Add TsFile (converted from AAdevloper/nifty50-market-regime)

README.md

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+---
+license: mit
+task_categories:
+- tabular-classification
+- time-series-forecasting
+tags:
+- tsfile
+- timeseries
+- time-series
+- finance
+- trading
+- market-data
+- nifty50
+- india
+- technical-indicators
+- format:tsfile
+pretty_name: NIFTY 50 Market Regime (TsFile)
+size_categories:
+- 1K<n<10K
+---
+
+# NIFTY 50 Market Regime (TsFile)
+
+Apache TsFile version of [`AAdevloper/nifty50-market-regime`](https://huggingface.co/datasets/AAdevloper/nifty50-market-regime).
+
+## Overview
+
+Technical indicators and corresponding market-regime labels for the NIFTY 50
+index, used to train binary classification models that predict market regimes
+(`RISK_ON` / `RISK_OFF`) in Indian financial markets. Each record is one daily
+observation with derived indicators (VIX, RSI, moving averages) plus the regime
+label.
+
+- **Regimes:** `RISK_ON` (1) — favorable conditions, lower volatility, bullish
+  momentum; `RISK_OFF` (0) — unfavorable conditions.
+
+## Schema (TsFile structure)
+
+- **Time** (INT64, milliseconds) — the trading date.
+- **india_vix** (FIELD, FLOAT) — India VIX.
+- **rsi_14** (FIELD, FLOAT) — 14-period Relative Strength Index.
+- **ma_50** / **ma_200** (FIELD, FLOAT) — 50-/200-period moving averages.
+- **regime** (FIELD, INT64) — regime label (1 = RISK_ON, 0 = RISK_OFF).
+
+## 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("nifty50_market_regime.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/AAdevloper/nifty50-market-regime
+- Author / publisher: AAdevloper
+- License: MIT