feat(dataset): add S&P 500 Index SPX (🇺🇸): +173 new symbols

.gitignore

@@ -18,6 +18,7 @@
 *.tmp 
 *.bak 
 *.cmd 
+thumbs.db
 *config.yml
 validated_symbols.txt
 .DS_Store 

README.md

@@ -1,10 +1,53 @@
 ---
+language:
+  - en
 license: other
-license_name: license
-license_link: LICENSE
+pretty_name: TroveLedger Financial Time Series Dataset
+task_categories:
+  - time-series-forecasting
+  - tabular-regression
 tags:
-- finance
+  - finance
+  - financial
+  - stock-market
+  - OHLC
+  - time-series
+  - trading
+  - equities
+  - indices
+  - historical-data
+dataset_info:
+  features:
+    - name: symbol
+      dtype: string
+    - name: time
+      dtype: int64
+    - name: open
+      dtype: float64
+    - name: high
+      dtype: float64
+    - name: low
+      dtype: float64
+    - name: close
+      dtype: float64
+    - name: volume
+      dtype: int64
+  splits:
+    - name: daily
+      num_examples: null
+    - name: hourly
+      num_examples: null
+    - name: minute
+      num_examples: null
+size_categories:
+  - n<1K
+  - 1K<n<10K
+  - 10K<n<100K
+  - 100K<n<1M
+  - 1M<n<10M
+  - 10M<n<100M
 ---
+
 # 🗃️ TroveLedger — Financial Time Series Dataset
 
 ![TroveLedger Banner](media/Banner-TroveLedger.jpg)
@@ -12,43 +55,42 @@ tags:
 **A growing ledger of accumulated market history.**
 
 ---
-> ### 🔔 **Latest Dataset Update**
->
-> **Date:** 2025-12-18  
-> **New addition:** 🇭🇰 **Hang Seng Index (HSI)**
+### 🔔 **Latest Dataset Update**
+
+> **Date:** 2025-12-19  
+> **New addition:** 🇺🇸 **S&P 500 Index (SPX)**
 > 
-> Today, symbols from the **Hang Seng Index (HSI)** were added to TroveLedger.
+> Today, the S&P 500 Index was integrated as a dedicated category, consolidating the full US large-cap universe and adding 173 previously missing symbols.
 > 
-> The HSI represents **82 of the largest and most liquid companies listed in Hong Kong**, spanning finance, technology, energy, consumer sectors, and mainland China heavyweights with global relevance.
->
-> This update introduces **82 entirely new symbols** — none of which were present in the previous preliminary dataset — all fully validated via *yfinance*.
+> The S&P 500 represents **503 large-cap US companies** across all major sectors, serving as the premier benchmark for the US equity market.
 >
 > 📊 Data coverage highlights:
 >
-> • Minute-level data available for **30+ trading days**  
-> • Hourly data extending back **~13 months**  
-> • Continuous histories with no artificial gaps introduced
+> • Minute-level data for recent periods  
+> • Hourly and daily extending back years  
+> • Seamless integration with existing US equities for full coverage
 >
 > 📈 What this means:
 >
-> • TroveLedger now meaningfully expands into **Asian markets**  
-> • Direct exposure to China-linked equities via Hong Kong listings  
-> • A major step toward truly global index-level coverage
+> • TroveLedger now offers the ultimate US benchmark dataset  
+> • Ideal for training robust trading bots on diversified large-cap data  
+> • A key consolidation step toward global expansion
 >
 >🔜 What’s next:  
-> Further international indices will follow, continuing the gradual expansion across regions, exchanges, and market structures.
+> Further international indices will follow, continuing the gradual expansion across regions, exchanges, and market structures. Community suggestions what to prioritize first are welcome.
 
 <details>
 <summary>
 Click to expand
 </summary>
-<img src="media/HSI.jpg"/>
+<img src="media/SPX.jpg"/>
 </details>
 
 > ### Recent Index Additions
 >
 > | Date       | Index           | Region | Symbols | Notes |
 > |------------|-----------------|--------|---------|-------|
+> | 2025-12-19 | S&P 500         | 🇺🇸 US | 503     | +173 new symbols; full US benchmark coverage |
 > | 2025-12-18 | Hang Seng Index | 🇭🇰 Asia | 82      | All-new symbols, full minute & hourly coverage |
 > | 2025-12-18 | EURO STOXX 50   | 🇪🇺 Europe | 50      | Extended existing European coverage |
 
@@ -62,7 +104,10 @@ The dataset provides OHLC and volume data at multiple time resolutions and is de
 
 Unlike many freely available data sources, TroveLedger emphasizes **continuity over time**, especially for minute-level data.
 
