group_zscore(frame, group, name=None, metadata=None)

Return row-wise z-scores within each group.

Parameters

frame : Panel | Graph
Input numeric Panel or single-output Graph. group : Panel | Graph
Matching CategoryPanel containing row-wise group labels. name : str | None, default None
Optional graph-node name. A generated name is used when omitted. metadata : Mapping[str, Any] | None, default None
Optional metadata stored on the graph node.

Returns

Graph
Lazy single-output graph. Call .compute() to materialize a Panel.

Examples

import polars as pl

from bagelquant_core import CategoryPanel, Domain, Panel
from bagelquant_core.composer import group_zscore

domain = Domain(calendar=["2024-01-02"], universe=["a", "b", "c"])
factor = Panel.from_domain(
    pl.DataFrame({
        "time": ["2024-01-02"] * 3,
        "asset_id": ["a", "b", "c"],
        "value": [1.0, 3.0, 8.0],
    }),
    domain,
)
industry = CategoryPanel.from_domain(
    pl.DataFrame({
        "time": ["2024-01-02"] * 3,
        "asset_id": ["a", "b", "c"],
        "value": ["tech", "tech", "bank"],
    }),
    domain,
)

result = group_zscore(factor, industry).compute().data
print(result)

Notes

Inputs are aligned by (time, asset_id) before the operation runs.

Missing group labels are excluded from the group calculation.