sf_quant.data.load_assets_by_date

sf_quant.data.load_assets_by_date(date_: date, in_universe: bool, columns: list[str]) → DataFrame

Load a Polars DataFrame of assets data for a single date.

Parameters

date_datetime.date

Date of the data frame.

in_universebool

If True, restrict to assets that are in the universe. If False, include all assets.

columnslist of str

List of column names to include in the result.

Returns

polars.DataFrame

A DataFrame containing asset data on the specified date, filtered by universe membership if requested, with only the selected columns.

Examples

>>> import sf_quant as sf
>>> import datetime as dt
>>> date_ = dt.date(2024, 1, 3)
>>> columns = ["barrid", "date", "price"]
>>> df = sf.data.load_assets_by_date(
...     date_=date_,
...     in_universe=True,
...     columns=columns
... )
>>> df.head()
shape: (5, 3)
┌────────────┬─────────┬───────┐
│ date       ┆ barrid  ┆ price │
│ ---        ┆ ---     ┆ ---   │
│ date       ┆ str     ┆ f64   │
╞════════════╪═════════╪═══════╡
│ 2024-01-03 ┆ USA06Z1 ┆ 7.775 │
│ 2024-01-03 ┆ USA0771 ┆ 10.23 │
│ 2024-01-03 ┆ USA0C11 ┆ 74.15 │
│ 2024-01-03 ┆ USA0SY1 ┆ 130.1 │
│ 2024-01-03 ┆ USA11I1 ┆ 43.55 │
└────────────┴─────────┴───────┘