pola-rs/polars · error

cannot select elements using Sequence with elements of type

Error message

cannot select elements using Sequence with elements of type {qualified_type_name(first)!r}

What it means

Polars' Series.__getitem__ (get_series_item_by_key) was given a Python Sequence (list/tuple) whose first element is neither int, str, nor bool-castable numeric, so it cannot be interpreted as Int64 indices. Polars deliberately refuses instead of guessing, raising TypeError after pl.Series(key, dtype=Int64) fails. Only integer sequences (or booleans, handled earlier) are accepted for element selection.

Solutions

1. Use all-int lists for row selection: s[[0, 2, 4]].
2. Select columns on a DataFrame with all-str lists instead: df[['a', 'b']].
3. Cast floats to int explicitly before indexing: s[[int(i) for i in my_indices]].
4. Filter None/NaN out of the index list before indexing.
5. Use Series.filter() or slice/gather for programmatic element selection.

Example fix

// before
s[[0, 1.0, 'x']]
// after
s[[0, 1]]  # or s[s.to_list() ...] after cleaning/casting indices

def is_int_sequence(key):
    return isinstance(key, (list, tuple)) and all(isinstance(x, int) and not isinstance(x, bool) for x in key)
if not is_int_sequence(idx):
    idx = [int(x) for x in idx if x is not None]
series[idx]

def is_int_index_list(key: object) -> bool:
    return isinstance(key, (list, tuple)) and len(key) > 0 and all(isinstance(x, int) and not isinstance(x, bool) for x in key)

try:
    out = series[key]
except TypeError as e:
    if 'cannot select elements' in str(e):
        out = series[[int(x) for x in key if isinstance(x, (int, float)) and x is not None]]
    else:
        raise

When it happens

Trigger: s[[1, 'a']]; s[('a', 'b')]; s[[None]]; s[[1.5]] passed to Series getitem where the first sequence element fails Series(key, dtype=Int64) construction; also df[some_list] where the list contains non-int, non-str elements routed to series element selection.

Common situations: Mixing column names and row indices in one indexing list; passing float or None values in a list intended as indices; copying pandas-style mixed indexing like df[[0, 'col']]; typos where a float index (1.0) sneaks in from upstream computation.

Understand the failure class

Background: "Must be a positive integer", "Invalid value", "Unsupported": the invalid-argument-value error family, when a library rejects the value you pass — this error's family across 35 libraries.

Related errors

• can't convert to Decimal
• cannot select elements using key of type
• `arctan2` expected a `str` or `Expr` got a
• `arctan2` expected a `str` or `Expr` got a
• can only call '.item()' if the Series is of length 1, or an…

AI-assisted analysis of pola-rs/polars@fe841f959e (2026-09-18). Data as JSON: /api/errors/c3b483410dd71306. Report an issue: GitHub.

Appendix: source

Thrown at py-polars/src/polars/_utils/getitem.py:76

        return _select_elements_by_slice(s, key)

    elif isinstance(key, range):
        key = range_to_slice(key)
        return _select_elements_by_slice(s, key)

    elif isinstance(key, Sequence):
        if not key:
            return s.clear()

        first = key[0]
        if isinstance(first, bool):
            _raise_on_boolean_mask()

        try:
            indices = pl.Series("", key, dtype=Int64)
        except TypeError:
            msg = f"cannot select elements using Sequence with elements of type {qualified_type_name(first)!r}"
            raise TypeError(msg) from None

        indices = _convert_series_to_indices(indices, s.len())
        return _select_elements_by_index(s, indices)

    elif isinstance(key, pl.Series):
        indices = _convert_series_to_indices(key, s.len())
        return _select_elements_by_index(s, indices)

    elif _check_for_numpy(key) and isinstance(key, np.ndarray):
        indices = _convert_np_ndarray_to_indices(key, s.len())
        return _select_elements_by_index(s, indices)

    msg = f"cannot select elements using key of type {qualified_type_name(key)!r}: {key!r}"
    raise TypeError(msg)


def _select_elements_by_slice(s: Series, key: slice) -> Series:
    return PolarsSlice(s).apply(key)  # type: ignore[return-value]

View on GitHub (pinned to fe841f959e)