Duplicate from RudrakshNanavaty/earnings-call-data

Co-authored-by: Rudraksh Nanavaty <RudrakshNanavaty@users.noreply.huggingface.co>

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.avro filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.lz4 filter=lfs diff=lfs merge=lfs -text
+*.mds filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
+# Audio files - uncompressed
+*.pcm filter=lfs diff=lfs merge=lfs -text
+*.sam filter=lfs diff=lfs merge=lfs -text
+*.raw filter=lfs diff=lfs merge=lfs -text
+# Audio files - compressed
+*.aac filter=lfs diff=lfs merge=lfs -text
+*.flac filter=lfs diff=lfs merge=lfs -text
+*.mp3 filter=lfs diff=lfs merge=lfs -text
+*.ogg filter=lfs diff=lfs merge=lfs -text
+*.wav filter=lfs diff=lfs merge=lfs -text
+# Image files - uncompressed
+*.bmp filter=lfs diff=lfs merge=lfs -text
+*.gif filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text
+*.tiff filter=lfs diff=lfs merge=lfs -text
+# Image files - compressed
+*.jpg filter=lfs diff=lfs merge=lfs -text
+*.jpeg filter=lfs diff=lfs merge=lfs -text
+*.webp filter=lfs diff=lfs merge=lfs -text
+# Video files - compressed
+*.mp4 filter=lfs diff=lfs merge=lfs -text
+*.webm filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+language:
+  - en
+license: mit
+tags:
+  - finance
+  - earnings
+  - transcripts
+  - time-series
+  - parquet
+  - reinforcement-learning
+  - sp500
+  - xbrl
+  - fundamentals
+size_categories:
+  - 10K-100K
+task_categories:
+  - text-classification
+  - summarization
+  - feature-extraction
+  - text-retrieval
+  - reinforcement-learning
+  - other
+pretty_name: S&P 500 earnings episodes (2005–2025; merged transcripts, prices, SEC, labels)
+---
+
+# S&P 500 earnings episodes (2005–2025)
+
+**Augmented release** built on [`Bose345/sp500_earnings_transcripts`](https://huggingface.co/datasets/Bose345/sp500_earnings_transcripts) (same transcript calendar span as that collection: **2005–2025**). Static tabular data for supervised learning or RL-style experiments on **earnings-call episodes**. Each row is one company–quarter call, keyed by a stable `episode_id`, with long-form text (full earnings transcript, SEC press materials), pre-earnings price context, OHLCV anchors, **SEC XBRL fundamentals** (`xbrl_*` columns), and **post-earnings return labels**.
+
+**Companion report:** **`sweetviz_episodes.html`** — a **Sweetviz** profile of `episodes.parquet`, shipped in this dataset repo. [View on the Hub](https://huggingface.co/datasets/RudrakshNanavaty/earnings-call-data/blob/main/sweetviz_episodes.html) or download the [raw file](https://huggingface.co/datasets/RudrakshNanavaty/earnings-call-data/resolve/main/sweetviz_episodes.html) and open it locally in a browser (distributions, missingness, associations).
+
+---
+
+## What’s in this folder
+
+These files are the **materialized outputs** of the build pipeline (upstream Hugging Face transcripts → Yahoo Finance prices → SEC EDGAR 8-K press text → feature engineering → merge → optional XBRL join). Intermediate download caches usually live under `data/cache/` locally and are **not** required for analysis if you only use the parquet files below.
+
+| File | Role |
+|------|------|
+| **`episodes.parquet`** | **Primary dataset** — one row per episode with identity, text, features, OHLCV anchors, **SEC XBRL fundamentals** (`xbrl_*`), and labels (see [Schema](#schema-episodesparquet)). |
+| **`episodes_press_release_8k.parquet`** | **Subset** of `episodes.parquet`: only rows where `press_release_8k_body` is not null (same schema; fewer rows — on the order of **~16k** after a full pipeline run). [Browse on the Hub](https://huggingface.co/datasets/RudrakshNanavaty/earnings-call-data/blob/main/episodes_press_release_8k.parquet). Produced locally with `uv run python pipeline/filter_episodes_press_release_8k.py`. |
+| **`sweetviz_episodes.html`** | **Exploratory HTML report** (Sweetviz) for `episodes.parquet`; same folder on the Hub as the parquet files ([see below](#sweetviz-html)). |
+| `raw_hf.parquet` | Base transcript metadata and structured content source fields from the upstream Hugging Face dataset (see [Provenance](#provenance)). |
+| `raw_prices.parquet` | Per-episode OHLCV anchors, sector, and price-derived fields from market data. |
+| `raw_press_releases.parquet` | SEC 8-K body and exhibit text (e.g. EX-99.1 / EX-99.2) aligned to each episode. |
+| `features.parquet` | Formatted earnings transcript, text flags, momentum/volume features, and label columns produced in the feature stage. |
+
+Rough scale (after a full pipeline run): on the order of **~33k rows** in `episodes.parquet` and **~16k rows** in `episodes_press_release_8k.parquet`, and **hundreds of tickers** (in line with upstream transcript coverage), **2005–2025** span — confirm row and symbol counts on your copy with `len(pd.read_parquet("episodes.parquet"))` and `ep["symbol"].nunique()`.
