pola-rs/polars · error

expected data of type Sequence, got

Error message

expected data of type Sequence, got {type(data).__name__!r}\n\nHint: Try passing your data to the DataFrame constructor instead, e.g. `pl.DataFrame(data)`.

What it means

pl.from_records requires data to be an instance of collections.abc.Sequence (list, tuple, etc.). Passing a non-sequence such as a dict, set, generator, or numpy array that doesn't qualify raises a TypeError with a hint to use the DataFrame constructor instead.

Solutions

1. Use pl.DataFrame(data) or pl.from_dict(data) for dict-of-columns input.
2. Convert to a list first: pl.from_records(list(data)).
3. For generators: pl.from_records(list(gen)) or pl.DataFrame(gen).
4. For numpy arrays, use pl.DataFrame(arr) or pass arr.tolist().

Example fix

// before
pl.from_records({"a": [1, 2], "b": [3, 4]})
// after
pl.from_dict({"a": [1, 2], "b": [3, 4]})

from collections.abc import Sequence
if not isinstance(data, Sequence):
    raise TypeError("from_records needs a Sequence; use pl.DataFrame/pl.from_dict for other shapes")
pl.from_records(data)

from collections.abc import Sequence, Mapping
def is_record_sequence(v) -> bool:
    return isinstance(v, Sequence) and not isinstance(v, (str, bytes, Mapping))

try:
    df = pl.from_records(data)
except TypeError:
    df = pl.DataFrame(data)  # handles dicts, arrays, generators

When it happens

Trigger: pl.from_records({'a': [1,2]}), pl.from_records(some_set), pl.from_records(some_generator), or passing a dict-of-columns that should go through pl.DataFrame.

Common situations: Confusing from_records (rows as sequences) with from_dict (columns by name); passing generators or sets that were assumed to be 'record-like'; numpy arrays routed to the wrong constructor.

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

• arr.to_struct() got a str instead of a list. hint: pass
• cannot call `map_groups` when filtering groups with `having`
• cannot call `map_groups` when grouping by an expression
• cannot call `map_groups` when grouping by named expressions
• cannot set Series of dtype

AI-assisted analysis of pola-rs/polars@fe841f959e (2026-09-18). Data as JSON: /api/errors/e16133b3af8bd1fd. Report an issue: GitHub.

Appendix: source

Thrown at py-polars/src/polars/convert/general.py:297

    >>> df
    shape: (3, 2)
    ┌─────┬─────┐
    │ a   ┆ b   │
    │ --- ┆ --- │
    │ i64 ┆ i64 │
    ╞═════╪═════╡
    │ 1   ┆ 4   │
    │ 2   ┆ 5   │
    │ 3   ┆ 6   │
    └─────┴─────┘
    """
    if not isinstance(data, Sequence):
        msg = (
            f"expected data of type Sequence, got {type(data).__name__!r}"
            "\n\nHint: Try passing your data to the DataFrame constructor instead,"
            " e.g. `pl.DataFrame(data)`."
        )
        raise TypeError(msg)

    return wrap_df(
        sequence_to_pydf(
            data,
            schema=schema,
            schema_overrides=schema_overrides,
            strict=strict,
            orient=orient,
            infer_schema_length=infer_schema_length,
        )
    )


def from_numpy(
    data: np.ndarray[Any, Any],
    schema: SchemaDefinition | None = None,
    *,
    schema_overrides: SchemaDict | None = None,

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