| --- |
| license: cc-by-nc-nd-4.0 |
| task_categories: |
| - time-series-forecasting |
| language: |
| - en |
| tags: |
| - tsfile |
| - timeseries |
| - time-series |
| - macroeconomics |
| - forecasting |
| - economics |
| - finance |
| - format:tsfile |
| pretty_name: MacroEconHorizon (TsFile) |
| size_categories: |
| - 1M<n<10M |
| --- |
| |
| # MacroEconHorizon (TsFile) |
|
|
| Apache TsFile version of [`bkoyuncu/MacroEcon`](https://huggingface.co/datasets/bkoyuncu/MacroEcon). |
|
|
| ## Overview |
|
|
| MacroEconHorizon is a curated collection of macroeconomic time series spanning 63 |
| countries (plus the euro area and South Africa, 64 country files in total) from |
| 1970 to 2023. It is designed to support nowcasting, forecasting, and scenario |
| analysis for machine-learning researchers and economic policy makers. Indicators |
| cover GDP, inflation, unemployment rates, commodity prices, financial market |
| variables, and monetary policy metrics, curated by the Bank for International |
| Settlements (BIS). |
|
|
| Each variable is identified by a code, with a frequency (D=Daily, M=Monthly, |
| Q=Quarterly) and a transformation (`value`, `_delta`, `_log`, `_delta_log`). |
| Frequencies are standardized to a daily grid via forward-fill. |
|
|
| - **Countries:** 64 (63 countries + euro area) |
| - **Time span:** 1970 to 2023 (daily grid) |
| - **Rows:** ~1.3 million across all country panels |
| - **Indicators:** GDP, inflation, unemployment, commodity prices, financial |
| variables, monetary policy metrics |
|
|
| ## Schema (TsFile structure) |
|
|
| Because the feature columns are country-specific (the indicator set does not |
| overlap across countries), each country is converted to its own TsFile / table |
| `macroecon_<cc>` rather than a single sparse union table. |
|
|
| - **Time** (INT64, milliseconds) — the daily date (source `Unnamed: 0` column). |
| - **`Q_...` / `D_...` / `M_...` / `A_...`** (FLOAT) — the economic indicators. |
| Column names encode frequency, code, country, series row, and transformation |
| (e.g. `Q_FXSP_AE_row_0_value_delta_log`); dots/special characters are replaced |
| with underscores. |
|
|
| Each country is a single device; its indicators are numeric FIELD columns. |
| Missing values (forward-fill does not reach the start of every series) are stored |
| as null. |
|
|
| ## Usage |
|
|
| Install the Apache TsFile Python SDK (`pip install tsfile`) and read a converted file: |
|
|
| ```python |
| from pathlib import Path |
| from tsfile import TsFileReader |
| |
| path = Path("macroecon_ae.tsfile") |
| with TsFileReader(str(path)) as reader: |
| schemas = reader.get_all_table_schemas() |
| print("tables:", list(schemas)) |
| table_name = next(iter(schemas)) |
| table = schemas[table_name] |
| columns = [column.get_column_name() for column in table.get_columns()] |
| print("columns:", columns) |
| field_names = [ |
| column.get_column_name() |
| for column in table.get_columns() |
| if column.get_column_name() not in {"Time", "time"} |
| ] |
| if field_names: |
| with reader.query_table(table_name, field_names[:3], batch_size=1024) as result: |
| batch = result.read_arrow_batch() |
| if batch is not None: |
| print(batch.to_pandas().head()) |
| ``` |
|
|
| ## Source & license |
|
|
| - Original dataset: https://huggingface.co/datasets/bkoyuncu/MacroEcon |
| - Author / publisher: bkoyuncu |
| - Curated by: Bank for International Settlements (BIS) |
| - License: CC BY-NC-ND 4.0 |
|
|
