## About the Package:
The package was an assignment in a course I had taken about Machine Learning.
The package is about making the Gaussian, and the Binomial distribution easy to work with .
There's The Gaussian sub Module, and the Binomial sub Module as well.
## Features:
With The package , you can :
* Read from the dataset.
* calculate the mean for the Gaussian distribution, and the Binomial distribution as well.
* calculate the standard deviation .
* Plot the histogram of the data.
* Calculate the probability density function for the distribution.
* Plot the probability density function.
* Add two Gaussian Distributions .
* Add two Binomial Distributions (if only they have the same probability p, the complex case is not developed yet may be soon).
Raw data
{
"_id": null,
"home_page": "",
"name": "gauss-binomial-statdist",
"maintainer": "",
"docs_url": null,
"requires_python": "",
"maintainer_email": "",
"keywords": "python,gaussian,binomial,distributions,mean,standard deviation,statistics",
"author": "Oumayma EL-FAHSI",
"author_email": "<oumayma.elfahsi@ump.ac.ma>",
"download_url": "https://files.pythonhosted.org/packages/d9/00/5261f201377db4f8519d593460b1ba8b77a06859b05195b0353a716bc120/gauss_binomial_statdist-0.0.3.tar.gz",
"platform": null,
"description": "\r\n## About the Package:\r\n\r\nThe package was an assignment in a course I had taken about Machine Learning.\r\n\r\n\r\n\r\nThe package is about making the Gaussian, and the Binomial distribution easy to work with .\r\n\r\nThere's The Gaussian sub Module, and the Binomial sub Module as well.\r\n\r\n## Features:\r\n\r\nWith The package , you can :\r\n\r\n* Read from the dataset.\r\n\r\n* calculate the mean for the Gaussian distribution, and the Binomial distribution as well.\r\n\r\n* calculate the standard deviation .\r\n\r\n* Plot the histogram of the data.\r\n\r\n* Calculate the probability density function for the distribution.\r\n\r\n* Plot the probability density function.\r\n\r\n* Add two Gaussian Distributions .\r\n\r\n* Add two Binomial Distributions (if only they have the same probability p, the complex case is not developed yet may be soon).\r\n\r\n",
"bugtrack_url": null,
"license": "",
"summary": "Code to enable the use of the gaussian and the binomial distributions",
"version": "0.0.3",
"split_keywords": [
"python",
"gaussian",
"binomial",
"distributions",
"mean",
"standard deviation",
"statistics"
],
"urls": [
{
"comment_text": "",
"digests": {
"md5": "9975ede89f775e6fec7753a8bf046401",
"sha256": "530c9c9727f78a9406153b33e77105937fbd14fbea03fa94b635efbc3700e608"
},
"downloads": -1,
"filename": "gauss_binomial_statdist-0.0.3-py3-none-any.whl",
"has_sig": false,
"md5_digest": "9975ede89f775e6fec7753a8bf046401",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": null,
"size": 6431,
"upload_time": "2022-12-05T10:15:07",
"upload_time_iso_8601": "2022-12-05T10:15:07.680698Z",
"url": "https://files.pythonhosted.org/packages/d9/d5/b25b2bfcd160b965c5b042090812682feb9b3b72a585a848a6fb56504e85/gauss_binomial_statdist-0.0.3-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"md5": "5b5bf1e566acccece348ce82c82c8fb5",
"sha256": "c51b1c0185f81439f368ad893da10ef400f1c89cf46da1512a6c2d3b81fb5bf3"
},
"downloads": -1,
"filename": "gauss_binomial_statdist-0.0.3.tar.gz",
"has_sig": false,
"md5_digest": "5b5bf1e566acccece348ce82c82c8fb5",
"packagetype": "sdist",
"python_version": "source",
"requires_python": null,
"size": 4992,
"upload_time": "2022-12-05T10:15:10",
"upload_time_iso_8601": "2022-12-05T10:15:10.147475Z",
"url": "https://files.pythonhosted.org/packages/d9/00/5261f201377db4f8519d593460b1ba8b77a06859b05195b0353a716bc120/gauss_binomial_statdist-0.0.3.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2022-12-05 10:15:10",
"github": false,
"gitlab": false,
"bitbucket": false,
"lcname": "gauss-binomial-statdist"
}
JSON