Update Data Card (README.md)
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README.md
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---
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annotations_creators:
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- automated
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language:
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- en
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license:
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- mit
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task_categories:
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- time-series-forecasting
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- reinforcement-learning
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tags:
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- finance
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- stock-market
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- technical-analysis
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- yfinance
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size_categories:
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- 10K<n<100K
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---
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# 📊 Multi-Agent RL Trading System - Dataset
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This dataset contains historical OHLCV (Open, High, Low, Close, Volume) data for **AAPL**, **MSFT**, and **GOOGL**, pre-processed for Reinforcement Learning based trading systems.
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## 📁 Dataset Content
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The dataset consists of CSV files downloaded via `yfinance`:
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* `AAPL.csv`: Apple Inc. daily data (Jan 2018 - Dec 2024).
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* `MSFT.csv`: Microsoft Corp. daily data (Jan 2018 - Dec 2024).
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* `GOOGL.csv`: Alphabet Inc. daily data (Jan 2018 - Dec 2024).
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## 📝 Columns
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| Column | Description |
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| :--- | :--- |
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| **Date** | Trading date (YYYY-MM-DD) |
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| **Open** | Opening price |
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| **High** | Highest price of the day |
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| **Low** | Lowest price of the day |
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| **Close** | Closing price (Adjusted for splits/dividends) |
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| **Volume** | Number of shares traded |
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## ⚙️ Usage
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This data is designed to be fed into a Feature Engineering pipeline (calculating RSI, MACD, etc.) before being used by the `TradingEnv`.
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```python
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import pandas as pd
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# Load data
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df = pd.read_csv("AAPL.csv", parse_dates=['Date'], index_col='Date')
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print(df.head())
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```
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## ⚠️ Source
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Data was sourced from Yahoo Finance API. Not intended for real financial advice or live trading decisions.
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## 🛠️ Credits
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Collected by **Adityaraj Suman** for the Multi-Agent RL Trading System project.
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