def __init__(self, dtype, missing_value, name, doc, metadata, currency_aware): # Validating and calculating default missing values here guarantees # that we fail quickly if the user passes an unsupporte dtype or fails # to provide a missing value for a dtype that requires one # (e.g. int64), but still enables us to provide an error message that # points to the name of the failing column. try: self.dtype, self.missing_value = validate_dtype( termname="Column(name={name!r})".format(name=name), dtype=dtype, missing_value=missing_value, ) except NoDefaultMissingValue: # Re-raise with a more specific message. raise NoDefaultMissingValue( "Failed to create Column with name {name!r} and" " dtype {dtype} because no missing_value was provided\n\n" "Columns with dtype {dtype} require a missing_value.\n" "Please pass missing_value to Column() or use a different" " dtype.".format(dtype=dtype, name=name)) self.name = name self.doc = doc self.metadata = metadata self.currency_aware = currency_aware
def __init__(self, dtype, missing_value, name): # Validating and calculating default missing values here guarantees # that we fail quickly if the user passes an unsupporte dtype or fails # to provide a missing value for a dtype that requires one # (e.g. int64), but still enables us to provide an error message that # points to the name of the failing column. try: self.dtype, self.missing_value = validate_dtype( termname="Column(name={name!r})".format(name=name), dtype=dtype, missing_value=missing_value, ) except NoDefaultMissingValue: # Re-raise with a more specific message. raise NoDefaultMissingValue( "Failed to create Column with name {name!r} and" " dtype {dtype} because no missing_value was provided\n\n" "Columns with dtype {dtype} require a missing_value.\n" "Please pass missing_value to Column() or use a different" " dtype.".format(dtype=dtype, name=name) ) self.name = name