalue is given.
  
      Returns
      -------
      cupy.ndarray or numpy.ndarray
      """
      if col_name not in self.__vertex_vector_property_lengths:
          raise ValueError(
              f"{col_name!r} is not a known vertex vector property"
          )
      length = self.__vertex_vector_property_lengths[col_name]
      return self._get_vector_property(
          df, col_name, length, fillvalue, missing
      )
  
imports: import cudf
  import numpy
  import cugraph
  from cugraph.utilities.utils import import_optional, MissingModule, create_list_series_from_2d_ar
  from typing import Union
label_desc: Use image node_id 32 for calling the EXPERIMENTAL__PropertyGraph obj's underlying member method code with example usage: obj.vertex_vector_property_to_array(df, col_name, fillvalue) and returns: self