Publish ETF dataset
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README.md
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- google-colab
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size_categories:
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- 100K<n<1M
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---
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# skfolio Masterclass ETF Teaching Data
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This dataset provides cleaned ETF price, metadata, and
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The goal is to give learners a public, no-login data source that can be loaded in Google Colab and transformed into the return matrices used by skfolio portfolio workflows. It is designed for teaching diversification, liquidity screening, price-to-return transformation, risk, correlation, drawdowns, and allocation research.
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| `etf_daily_prices.parquet` | 117,864 | Daily ETF OHLCV-style price and volume records for 95 ETF symbols | Raw market history used to teach price checks and return conversion |
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| `instrument_metadata.parquet` | 98 | Symbol-level metadata and trading-status fields | Universe inspection, labeling, and practical data-quality checks |
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| `etf_liquidity_365d.parquet` | 95 | Average and median volume and dollar-volume rankings | Liquidity screening and realistic universe design |
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| `manifest.json` | 1 | Public snapshot metadata and row counts | Lightweight audit trail for notebooks and examples |
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The dataset intentionally does **not** include raw API responses, account data, balances, holdings, transactions, orders, credentials, or trading instructions.
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No Hugging Face token is required for the public dataset.
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## Current Snapshot
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| Item | Value |
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| Price rows | 117,864 |
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| Metadata rows | 98 |
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| Liquidity rows | 95 |
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| Date range | 2021-05-12 to 2026-05-12 |
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| Default file format | Parquet |
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| `lookback_bars`, `lookback_days` | Liquidity lookback settings |
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| `history_bars`, `history_start`, `history_end` | Available history summary |
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## Intended Use
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This dataset is meant for:
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## Suggestions
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Learners and researchers may suggest additional ETF fields, documentation improvements, or derived teaching tables. Suggestions are evaluated based on educational value, licensing and redistribution limits, privacy, data quality, maintainability, and fit with the cleaned teaching-data scope.
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- google-colab
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size_categories:
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- 100K<n<1M
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configs:
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- config_name: prices
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data_files: "etf_daily_prices.parquet"
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default: true
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- config_name: metadata
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data_files: "instrument_metadata.parquet"
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- config_name: liquidity
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data_files: "etf_liquidity_365d.parquet"
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- config_name: indexes
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data_files: "index_daily_prices.parquet"
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---
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# skfolio Masterclass ETF Teaching Data
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This dataset provides cleaned ETF price, metadata, liquidity, and selected market-index tables for educational portfolio-research notebooks, especially the **skfolio Masterclass by The Chart Truth**.
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The goal is to give learners a public, no-login data source that can be loaded in Google Colab and transformed into the return matrices used by skfolio portfolio workflows. It is designed for teaching diversification, liquidity screening, price-to-return transformation, risk, correlation, drawdowns, and allocation research.
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| `etf_daily_prices.parquet` | 117,864 | Daily ETF OHLCV-style price and volume records for 95 ETF symbols | Raw market history used to teach price checks and return conversion |
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| `instrument_metadata.parquet` | 98 | Symbol-level metadata and trading-status fields | Universe inspection, labeling, and practical data-quality checks |
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| `etf_liquidity_365d.parquet` | 95 | Average and median volume and dollar-volume rankings | Liquidity screening and realistic universe design |
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| `index_daily_prices.parquet` | TBD | Selected daily market-index records such as SPX, NDX, and VIX when available | Regime overlays, benchmark context, and volatility exploration |
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| `manifest.json` | 1 | Public snapshot metadata and row counts | Lightweight audit trail for notebooks and examples |
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The dataset intentionally does **not** include raw API responses, account data, balances, holdings, transactions, orders, credentials, or trading instructions.
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No Hugging Face token is required for the public dataset.
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You can also load the tables through the `datasets` library. The dataset card defines three named configs so the tables stay separate in the Hugging Face Dataset Viewer:
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```python
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from datasets import load_dataset
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prices = load_dataset("thecharttruth/etf-data", "prices", split="train")
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metadata = load_dataset("thecharttruth/etf-data", "metadata", split="train")
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liquidity = load_dataset("thecharttruth/etf-data", "liquidity", split="train")
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indexes = load_dataset("thecharttruth/etf-data", "indexes", split="train")
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```
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## Current Snapshot
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| Item | Value |
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| Price rows | 117,864 |
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| Metadata rows | 98 |
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| Liquidity rows | 95 |
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| Index rows | TBD |
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| Date range | 2021-05-12 to 2026-05-12 |
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| Default file format | Parquet |
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| `lookback_bars`, `lookback_days` | Liquidity lookback settings |
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| `history_bars`, `history_start`, `history_end` | Available history summary |
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### `index_daily_prices.parquet`
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| Column | Meaning |
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| `date` | Trading date used for analysis and overlays |
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| `timestamp` | Source timestamp value |
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| `symbol` | Index symbol, such as `SPX`, `NDX`, or `VIX` when available |
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| `asset_type` | Asset label, currently `INDEX` for this file |
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| `period` | Source period used by the collector |
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| `source_run` | Public run label for traceability |
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| `open`, `high`, `low`, `close` | Daily index level fields |
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| `value` | Source value field when provided |
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| `volume` | Usually empty or zero for indexes |
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| `gain_amount`, `gain_percentage` | Source-provided daily change fields |
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## Intended Use
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This dataset is meant for:
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## Suggestions
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Learners and researchers may suggest additional ETF or index fields, documentation improvements, or derived teaching tables. Suggestions are evaluated based on educational value, licensing and redistribution limits, privacy, data quality, maintainability, and fit with the cleaned teaching-data scope.
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