----
+### Scale & Granularity
+- Total: Over 32 million rows across all symbols and resolutions (growing rapidly)
+- Per symbol: Varies significantly – from <1,000 rows (young stocks, daily) to >500,000 rows (established stocks, minute-resolution)
+- Ideal for both focused single-symbol training and large-scale multi-market models
 
 ## 🔑 What makes TroveLedger different
 
@@ -84,25 +129,58 @@ TroveLedger takes a different approach:
 
 This accumulated depth forms a substantially more reliable foundation for intraday research and model training.
 
----
+> 🧱 **Data Integrity Philosophy**
+>
+> TroveLedger prioritizes *continuity over frequency*.  
+> The primary goal is not to fetch data as often as possible, but to ensure that once a time series starts, it remains **gap-free**.
+>
+> Minute-level data is accumulated incrementally over time, creating long, uninterrupted histories that are not obtainable from fresh API queries alone.
+>
+> This makes the dataset particularly suitable for model training, backtesting, and regime analysis.
 
-## 📦 Dataset Contents
 
-For each instrument, the dataset will contain:
+## 📦 Dataset Structure
 
-* **Daily OHLC + volume**
-* **Hourly OHLC + volume**
-* **Minute OHLC + volume**
+The dataset is organized as follows:
 
-All data is stored in **Parquet format** for efficient processing.
+- **/data/{category}/{symbol}/{symbol}.{interval}.valid.parquet**
 
-```
-/data/{category}/{symbol}/{symbol}.days.{state}.parquet
-/data/{category}/{symbol}/{symbol}.hours.{state}.parquet
-/data/{category}/{symbol}/{symbol}.minutes.{state}.parquet
-```
+Where:
+- `{category}`: e.g., `equities/us`, `indices/sp500`, `indices/eurostoxx50` (growing with new indices)
+- `{symbol}`: Stock ticker (e.g., AAPL, BMW.DE)
+- `{interval}`: One of `days` (daily), `hours` (hourly), or `minutes` (1-minute)
 
----
+The `.valid` suffix indicates that these files have passed quality checks and are ready for use. Only these cleaned, validated files are included in the dataset – temporary or intermediate files from the pipeline are excluded.
+
+**Tip for users**: The `.valid` part is intentionally kept as a flexible "state" marker. You can easily rename or copy files to add your own states (e.g., `.train.parquet` or `.test.parquet`) for train/validation/test splits in your ML workflows. This pattern makes it simple to organize experiments without changing the core data.
+
+### Data Instances
+
+Here's an example row from a typical daily Parquet file (e.g., for AAPL.days.valid.parquet):
+
+| symbol | time       | open   | high   | low    | close  | volume    |
+|--------|------------|--------|--------|--------|--------|-----------|
+| AAPL  | 1704067200 | 192.28 | 192.69 | 191.73 | 192.53 | 42672100 |
+
+- `time` is a Unix timestamp (e.g., 1704067200 = January 1, 2024, 00:00 UTC).
+- All prices are in the symbol's native currency (e.g., USD for US equities).
+
+### Dataset Creation
+
+### Curation Rationale
+TroveLedger was created to provide a reliable, expanding source of historical OHLCV data for AI-driven trading research, addressing gaps in continuity and international coverage.
+
+### Source Data
+All data is sourced from Yahoo Finance via the `yfinance` Python library. Index components are automatically extracted from Wikipedia pages using a custom API-based pipeline for sustainability.
+
+### Data Collection and Processing
+- Symbols are selected from major indices (e.g., S&P 500, EURO STOXX 50) and equities.
+- Data is fetched at daily, hourly, and 1-minute resolutions, validated for completeness, and stored in Parquet format for efficiency.
+- Quality checks remove gaps or anomalies; only ".valid" files are included.
+- Updates occur periodically to extend histories and add new indices based on community input.
+
+### Who are the source data producers?
+Yahoo Finance (public market data). No personal data is included.
 
