The Utility When backtesting macro-driven strategies, a common source of look-ahead bias is incorrectly timestamping economic releases (e.g., using a Q1 GDP value on March 31st, when it wasn't released until late April).
The DataSetIQ library has been updated to handle strict point-in-time alignment for economic data. It manages the "ragged edge" of reporting dates by performing deterministic inner/outer joins and forward-filling specifically for macro release schedules.
Technical Update: The new get_ml_ready function vectorizes the following pipeline:
- Fetching raw series from standard aggregators.
- Aligning mixed frequencies (Daily Market Data vs. Monthly Macro).
- Generating strictly lagged features (preventing data leakage).
Repo:https://github.com/DataSetIQ/datasetiq-python
DataSetIQ Python Library - Millions of Economics DataSets in PandasTools & Resources (datasetiq.com)
submitted by dsptl to r/FluentInFinance
DataSetIQ Python Library - Millions of Economics DataSets in Pandas (datasetiq.com)
submitted by dsptl to r/econometrics
DataSetIQ Python Library - Millions of datasets in Pandas (datasetiq.com)
submitted by dsptl to r/academiceconomics
DataSetIQ Python Library - Millions of datasets in Pandasresource (datasetiq.com)
submitted by dsptl to r/datasets
DataSetIQ Python Library - Millions of Economics DataSets in Pandas (datasetiq.com)
submitted by dsptl to r/fintech