tf.compat.v1.estimator.inputs.pandas_input_fn

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

tf.compat.v1.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'
)

Note: y's index must match x's index.

Args:

x: pandas DataFrame object.
y: pandas Series object or DataFrame. 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. This parameter is not used when y is a DataFrame.

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.