tf.estimator.inputs.pandas_input_fn

tf.estimator.inputs.pandas_input_fn(
    x,
    y=None,
    batch_size=128,
    num_epochs=1,
    shuffle=None,
    queue_capacity=1000,
    num_threads=1,
    target_column='target'
)

Defined in tensorflow/python/estimator/inputs/pandas_io.py.

Returns input function that would feed Pandas DataFrame into the model.

Args:

  • x: pandas DataFrame object.
  • y: pandas Series object. None if absent.
  • batch_size: int, size of batches to return.
  • num_epochs: int, number of epochs to iterate over data. If not None, read attempts that would exceed this value will raise OutOfRangeError.
  • shuffle: bool, whether to read the records in random order.
  • queue_capacity: int, size of the read queue. If None, it will be set roughly to the size of x.
  • num_threads: Integer, number of threads used for reading and enqueueing. In order to have predicted and repeatable order of reading and enqueueing, such as in prediction and evaluation mode, num_threads should be 1.
  • target_column: str, name to give the target column y.

Returns:

Function, that has signature of ()->(dict of features, target)

Raises:

  • ValueError: if x already contains a column with the same name as y, or if the indexes of x and y don't match.
  • ValueError: if 'shuffle' is not provided or a bool.