tfdv.DecodeCSV

Decodes CSV records into Arrow RecordBatches.

tfdv.DecodeCSV(
    column_names: List[types.FeatureName],
    delimiter: Text = ',',
    skip_blank_lines: bool = True,
    schema: Optional[schema_pb2.Schema] = None,
    desired_batch_size: Optional[int] = constants.DEFAULT_DESIRED_INPUT_BATCH_SIZE,
    multivalent_columns: Optional[List[types.FeatureName]] = None,
    secondary_delimiter: Optional[Union[Text, bytes]] = None
)

DEPRECATED: please use tfx_bsl.public.CsvTFXIO instead.

Args
`column_names`	List of feature names. Order must match the order in the CSV file.
`delimiter`	A one-character string used to separate fields.
`skip_blank_lines`	A boolean to indicate whether to skip over blank lines rather than interpreting them as missing values.
`schema`	An optional schema of the input data. If provided, types will be inferred from the schema. If this is provided, the feature names must equal column_names.
`desired_batch_size`	Batch size. The output Arrow RecordBatches will have as many rows as the `desired_batch_size`.
`multivalent_columns`	Name of column that can contain multiple values.
`secondary_delimiter`	Delimiter used for parsing multivalent columns.

Class Variables
pipeline	`None`

tfdv.DecodeCSV

Args

Class Variables