+
+---
+
+## Schema (`episodes.parquet`)
+
+Columns follow this order in the merged export:
+
+**Identity:** `episode_id`, `symbol`, `company_name`, `company_id`, `year`, `quarter`, `date`, `earnings_date`, `sector`
+
+**Text (observation):** `earnings_transcript`, `press_release_8k_body`, `press_release_ex991`, `press_release_ex992`, `press_release_sources`
+
+**Text flags:** `guidance_mentioned`, `beat_mentioned`
+
+**Pre-call price features:** `price_momentum_30d`, `price_momentum_90d`, `pct_from_52w_high_pt`, `avg_volume_20d`
+
+**OHLCV anchors (grading / simulation):** `d_minus_1_*`, `d_plus_1_*`, `d_plus_30_*`, `next_qtr_d_minus_1_*` (open, high, low, close, volume as listed in the table)
+
+**Labels / targets:** `sentiment_label`, `move_1d`, `move_30d`, `move_next_qtr`, `move_1d_direction`, `gap_open_d1`, `volume_surge_d1`
+
+**Audit / quality:** `next_qtr_date`
+
+**XBRL (SEC EDGAR companyfacts, 2009+):** Per-episode numeric facts from the SEC **company facts** JSON API (`data.sec.gov/api/xbrl/companyfacts/CIK{cik}.json`), documented under [SEC EDGAR APIs](https://www.sec.gov/edgar/sec-api-documentation). Facts use **`us-gaap`** concepts only. Episodes with **`year < 2009`** have nulls in all `xbrl_*` columns (no companyfacts match is attempted for those rows).
+
+**How it is joined:** each episode’s ticker maps to a **CIK** via the same SEC ticker map used elsewhere in the pipeline (`data/cache/edgar/cik_map.json`, built during EDGAR steps or with `uv run python pipeline/build_cik_map.py`). If no CIK is found, companyfacts are not fetched for that row. After the merged table exists, run:
+
+`uv run python pipeline/06_xbrl.py`
+
+That step fills `xbrl_*` on **`episodes.parquet`** and refreshes **`episodes_press_release_8k.parquet`** with the same columns. Requests respect SEC rate limits (under 10 requests per second). When you run the pipeline locally, gaps and reasons are appended to **`reports/failures_xbrl.csv`** (not required to use the Hub parquet).
+
+**Matching logic:** each metric tries **several GAAP local names in priority order** (e.g. revenue tries `Revenues`, then revenue-from-contract variants, then net sales) so more cells populate despite issuer tag choice; see `pipeline/06_xbrl.py` for the exact chains.
+
+**Provenance (string):** for each value column there is a sibling `*_tag` column (e.g. `xbrl_revenue_tag`) with the **winning** local GAAP name, or null if the value is null.
+
+- **Income statement:** `xbrl_revenue`, `xbrl_cost_of_revenue`, `xbrl_gross_profit`, `xbrl_operating_income`, `xbrl_net_income`, `xbrl_eps_basic`, `xbrl_eps_diluted` — plus `xbrl_revenue_tag`, …, `xbrl_eps_diluted_tag`
+- **Balance sheet:** `xbrl_cash_and_cash_equivalents`, `xbrl_total_assets`, `xbrl_total_liabilities` — plus `xbrl_cash_and_cash_equivalents_tag`, `xbrl_total_assets_tag`, `xbrl_total_liabilities_tag`
+- **Cash flow:** `xbrl_net_cash_operating_activities`, `xbrl_capital_expenditures` — plus `xbrl_net_cash_operating_activities_tag`, `xbrl_capital_expenditures_tag`
+
+Treat these fields as **best-effort fundamentals aligned to the earnings quarter**, not audited restatements; expect **sparse cells** where filings, tags, or timing do not yield a match.
+
+`sentiment_label` is derived from `move_1d` using fixed percentage bands (very bearish through very bullish). Treat labels as **historical hindsight** for research, not investment advice.
+
+---
+
+## Sweetviz HTML
+
+The **Sweetviz** report is an exploratory companion to **`episodes.parquet`** only. It summarizes column types, missingness, numeric distributions, and target associations without loading the full frame in a notebook.
