Datasets:
Add PlaneCrashData global aviation dataset (Parquet, CSV, JSONL) with comprehensive metadata and documentation
b817a96 verified |
Download README.md from MauroPello/planecrashdata: direct link, hf CLI and curl.
- Browser
- Download file 8.28 kB
-
https://huggingface.co/datasets/MauroPello/planecrashdata/resolve/main/README.md
- Command line
-
hf download hf://datasets/MauroPello/planecrashdata/README.md
-
curl -L -o README.md https://huggingface.co/datasets/MauroPello/planecrashdata/resolve/main/README.md
8.28 kB
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: train | |
| path: data/train-* | |
| dataset_info: | |
| features: | |
| - name: id | |
| dtype: int64 | |
| - name: aircraft | |
| dtype: string | |
| - name: operator | |
| dtype: string | |
| - name: registration | |
| dtype: string | |
| - name: flight_phase | |
| dtype: string | |
| - name: flight_type | |
| dtype: string | |
| - name: survivors | |
| dtype: int64 | |
| - name: crash_site | |
| dtype: string | |
| - name: schedule | |
| dtype: string | |
| - name: msn | |
| dtype: string | |
| - name: yom | |
| dtype: int64 | |
| - name: crash_location | |
| dtype: string | |
| - name: country | |
| dtype: string | |
| - name: region | |
| dtype: string | |
| - name: crew_on_board | |
| dtype: int64 | |
| - name: crew_fatalities | |
| dtype: int64 | |
| - name: passengers_on_board | |
| dtype: int64 | |
| - name: passengers_fatalities | |
| dtype: int64 | |
| - name: other_fatalities | |
| dtype: int64 | |
| - name: total_fatalities | |
| dtype: int64 | |
| - name: circumstances | |
| dtype: string | |
| - name: crash_cause | |
| dtype: string | |
| - name: timestamp | |
| dtype: string | |
| - name: latitude | |
| dtype: float64 | |
| - name: longitude | |
| dtype: float64 | |
| - name: image_url | |
| dtype: string | |
| - name: hex_code | |
| dtype: string | |
| - name: external_id | |
| dtype: string | |
| splits: | |
| - name: train | |
| num_bytes: 10260424 | |
| num_examples: 27598 | |
| download_size: 10260424 | |
| dataset_size: 10260424 | |
| pretty_name: PlaneCrashData - Global Aviation Safety & Accident Database (1918-Present) | |
| license: cc-by-4.0 | |
| tags: | |
| - aviation | |
| - transportation | |
| - flight-safety | |
| - plane-crashes | |
| - aircraft-accidents | |
| - aviation-history | |
| - geospatial | |
| - time-series | |
| - open-data | |
| task_categories: | |
| - tabular-classification | |
| - tabular-regression | |
| - text-classification | |
| - time-series-forecasting | |
| size_categories: | |
| - 10K<n<100K | |
| language: | |
| - en | |
| # PlaneCrashData — Global Aviation Safety & Accident Database (1918–Present) | |
| [](https://creativecommons.org/licenses/by/4.0/) | |
| [](https://huggingface.co/datasets/MauroPello/planecrashdata) | |
| [](https://www.planecrashdata.com) | |
| [](https://github.com/MauroPello/flight-crashes) | |
| **PlaneCrashData** is a comprehensive, open historical dataset cataloging global aviation accidents and incidents covering over a century of civil and military aviation from **1918 to the present day**. | |
| The dataset aggregates **27,598 verified aviation accident records** with rich structural metadata, including aircraft technical specifications, operator/airline records, flight phases, full textual circumstance narratives, causal categorizations, survival and fatality statistics, and geospatial coordinates. | |
| Accompanying interactive web visualization: [www.planecrashdata.com](https://www.planecrashdata.com). | |
| --- | |
| ## Key Highlights & Dataset Statistics | |
| - **Total Recorded Incidents**: `27,598` | |
| - **Temporal Coverage**: `May 1918 – August 2026` (over 108 years) | |
| - **Unique Aircraft Types/Models**: `1,187` | |
| - **Unique Airlines & Operators**: `9,002` | |
| - **Countries & Territories**: `226` | |
| - **Total Fatalities Recorded**: `151,390` | |
| - **Geospatially Geocoded Records**: Coordinates (`latitude`, `longitude`) for geospatial GIS analysis | |
| --- | |
| ## Dataset Schema & Fields | |
| | Field Name | Type | Description | Example | | |
| | :--- | :--- | :--- | :--- | | |
| | `id` | `int64` | Unique incident identifier | `1` | | |
| | `aircraft` | `string` | Aircraft model / type | `Boeing 737-800`, `Douglas DC-3` | | |
| | `operator` | `string` | Airline or operating organization | `Pan American World Airways`, `USAF` | | |
| | `registration` | `string` | Aircraft registration / tail number | `N737AA`, `G-ABCD` | | |
| | `flight_phase` | `string` | Phase of flight when incident occurred | `Takeoff (climb)`, `Cruise`, `Approach`, `Landing` | | |
