# pythreadex
Pythreadex is a simple Python utility to fetch long-term station data for the United States from ThreadEx, courtesy of ACIS (https://www.rcc-acis.org/). This utility includes a few plotting and climatology functions, as well as converting data to CSV format.
## Installation
### Pip
Installation is available via pip:
```sh
pip install pythreadex
```
### From source
pythreadex can also be installed from source by cloning the GitHub repository:
```sh
git clone https://github.com/tomerburg/pythreadex
cd pythreadex
python setup.py install
```
## Dependencies
- matplotlib >= 2.2.2
- numpy >= 1.14.3
- scipy >= 1.1.0
- pandas >= 1.3.0
## Sample Usage
For full documentation and examples, please refer to [Tropycal Documentation](https://tropycal.github.io/tropycal/).
As of v0.3, the documentation is up-to-date following a bug that started with v0.2.5 where the documentation was not updated with each release.
## Sample Usage
This sample code shows how to search through a dataset, retrieve station data, make a plot and convert the data to CSV format:
```python
from pyhreadex import Dataset
import matplotlib.pyplot as plt
# Create an instance of Dataset
dataset = Dataset()
# Retrieve all stations in New Jersey
print(stations.search_by_state('NJ'))
# Search for Newark, NJ's station ID
station_id = dataset.search_by_name('Newark, NJ')
# Create an instance of a Station object with this station ID
station = dataset.get_station(station_id)
# Make a plot of 2023 maximum temperatures, from January to May
station.plot_temp_time_series('max', year=2023, date_range=('1/1','5/31'))
# Convert data to a CSV file
station.to_csv('newark.csv')
```
Raw data
{
"_id": null,
"home_page": "https://github.com/tomerburg/pythreadex",
"name": "pythreadex",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.6",
"maintainer_email": "",
"keywords": "meteorology,weather",
"author": "Tomer Burg",
"author_email": "",
"download_url": "https://files.pythonhosted.org/packages/cb/f6/bfd0a00e2b3a5f09b0c496cf1521fa7df59a6f5f836592eb4800324206db/pythreadex-0.1.tar.gz",
"platform": "any",
"description": "# pythreadex\nPythreadex is a simple Python utility to fetch long-term station data for the United States from ThreadEx, courtesy of ACIS (https://www.rcc-acis.org/). This utility includes a few plotting and climatology functions, as well as converting data to CSV format.\n\n## Installation\n\n\n### Pip\n\nInstallation is available via pip:\n\n```sh\npip install pythreadex\n```\n\n### From source\n\npythreadex can also be installed from source by cloning the GitHub repository:\n\n```sh\ngit clone https://github.com/tomerburg/pythreadex\ncd pythreadex\npython setup.py install\n```\n\n## Dependencies\n- matplotlib >= 2.2.2\n- numpy >= 1.14.3\n- scipy >= 1.1.0\n- pandas >= 1.3.0\n\n## Sample Usage\nFor full documentation and examples, please refer to [Tropycal Documentation](https://tropycal.github.io/tropycal/).\n\nAs of v0.3, the documentation is up-to-date following a bug that started with v0.2.5 where the documentation was not updated with each release.\n\n## Sample Usage\nThis sample code shows how to search through a dataset, retrieve station data, make a plot and convert the data to CSV format:\n\n```python\nfrom pyhreadex import Dataset\nimport matplotlib.pyplot as plt\n \n# Create an instance of Dataset\ndataset = Dataset()\n\n# Retrieve all stations in New Jersey\nprint(stations.search_by_state('NJ'))\n\n# Search for Newark, NJ's station ID\nstation_id = dataset.search_by_name('Newark, NJ')\n\n# Create an instance of a Station object with this station ID\nstation = dataset.get_station(station_id)\n\n# Make a plot of 2023 maximum temperatures, from January to May\nstation.plot_temp_time_series('max', year=2023, date_range=('1/1','5/31'))\n\n# Convert data to a CSV file\nstation.to_csv('newark.csv')\n```\n",
"bugtrack_url": null,
"license": "",
"summary": "Utility for retrieving and plotting ThreadEx data",
"version": "0.1",
"project_urls": {
"Homepage": "https://github.com/tomerburg/pythreadex",
"Source Code": "https://github.com/tomerburg/pythreadex"
},
"split_keywords": [
"meteorology",
"weather"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "cbf6bfd0a00e2b3a5f09b0c496cf1521fa7df59a6f5f836592eb4800324206db",
"md5": "4fa7dceeb2ec7ec5c0646c1640e73177",
"sha256": "9ef243cb0d160aeed9b7a7106fb5f0caf740df30c9700738498f4ac56592dabb"
},
"downloads": -1,
"filename": "pythreadex-0.1.tar.gz",
"has_sig": false,
"md5_digest": "4fa7dceeb2ec7ec5c0646c1640e73177",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.6",
"size": 13803,
"upload_time": "2023-10-13T22:34:27",
"upload_time_iso_8601": "2023-10-13T22:34:27.598064Z",
"url": "https://files.pythonhosted.org/packages/cb/f6/bfd0a00e2b3a5f09b0c496cf1521fa7df59a6f5f836592eb4800324206db/pythreadex-0.1.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2023-10-13 22:34:27",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "tomerburg",
"github_project": "pythreadex",
"travis_ci": false,
"coveralls": false,
"github_actions": false,
"lcname": "pythreadex"
}
JSON
