[](https://pypi.org/project/parcoords/)
[](https://voigtpeter.github.io/parcoords/index.html)
# Parallel Coordinates Plotting for Python `parcoords`
This package implements a parallel-coordinate plot, commonly used in machine learning, i.e. for hyperparameter visualization.
<p align="center">
<img alt="Example parallel-coordinate plot" src="https://raw.githubusercontent.com/VoigtPeter/parcoords/main/img/example_plot.png">
</p>
## Installation
The `parcoords` package can be installed with pip:
```
pip install parcoords
```
You can also view the package on [PyPI](https://pypi.org/project/parcoords/).
## Usage
The following code produces the sample plot at the beginning of this page.
```python
import matplotlib.pyplot as plt
from parcoords import plot_parcoords
# let's define some data to plot
values = [
[0.1, 10, "smote", 0.78],
[0.15, 9, "none", 0.46],
[0.18, 8, "rand_over", 0.67],
[0.01, 16, "rand_over", 0.84],
[0.01, 15, "smote", 0.86],
[0.015, 12, "smote", 0.87],
[0.03, 12, "smote", 0.81],
[0.12, 13, "none", 0.51],
[0.07, 11, "rand_over", 0.7],
[0.2, 14, "none", 0.55],
]
# plot the values as parallel-coordinate plot
plot_parcoords(
values,
labels=["lr", "# epochs", "sampling method", "accuracy"],
color_field="accuracy",
scale=[("lr", "log")],
title="Parallel-Coordinates of the Hyperparameters",
)
plt.show()
```
## License
This repository is licensed under the [MIT-License](https://github.com/VoigtPeter/parcoords/blob/main/LICENSE.txt).
Raw data
{
"_id": null,
"home_page": "https://github.com/VoigtPeter/parcoords",
"name": "parcoords",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.6",
"maintainer_email": "",
"keywords": "parallel coordinates,parallel-coordinates,plot,hyperparameter,visualization",
"author": "Peter Voigt",
"author_email": "",
"download_url": "https://files.pythonhosted.org/packages/f9/76/4838bc9e07465915b8e825eaa5328a06c52f3227553436bca45b2dd7c3ef/parcoords-0.1.4.tar.gz",
"platform": null,
"description": "\n[](https://pypi.org/project/parcoords/)\n[](https://voigtpeter.github.io/parcoords/index.html)\n\n# Parallel Coordinates Plotting for Python `parcoords`\n\nThis package implements a parallel-coordinate plot, commonly used in machine learning, i.e. for hyperparameter visualization.\n\n<p align=\"center\">\n <img alt=\"Example parallel-coordinate plot\" src=\"https://raw.githubusercontent.com/VoigtPeter/parcoords/main/img/example_plot.png\">\n</p>\n\n## Installation\nThe `parcoords` package can be installed with pip:\n```\npip install parcoords\n```\nYou can also view the package on [PyPI](https://pypi.org/project/parcoords/).\n\n## Usage\nThe following code produces the sample plot at the beginning of this page.\n```python\nimport matplotlib.pyplot as plt\nfrom parcoords import plot_parcoords\n\n# let's define some data to plot\nvalues = [\n [0.1, 10, \"smote\", 0.78],\n [0.15, 9, \"none\", 0.46],\n [0.18, 8, \"rand_over\", 0.67],\n [0.01, 16, \"rand_over\", 0.84],\n [0.01, 15, \"smote\", 0.86],\n [0.015, 12, \"smote\", 0.87],\n [0.03, 12, \"smote\", 0.81],\n [0.12, 13, \"none\", 0.51],\n [0.07, 11, \"rand_over\", 0.7],\n [0.2, 14, \"none\", 0.55],\n]\n\n# plot the values as parallel-coordinate plot\nplot_parcoords(\n values,\n labels=[\"lr\", \"# epochs\", \"sampling method\", \"accuracy\"],\n color_field=\"accuracy\",\n scale=[(\"lr\", \"log\")],\n title=\"Parallel-Coordinates of the Hyperparameters\",\n)\n\nplt.show()\n```\n\n## License\nThis repository is licensed under the [MIT-License](https://github.com/VoigtPeter/parcoords/blob/main/LICENSE.txt).\n",
"bugtrack_url": null,
"license": "MIT",
"summary": "Parallel coordinates plotting",
"version": "0.1.4",
"project_urls": {
"Documentation": "https://voigtpeter.github.io/parcoords/index.html",
"Homepage": "https://github.com/VoigtPeter/parcoords",
"Source": "https://github.com/VoigtPeter/parcoords"
},
"split_keywords": [
"parallel coordinates",
"parallel-coordinates",
"plot",
"hyperparameter",
"visualization"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "c1834756c3edb110432765f409b46906095ba9074292573375189c4e23c75f49",
"md5": "2a60f5ef770ee5d781ab6007b2f7adda",
"sha256": "0eb02413a4d1871c1199d2cb9b774099d240f3d58e76172ee7360e4e6929ed88"
},
"downloads": -1,
"filename": "parcoords-0.1.4-py3-none-any.whl",
"has_sig": false,
"md5_digest": "2a60f5ef770ee5d781ab6007b2f7adda",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.6",
"size": 5367,
"upload_time": "2023-07-18T13:44:33",
"upload_time_iso_8601": "2023-07-18T13:44:33.401196Z",
"url": "https://files.pythonhosted.org/packages/c1/83/4756c3edb110432765f409b46906095ba9074292573375189c4e23c75f49/parcoords-0.1.4-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "f9764838bc9e07465915b8e825eaa5328a06c52f3227553436bca45b2dd7c3ef",
"md5": "1c4fa428c5d469d7006af07fbf3c1144",
"sha256": "b93b1b57fa7f8f41601fcf10048a460b96d6282eca8d4453ca9529d3761b808f"
},
"downloads": -1,
"filename": "parcoords-0.1.4.tar.gz",
"has_sig": false,
"md5_digest": "1c4fa428c5d469d7006af07fbf3c1144",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.6",
"size": 5029,
"upload_time": "2023-07-18T13:44:34",
"upload_time_iso_8601": "2023-07-18T13:44:34.522697Z",
"url": "https://files.pythonhosted.org/packages/f9/76/4838bc9e07465915b8e825eaa5328a06c52f3227553436bca45b2dd7c3ef/parcoords-0.1.4.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2023-07-18 13:44:34",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "VoigtPeter",
"github_project": "parcoords",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"lcname": "parcoords"
}
JSON