| | `flight_type` | `string` | Category of flight operation | `Scheduled Revenue Flight`, `Cargo`, `Military`, `Test` | | |
| | `survivors` | `int64` | Number of verified survivors (nullable) | `15` | | |
| | `crash_site` | `string` | Physical surroundings / environment | `Airport (less than 10 km from airport)`, `Mountains`, `Sea` | | |
| | `schedule` | `string` | Origin and destination route | `New York - London`, `Paris - Rome` | | |
| | `msn` | `string` | Manufacturer Serial Number (MSN / c/n) | `24680` | | |
| | `yom` | `int64` | Year of aircraft manufacture | `1998` | | |
| | `crash_location` | `string` | Detailed geographical location description | `Tenerife-Los Rodeos Airport Canary Islands` | | |
| | `country` | `string` | Country of incident | `United States of America`, `Spain` | | |
| | `region` | `string` | Geographical region / continent | `North America`, `Europe`, `Asia` | | |
| | `crew_on_board` | `int64` | Number of crew members on board | `8` | | |
| | `crew_fatalities` | `int64` | Crew fatalities count | `0` | | |
| | `passengers_on_board` | `int64` | Number of passengers on board | `150` | | |
| | `passengers_fatalities` | `int64` | Passenger fatalities count | `0` | | |
| | `other_fatalities` | `int64` | Ground / non-occupant fatalities count | `0` | | |
| | `total_fatalities` | `int64` | Total fatalities (crew + passengers + ground) | `0` | | |
| | `circumstances` | `string` | Detailed narrative description of the event | *Narrative text...* | | |
| | `crash_cause` | `string` | Categorized primary cause | `Technical failure`, `Pilot error`, `Weather` | | |
| | `timestamp` | `string` | UTC timestamp in ISO-8601 format | `1977-03-27 17:06:50+00:00` | | |
| | `latitude` | `float64` | Latitude coordinate in decimal degrees | `28.4827` | | |
| | `longitude` | `float64` | Longitude coordinate in decimal degrees | `-16.3415` | | |
| | `image_url` | `string` | Representative or historical aircraft image URL | `https://...` | | |
| | `hex_code` | `string` | ICAO 24-bit Mode S transponder hex code | `4005B5` | | |
| | `external_id` | `string` | External database reference ID (e.g. ASN) | `19770327-0` | | |
| --- | |
| ## Quickstart & Usage | |
| ### Using Hugging Face `datasets` (Python) | |
| ```python | |
| from datasets import load_dataset | |
| # Load dataset | |
| dataset = load_dataset("MauroPello/planecrashdata") | |
| # Inspect dataset | |
| print(dataset["train"][0]) | |
| ``` | |
| ### Using `pandas` or `polars` directly with Parquet | |
| ```python | |
| import pandas as pd | |
| # Load Parquet directly from Hugging Face Hub | |
| url = "hf://datasets/MauroPello/planecrashdata/data/train-00000-of-00001.parquet" | |
| df = pd.read_parquet(url) | |
| print(f"Loaded {len(df):,} incidents spanning {df['yom'].min()} to {df['yom'].max()}") | |
| ``` | |
| ```python | |
| import polars as pl | |
| # Fast Polars scan | |
| df = pl.read_parquet("hf://datasets/MauroPello/planecrashdata/data/train-00000-of-00001.parquet") | |
| print(df.group_by("region").agg(pl.col("total_fatalities").sum())) | |
| ``` | |
| ### Using `DuckDB` (SQL) | |
| ```sql | |
| INSTALL httpfs; | |
| LOAD httpfs; | |
| SELECT | |
| country, | |
| COUNT(*) AS total_crashes, | |
| SUM(total_fatalities) AS total_fatalities | |
| FROM 'https://huggingface.co/datasets/MauroPello/planecrashdata/resolve/main/data/train-00000-of-00001.parquet' | |
| GROUP BY country | |
| ORDER BY total_crashes DESC | |
| LIMIT 10; | |
| ``` | |
| --- | |
| ## Applications & Use Cases | |
| 1. **Aviation Safety Analysis**: Long-term safety trend evaluations, flight phase vulnerability analysis, and accident rate comparisons across decades. | |
| 2. **Predictive Modeling & NLP**: Cause classification and risk factor extraction from historical accident narrative circumstances. | |
| 3. **Geospatial & Temporal GIS**: Mapping aviation incident hotspots, terrain correlation, and regional safety improvements. | |
| 4. **Historical & Academic Research**: Cross-referencing fleet evolution, aircraft manufacturer safety records, and regulatory milestones. | |
| --- | |
| ## License | |
| This dataset is released under the **Creative Commons Attribution 4.0 International (CC BY 4.0)** license. | |
| --- | |
| ## Citation | |
| ```bibtex | |
| @misc{planecrashdata2026, | |
| author = {Mauro Pellonara}, | |
| title = {PlaneCrashData: Global Aviation Safety and Accident Database (1918-Present)}, | |
| year = {2026}, | |
| publisher = {Hugging Face}, | |
| howpublished = {\url{https://huggingface.co/datasets/MauroPello/planecrashdata}} | |
| } | |
| ``` | |