pola-rs/polars · error · TypeError

cannot use Series of dtype

Error message

cannot use Series of dtype {key.dtype!r} for indexing; expected boolean or integer dtype

What it means

Series.__setitem__ raises this TypeError when the key is a Series whose dtype is neither Boolean (mask) nor integer (indices). Only boolean masks and integer index Series are valid for set/scatter operations; e.g. a Float64 or Str Series key is rejected.

Solutions

1. Cast an index Series to integer: `series[key.cast(pl.Int64)] = value`
2. Convert a float mask to Boolean: `series[(values > 0)] = value` using a boolean expression
3. If using floats as positions, round/cast them: `series[key.round().cast(pl.Int32)] = value`

Example fix

// before
s[idx_float_series] = 5  # TypeError
// after
s[idx_float_series.cast(pl.Int64)] = 5

if isinstance(key, pl.Series) and key.dtype != pl.Boolean and not key.dtype.is_integer():
    key = key.cast(pl.Int64)
series[key] = value

def is_valid_key(key: pl.Series) -> bool:
    return key.dtype == pl.Boolean or key.dtype.is_integer()

try:
    series[key] = value
except TypeError as e:
    if "for indexing" in str(e):
        series[key.cast(pl.Int64)] = value
    else:
        raise

When it happens

Trigger: `series[float_series_or_str_series] = value` — the key Series dtype fails both `key.dtype == Boolean` and `key.dtype.is_integer()` at py-polars/src/polars/series/series.py:1441.

Common situations: Using float position indices from another computation; mistakenly indexing by a string-valued Series; result of a join/computation left as Float64 indices.

Understand the failure class

Background: Type mismatch errors: IllegalArgumentException, TypeError and type guards across 150 open-source libraries — this error's family across 150 libraries.

Related errors

• cannot compare datetime.datetime to Series of type
• cannot construct PySeries for type
• cannot convert DataFrame to
• cannot convert List column
• cannot convert Python type

AI-assisted analysis of pola-rs/polars@fe841f959e (2026-09-18). Data as JSON: /api/errors/edbe72ccf340b626. Report an issue: GitHub.

Appendix: source

Thrown at py-polars/src/polars/series/series.py:1441

            self.scatter(key, value)
            return None
        elif isinstance(value, Sequence) and not isinstance(value, str):
            if self.dtype.is_numeric() or self.dtype.is_temporal():
                self.scatter(key, value)  # type: ignore[arg-type]
                return None
            msg = (
                f"cannot set Series of dtype: {self.dtype!r} with list/tuple as value;"
                " use a scalar value"
            )
            raise TypeError(msg)
        if isinstance(key, Series):
            if key.dtype == Boolean:
                self._s = self.set(key, value)._s
            elif key.dtype.is_integer():
                self._s = self.scatter(key, value)._s
            else:
                msg = f"cannot use Series of dtype {key.dtype!r} for indexing; expected boolean or integer dtype"
                raise TypeError(msg)

        # TODO: implement for these types without casting to series
        elif _check_for_numpy(key) and isinstance(key, np.ndarray):
            if key.dtype == np.bool_:
                # boolean numpy mask
                self._s = self.scatter(np.argwhere(key)[:, 0], value)._s
            else:
                s = self._from_pyseries(
                    PySeries.new_u32("", np.array(key, np.uint32), _strict=True)
                )
                self.__setitem__(s, value)
        elif isinstance(key, (list, tuple)):
            s = self._from_pyseries(sequence_to_pyseries("", key, dtype=UInt32))
            self.__setitem__(s, value)
        else:
            msg = f'cannot use "{key!r}" for indexing'
            raise TypeError(msg)

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