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https://github.com/alvarofpp/dataset-flights-brazil
Flights in Brazil registered by ANAC (Agência Nacional de Aviação Civil - National Civil Aviation Agency)
https://github.com/alvarofpp/dataset-flights-brazil
air-traffic air-traffic-data brazil csv dataset flights graphml python3
Last synced: 2 days ago
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Flights in Brazil registered by ANAC (Agência Nacional de Aviação Civil - National Civil Aviation Agency)
- Host: GitHub
- URL: https://github.com/alvarofpp/dataset-flights-brazil
- Owner: alvarofpp
- License: other
- Created: 2021-07-19T19:26:19.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2024-02-24T21:27:09.000Z (9 months ago)
- Last Synced: 2024-02-24T22:31:03.873Z (9 months ago)
- Topics: air-traffic, air-traffic-data, brazil, csv, dataset, flights, graphml, python3
- Language: Python
- Homepage:
- Size: 96.3 MB
- Stars: 8
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Flights in Brazil
This repository have datasets with all flights in Brazil registered by ANAC
(Agência Nacional de Aviação Civil - National Civil Aviation Agency), all airports
involved in these flights and a undirected graph with the number of flights between two airports.
Sources:
- [Flights in Brazil by ANAC](https://www.gov.br/anac/pt-br/assuntos/dados-e-estatisticas/dados-estatisticos).
- [List of public aerodromes by ANAC](https://www.anac.gov.br/acesso-a-informacao/dados-abertos/areas-de-atuacao/aerodromos/lista-de-aerodromos-publicos-v2).
- [Airport Codes by DataHub.io](https://datahub.io/core/airport-codes)
(note: the latitude and longitude columns have their values swapped).
After merging the datasets, the [geocoder](https://github.com/DenisCarriere/geocoder)
package was used to fill in the empty values.
## Datasets
You can find the datasets in `data/`.
### [`anac.csv.lrz`](data/anac.csv.lrz)
All flights in Brazil by ANAC. ANAC does not provide the data dictionary.
You can use `lrzip` to decompress the file.
### [`airports.csv`](data/airports.csv)
All airports on ANAC flight records.
| Column | Type | Description | Example |
| --- | --- | --- | --- |
| code | `string` | [ICAO airport code](https://en.wikipedia.org/wiki/ICAO_airport_code) | `"SNBG"` |
| name | `string` | Airport name. | `"BAIXO GUANDU"` |
| state | `string` | State where the airport is located. | `"ES"` |
| region | `string` | Region where the airport is located. | `"SUDESTE"` |
| country | `string` | Country where the airport is located. | `"BRASIL"` |
| continent | `string` | Continent where the airport is located. | `"AMÉRICA DO SUL"` |
| lat_geo_point | `double` | Latitude of the airport reference point. | `-19.498889` |
| lon_geo_point | `double` | Longitude of the airport reference point. | `-41.041944` |
### [`air_traffic.graphml`](data/air_traffic.graphml)
It's an undirected graph.
#### Node attributes
The id of each node is the ICAO airport code.
| Column | Type | Description | Example |
| --- | --- | --- | --- |
| name | `string` | Airport name. | `"GUARULHOS"` |
| country | `string` | Country where the airport is located. | `"BRASIL"` |
| latitude | `double` | Latitude of the airport reference point. | `-23.435556` |
| longitude | `double` | Longitude of the airport reference point. | `-46.473056` |
#### Edge attributes
| Column | Type | Description | Example |
| --- | --- | --- | --- |
| flight_count | `int` | Number of flights carried out between these airports. | `147` |
## Scripts
- `extract.py` - Download all CSV files and puts them in the `data/extract` folder.
- `transform_to_anac_csv.py` - Merges all files downloaded from ANAC, rename the columns and create `anac.csv`.
- `transform_to_airports_csv.py` - Creates a dataset with all airports (`airports.csv`).
- `transform_to_graphml.py` - Creates an undirected graph (`air_traffic.graphml`).
## Generate
In your environment:
```shell
# Install requirements for scripts
pip install -r requirements.txt
# Download csv files from sources
python3 extract.py
# Transform to final files
python3 transform_to_anac_csv.py
python3 transform_to_airports_csv.py
python3 transform_to_graphml.py
```
If you have Docker and Makefile installed on your machine,
you can execute the `make build` command to create the image,
followed by `make shell` to access a container and execute
the aforementioned steps to generate the files.
To convert the `data/anac.csv` file into `data/anac.csv.lrz`, you must execute the following commands:
```shell
sudo apt install lrzip
lrzip -z data/anac.csv
```
## Contributing
Contributions are more than welcome. Fork, improve and make a pull request.
For bugs, ideas for improvement or other, please create an
[issue](https://github.com/alvarofpp/dataset-flights-brazil/issues).
## License
This project is licensed under the CDLA-Sharing-1.0 License - see the [LICENSE](LICENSE)
file for details.