budget-data-panel

To create a uniform data panel for budgeting, you process stock price data into a unified dataset designed for the budget layer. This normalizes multi-asset price data post-execution into standardized files like panel_ohlcv.parquet for analysis.

Asset price normalization generates standardized output files including panel_ohlcv.parquet, returns_wide.parquet, and data_panel_manifest.json. These files structure the uniform data panel to standardize outputs for budgeting analysis.

You generate a data panel by executing the command line interface with your budget run state file path. Use `python -m strategy_lab.cli budget data-panel` followed by the JSON state file path to process budgeted assets.

You need a unified data panel for post-budget run analysis when you must sum up registered stock market price data for budgeted assets. It serves scenarios involving comprehensive data normalization within a complex financial budgeting pipeline.

No, you cannot use this data panel skill without a completed budget run state file. The skill is specifically designed to process asset prices after budgeting runs are completed, requiring the state JSON as input.

The best way to standardize multi-asset financial data for a budget layer is processing stock market prices into a uniform data panel. This approach normalizes registered asset prices and writes standardized parquet files for the budgeting process.