+
+**On this Hub repo** the file lives next to the parquet exports:
+
+- **Filename:** `sweetviz_episodes.html`
+- **Browse:** [dataset files → `sweetviz_episodes.html`](https://huggingface.co/datasets/RudrakshNanavaty/earnings-call-data/tree/main)
+- **Direct download:** [`.../resolve/main/sweetviz_episodes.html`](https://huggingface.co/datasets/RudrakshNanavaty/earnings-call-data/resolve/main/sweetviz_episodes.html)
+
+**Download with Python** ([`huggingface_hub`](https://huggingface.co/docs/huggingface_hub)):
+
+```python
+from huggingface_hub import hf_hub_download
+
+path = hf_hub_download(
+    repo_id="RudrakshNanavaty/earnings-call-data",
+    filename="sweetviz_episodes.html",
+    repo_type="dataset",
+)
+print(path)  # open this path in a browser
+```
+
+**Regenerate locally** (from the pipeline repo that produced these files):
+
+`uv run python pipeline/sweetviz_report.py data/episodes.parquet -o reports/sweetviz_episodes.html`
+
+Sweetviz is a third-party tool; report content reflects the table at generation time.
+
+---
+
+## Provenance
+
+- **Transcripts / call metadata:** same underlying universe and years as [`Bose345/sp500_earnings_transcripts`](https://huggingface.co/datasets/Bose345/sp500_earnings_transcripts) (this release **augments** those transcripts with market, SEC, and label columns; respect that dataset’s license and terms when redistributing derived work).
+- **Market data:** via [yfinance](https://github.com/ranaroussi/yfinance) (subject to Yahoo / vendor terms of use).
+- **Filings:** U.S. SEC EDGAR public data (comply with [SEC fair access](https://www.sec.gov/os/accessing-edgar-data) and rate-limiting expectations when re-fetching).
+- **XBRL fundamentals:** derived from SEC **company facts** (same public data policy as above); re-fetch only with a proper [User-Agent](https://www.sec.gov/os/accessing-edgar-data) and polite throughput.
+
+This package is a **processed merge** for research; it is not an official SEC or exchange product.
+
+---
+
+## Loading examples
+
+**pandas / PyArrow**
+
+```python
+import pandas as pd
+
+ep = pd.read_parquet("episodes.parquet")
+print(ep.shape, ep.columns[:5].tolist())
+
+# Optional: only episodes with SEC 8-K body text populated
+ep_8k = pd.read_parquet("episodes_press_release_8k.parquet")
+print(ep_8k.shape)
+
+# Optional: rows with at least headline XBRL (example)
+ep_xbrl = ep.dropna(subset=["xbrl_revenue", "xbrl_net_income"])
+print(ep_xbrl.shape)
+```
+
+**Hugging Face `datasets`** (if you upload parquet to a Hub dataset repo)
+
+```python
+from datasets import Dataset
+
+ds = Dataset.from_parquet("episodes.parquet")  # or hf://datasets/<user>/<name>/path.parquet
+print(ds)
+```
+
+---
+
+## Use cases
+
+- Train or evaluate models on **text + tabular market context** with aligned **forward returns** and optional **reported fundamentals** (`xbrl_*`).
+- Build **RL environments** where observations include call text and pre-earnings features and rewards depend on realized moves (subject to your own leakage and causality checks).
+- Reproduce or extend the pipeline using the sibling repository that emits these files.
+
+---
+
+## Limitations
+
+- Rows may contain **nulls** where a source (e.g. a filing or price window) was missing; use the audit columns and null summaries in the Sweetviz report or your own QC.
+- **`xbrl_*` columns are intentionally sparse:** many episodes will have nulls (no CIK, no matching GAAP fact for the quarter, or `year < 2009`). Do not assume complete fundamentals coverage.
+- **Survivorship and sample bias** follow the upstream universe and filters.
+- **Non-stationarity:** financial regimes change; test generalization across time and sectors.
+
+---
+
+## Citation
+
+If you use this dataset, cite the **upstream transcript dataset** as its authors request, plus a citation or link to **this Hub dataset**. Example BibTeX skeleton (fill in author as appropriate):
+
+```bibtex
+@misc{earnings_episodes_2026,
+  title        = {S\&P 500 Earnings Episodes (merged transcripts, prices, SEC, labels)},
+  author       = {YOUR NAME OR ORG},
+  year         = {2026},
+  howpublished = {\url{https://huggingface.co/datasets/RudrakshNanavaty/earnings-call-data}},
+  note         = {Augments Bose345/sp500\_earnings\_transcripts (2005--2025); adds yfinance, SEC EDGAR-derived fields, and optional SEC XBRL companyfacts (us-gaap) on episodes from 2009+.}
+}
+```
+
+---
+
+## License
+
+This dataset card specifies **MIT** (`license: mit` in the frontmatter). You remain responsible for **upstream** terms (e.g. the Hugging Face transcript dataset, Yahoo/yfinance, SEC redistribution) when publishing or redistributing derived data.

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