 ## 🔄 Update Philosophy
 
@@ -122,8 +200,6 @@ These datasets are guaranteed to be **no older than one week**.
 For most training scenarios, this is fully sufficient.
 When models are deployed in real-world environments, current market data is typically provided directly by the target trading platform.
 
----
-
 ## 📈 Scope & Growth
 
 TroveLedger started with a curated universe of approximately 500 equities inherited from earlier *Preliminary* datasets.
@@ -136,9 +212,10 @@ Going forward:
 
 This gradual approach allows issues to be detected early and handled without disrupting existing data.
 
----
+## 🎯 Intended Uses
 
-## 🎯 Intended Use
+- **Primary Use**: Training and evaluating machine learning models for trading strategies and autonomous AI bots.
+- **Other Uses**: Time series analysis, financial research, educational projects, and community-driven extensions.
 
 TroveLedger is suitable for:
 
@@ -148,9 +225,12 @@ TroveLedger is suitable for:
 * backtesting strategies requiring dense intraday history
 * exploratory quantitative analysis
 
----
+## ⚠️ Limitations & Notes on Data Sources
 
-## ⚠️ Notes on Data Sources
+- **Data Freshness**: Data is typically a few days old, not real-time.
+- **Coverage**: Not all symbols may have complete historical data, especially for minute-resolution or newly added indices.
+- **Growth Phase**: The dataset is actively expanding; check for updates on new indices and symbols.
+- **Not financial advice**: This dataset is for research and educational purposes only. Past performance is no guarantee of future results.
 
 Data is derived from publicly accessible market data sources (e.g. via yfinance).
 
@@ -158,17 +238,7 @@ While care is taken to ensure consistency and continuity, this dataset is provid
 
 Users are responsible for verifying suitability for their specific use cases and for complying with the terms of the original data providers.
 
----
-
-## 💬 Community & Feedback
-
-Questions, observations, and constructive feedback are welcome via the **Community** tab.
-
-TroveLedger is intended to evolve over time — thoughtful input helps steer that evolution in a useful direction.
-
----
-
-## License & Usage
+## 📜 License & Usage
 
 This dataset is provided **solely for non-commercial research and educational purposes**.
 
@@ -180,9 +250,33 @@ See the [`LICENSE`](./LICENSE) file for full details.
 
 NO WARRANTY IS PROVIDED. Use at your own risk.
 
----
+## 💬 Feedback, Suggestions & Community Support
+
+TroveLedger is a growing, community-driven project providing high-quality OHLCV data for training AI models on financial markets and trading strategies. Your input makes it better!
+
+- **What are you building?** I'd love to hear how you're using TroveLedger! Share your projects, trading bot ideas, ML models, or research directions – it motivates me to keep expanding and might inspire others.
+- **Desired indices**: Which major indices are you waiting for most? I'll prioritize based on demand and feasibility.
+- **Helping expand indices**: The pipeline uses the Wikipedia API to automatically extract components. It works best with a structured table containing both company names and clean, yfinance-compatible ticker symbols.
+  - Simply share the Wikipedia page URL (any language) for your desired index.
+  - If the table needs tweaks (e.g., missing or unclear ticker column, prefixes in symbols), improving it on Wikipedia is the most sustainable way – the global community then keeps it updated long-term!
+  - Once ready, post the link here, and I'll integrate it quickly.
+
+Interested in a deeper dive into the exact table format and config options my pipeline supports (with examples like zero-padding, suffixes, or language overrides)? Let me know – if there's demand, I'll create a dedicated guide soon!
+
+Join the discussion in [Hugging Face Discussions](https://huggingface.co/datasets/Traders-Lab/TroveLedger/discussions).
+
+## 🔖 Citation
+
+If you use TroveLedger in your work, please cite it as:
+
+@dataset{Traders-Lab_TroveLedger_2025,
+  author = {Traders-Lab},
+  title = {TroveLedger Financial Time Series Dataset},
+  year = {2025},
+  url = {https://huggingface.co/datasets/Traders-Lab/TroveLedger}
+}
 
-## 🔚 Final note (subtle personality, optional)
+## 🔚 Final note
 
 TroveLedger is not built to chase yesterday’s tick.
 It is built to **remember**.

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