# Topsis-102103596
Library for calculating topsis score and rank for a Multi Criteria Decision Making problem.
## Usage
#### Installation
```sh
pip install topsis-102103596
```
#### Usage
Contains a single function
**cal_topsis_score(df,w,i,out_file):**
where:
df -> pd.DataFrame
w -> list of weights (only numeric columns are considered, rest are ignored)
i -> impact list ("+" for columns that are to be maximized, "-" for columns to be minimized, for example ["-","+","+","+"])
out_file -> csv file in which output Dataset will be stored
#### Screenshots
Input file: data.csv
![Data.csv](images/data.png)
Output file: out.csv
![Output.csv](images/out.png)
Raw data
{
"_id": null,
"home_page": "https://github.com/Hitesh-Aggarwal/topsis-102103596",
"name": "topsis-102103596",
"maintainer": "",
"docs_url": null,
"requires_python": "",
"maintainer_email": "",
"keywords": "topsis,Decision Making,Data Analytics",
"author": "Hitesh Aggarwal",
"author_email": "haggarwal_be21@thapar.edu",
"download_url": "https://files.pythonhosted.org/packages/fc/55/d2941a85e56b8b96f52de9cc9f0ffd56895a9e9f0e801bb46159b413740c/topsis-102103596-0.2.tar.gz",
"platform": null,
"description": "# Topsis-102103596\nLibrary for calculating topsis score and rank for a Multi Criteria Decision Making problem.\n\n## Usage\n#### Installation\n```sh\npip install topsis-102103596\n```\n\n#### Usage\nContains a single function\n**cal_topsis_score(df,w,i,out_file):**\n\nwhere:\n\n df -> pd.DataFrame\n\n w -> list of weights (only numeric columns are considered, rest are ignored)\n\n i -> impact list (\"+\" for columns that are to be maximized, \"-\" for columns to be minimized, for example [\"-\",\"+\",\"+\",\"+\"])\n\n out_file -> csv file in which output Dataset will be stored\n \n#### Screenshots\nInput file: data.csv\n\n![Data.csv](images/data.png)\n\nOutput file: out.csv\n\n![Output.csv](images/out.png)\n",
"bugtrack_url": null,
"license": "MIT",
"summary": "Calculates the topsis score",
"version": "0.2",
"project_urls": {
"Download": "https://github.com/Hitesh-Aggarwal/topsis-102103596/archive/refs/tags/v_02.tar.gz",
"Homepage": "https://github.com/Hitesh-Aggarwal/topsis-102103596"
},
"split_keywords": [
"topsis",
"decision making",
"data analytics"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "525968c60cace91306046c65a4069459c4226f04575b15badb9008426049ae5b",
"md5": "ed3b9d4489219808734de3ef5effc762",
"sha256": "7ea81d1479e54af09b9d5eaf7a0beb1de1e1c6f9e347023f3f07d803363f48b8"
},
"downloads": -1,
"filename": "topsis_102103596-0.2-py3-none-any.whl",
"has_sig": false,
"md5_digest": "ed3b9d4489219808734de3ef5effc762",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": null,
"size": 3657,
"upload_time": "2024-01-21T21:00:39",
"upload_time_iso_8601": "2024-01-21T21:00:39.314162Z",
"url": "https://files.pythonhosted.org/packages/52/59/68c60cace91306046c65a4069459c4226f04575b15badb9008426049ae5b/topsis_102103596-0.2-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "fc55d2941a85e56b8b96f52de9cc9f0ffd56895a9e9f0e801bb46159b413740c",
"md5": "ee4e5c74a0b21c83df45bfa3858decd4",
"sha256": "eee0251db2383d2cfe1a59820e096620c976f8b583e359abe74e255d42cc1404"
},
"downloads": -1,
"filename": "topsis-102103596-0.2.tar.gz",
"has_sig": false,
"md5_digest": "ee4e5c74a0b21c83df45bfa3858decd4",
"packagetype": "sdist",
"python_version": "source",
"requires_python": null,
"size": 3701,
"upload_time": "2024-01-21T21:00:40",
"upload_time_iso_8601": "2024-01-21T21:00:40.660725Z",
"url": "https://files.pythonhosted.org/packages/fc/55/d2941a85e56b8b96f52de9cc9f0ffd56895a9e9f0e801bb46159b413740c/topsis-102103596-0.2.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-01-21 21:00:40",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "Hitesh-Aggarwal",
"github_project": "topsis-102103596",
"travis_ci": false,
"coveralls": false,
"github_actions": false,
"lcname": "topsis-102103596"
}