pandas-dev/pandas · error · ValueError

{s} cannot be cast to bool

Error message

{s} cannot be cast to bool

What it means

BooleanArray._from_sequence_of_strings (boolean.py:376) maps each string to True/False/None using configurable true_values/false_values/none_values sets; any string not in those sets raises ValueError naming the offending token. This is the string-to-boolean parsing path used by read_csv/astype on string data.

Source

Thrown at pandas/core/arrays/boolean.py:376

        true_values: list[str] | None = None,
        false_values: list[str] | None = None,
        none_values: list[str] | None = None,
    ) -> BooleanArray:
        true_values_union = cls._TRUE_VALUES.union(true_values or [])
        false_values_union = cls._FALSE_VALUES.union(false_values or [])

        if none_values is None:
            none_values = []

        def map_string(s) -> bool | None:
            if s in true_values_union:
                return True
            elif s in false_values_union:
                return False
            elif s in none_values:
                return None
            else:
                raise ValueError(f"{s} cannot be cast to bool")

        scalars = np.array(strings, dtype=object)
        mask = isna(scalars)
        scalars[~mask] = list(map(map_string, scalars[~mask]))
        return cls._from_sequence(scalars, dtype=dtype, copy=copy)

    _HANDLED_TYPES = (np.ndarray, numbers.Number, bool, np.bool_)

    @classmethod
    def _coerce_to_array(
        cls, value, *, dtype: DtypeObj, copy: bool = False
    ) -> tuple[np.ndarray, np.ndarray]:
        if dtype:
            assert dtype == "boolean"
        return coerce_to_array(value, copy=copy)

    def _logical_method(self, other, op):
        assert op.__name__ in {"or_", "ror_", "and_", "rand_", "xor", "rxor"}

View on GitHub (pinned to 71959b8cb9)

Solutions

1. Pass explicit true_values/false_values/none_values when reading: pd.read_csv(..., true_values=['Y'], false_values=['N']).
2. Pre-map the strings: s.map({'Y': True, 'N': False}).astype('boolean').
3. Normalize whitespace/case before conversion: s.str.strip().str.lower().map(...).
4. Inspect the unique values with s.unique() and extend the mapping sets accordingly.

Example fix

# before
pd.array(["True", "maybe"], dtype="boolean")  # raises on 'maybe'

# after
pd.Series(["True", "maybe"]).map({"True": True, "maybe": None}).astype("boolean")

def parse_bool_strings(strings, true_values=None, false_values=None, none_values=None):
    import pandas as pd
    true_values = set(true_values or [])
    false_values = set(false_values or [])
    none_values = set(none_values or [])
    def m(s):
        if s in true_values or s in {"True","TRUE","true","1","1.0"}: return True
        if s in false_values or s in {"False","FALSE","false","0","0.0"}: return False
        if s in none_values: return None
        raise ValueError(f"{s} cannot be cast to bool")
    return [m(s) for s in strings]

def strings_are_bool_parseable(strings, true_values=None, false_values=None, none_values=None) -> bool:
    try:
        parse_bool_strings(strings, true_values, false_values, none_values)
        return True
    except ValueError:
        return False

try:
    ba = pd.array(strings, dtype="boolean")
except ValueError as e:
    if "cannot be cast to bool" in str(e):
        mapping = {"Y": True, "N": False}
        ba = pd.Series(strings).map(mapping).astype("boolean")
    else:
        raise

When it happens

Trigger: pd.array(['True','maybe'], dtype='boolean'), s.astype('boolean') on a string Series with unrecognized tokens, or read_csv with dtype='boolean' on a column containing values outside true/false/none sets.

Common situations: Datasets with custom boolean encodings ('Y'/'N', 'yes'/'no', 'enabled'/'disabled') without telling pandas the mapping; stray whitespace or case variants; typos in flag columns.

Related errors

• Converting strings to {pa_type} is not implemented.
• Cannot use quantile with bool dtype
• Expected array of boolean type, got {array.type} instead
• cannot pass mask for BooleanArray input
• Need to pass bool-like values

AI-assisted analysis of pandas-dev/pandas@71959b8cb9 (2026-08-07). Data as JSON: /api/errors/4273fe25effd2aad. Report an issue: GitHub.