class_docstr: Abstract base class for graph data generators.
  
  The supplied graph should be a StellarGraph object that is ready for
  machine learning.
  
  Do not use this base class: use a subclass specific to the method.
  
  Args:
      G (StellarGraph): The machine-learning ready graph.
      batch_size (int): Size of batch to return.
      schema (GraphSchema): [Optional] Schema for the graph, for heterogeneous graphs.
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docstr: Creates a generator/sequence object for training or evaluation
  with the supplied node ids and numeric targets.
  
  Args:
      node_targets: a Pandas DataFrame of numeric targets indexed
          by the node ID for that target.
      shuffle (bool): If True the node_ids will be shuffled at each
          epoch, if False the node_ids will be processed in order.
  
  Returns:
      A NodeSequence object to use with with StellarGraph models
      in Keras methods ``fit``, ``evaluate``,
      and ``predict``
code: def flow_from_dataframe(self, node_targets, shuffle=False):
      """
      Creates a generator/sequence object for training or evaluation
      with the supplied node ids and numeric targets.
  
      Args:
          node_targets: a Pandas DataFrame of numeric targets indexed
              by the node ID for that target.
          shuffle (bool): If True the node_ids will be shuffled at each
              epoch, if False the node_ids will be processed in order.
  
      Returns:
          A NodeSequence object to use with with StellarGraph models
          in Keras methods ``fit``, ``evaluate``,
          and ``predict``
  
      """
      return self.flow(
          node_targets.index, node_targets.values, shuffle=shuffle
      )
  
imports: import warnings
  import operator
  import random
  import abc
  import warnings
  import numpy
  import itertools
  import networkx
  import scipy.sparse
  from tensorflow.keras import backend
  from functools import reduce
  from tensorflow.keras.utils import Sequence
  from collections import defaultdict
  from ..data import SampledBreadthFirstWalk, SampledHeterogeneousBreadthFirstWalk, DirectedBreadthFirstNeighbours
  from ..core.graph import StellarGraph, GraphSchema
  from ..core.utils import is_real_iterable
  from ..core.validation import comma_sep
  from .None import NodeSequence, Generator
  from ..random import SeededPerBatch
label_desc: Use image node_id 5 for calling the BatchedNodeGenerator obj's underlying member method code with example usage: obj.flow_from_dataframe(node_targets, shuffle) and returns: self