semvec/pypi-packages huggingface dataset:
topsis-VK 1.0.0
A Python package implementing TOPSIS technique used to solve the multi criteria decision making problems.
License: MIT

# TOPSIS-Python

**Assignment 1 : UCS654 Predictive Analysis using Statistics**

**Author - Vardaan Khosla(102003295), TIET Patiala**

## What is TOPSIS

**T**echnique for **O**rder **P**reference by **S**imilarity to **I**deal
**S**olution (TOPSIS) originated in the 1980s as a multi-criteria decision
making method. TOPSIS chooses the alternative of shortest Euclidean distance
from the ideal solution, and greatest distance from the negative-ideal
solution.

<br>

## This is how we can use the developed package:

Topsis-VardaanKhosla-102003295 package can be run as follows:

### In the Command Prompt type:

```
>> topsis input_data.csv "0.25,0.25,0.25,0.25" "+,+,-,+" output_data.csv
```

## Sample dataset

The decision matrix (`a`) should be constructed with each row representing a Model alternative, and each column representing a criterion like Accuracy, R<sup>2</sup>, Root Mean Squared Error, Correlation, and many more.The number of entries in the impacts and weights column must be equal to the number of columns starting from the 2nd column in the input dataset. For example, in this case there are 4 columns consisting of parameters which affect the decision making procedure. Each column will have an according weight and impact associated to it.

| Model | Correlation | R<sup>2</sup> | RMSE | Accuracy |
| ----- | ----------- | ------------- | ---- | -------- |
| M1    | 0.79        | 0.62          | 1.25 | 60.89    |
| M2    | 0.66        | 0.44          | 2.89 | 63.07    |
| M3    | 0.56        | 0.31          | 1.57 | 62.87    |
| M4    | 0.82        | 0.67          | 2.68 | 70.19    |
| M5    | 0.75        | 0.56          | 1.3  | 80.39    |

Weights (`w`) is not already normalised will be normalised later in the code.

Information of benefit positive(+) or negative(-) impact criteria should be provided in `I`.

<br>

## Output

The output will consist of the original csv file along with two additional columns Topsis Score and Rank.

```
Model  Topsis Score    Rank
-----  ------------    ----
  1    0.77221          2
  2    0.225599         5
  3    0.438897         4
  4    0.523878         3
  5    0.811389         1 
```

<br>
taoist 0.7.3
Python-based Terminal Utility for Todoist
License: MIT
Requires Python: >=3.6

<img src="docs/source/images/taijitu.png" width="100" />

# Taoist: Python-based Terminal Utility for Todoist

[![pipeline status](https://gitlab.com/popgendad/taoist/badges/main/pipeline.svg)](https://gitlab.com/popgendad/taoist/-/commits/main)
      

This project is still under development and is not yet ready for release. It is a simple utility that relies on the [official Todoist Python REST API](https://github.com/Doist/todoist-api-python). This software is not created by, affiliated with, or supported by Doist. The `taoist` utility has functionality for performing basic transactions involving Todoist projects, sections, labels and tasks. The goal of the project is to enable most major components of 
a ["getting-things-done"](https://todoist.com/productivity-methods/getting-things-done) workflow from a terminal environment and is not intended to replicate the functionality of the Todoist app.

## Quick Start

 The taoist package can be installed via PyPi
 ```
 $ pip3 install taoist
 ```
 Next, connect `taoist` to your Todoist account. First you must retrieve your API token from the Todoist app.
 Once you have your API token, you can authenticate to the web service by running
 ```
 taoist init --token <TOKEN>
 ```
 if run without the `--token` switch, you will be interactively prompted to provide the API token.

 To see your list of projects, run
 ```
 taoist project list
 ```
 Similarly, to see your list of tasks, run
 ```
 taoist task list
 ```

## Documentation

Please visit [readthedocs](https://taoist.readthedocs.io/en/latest) for full documentation of the `taoist` project