semvec/pypi-packages huggingface dataset:
topsis-tanisha-101803042 1.2
Topsis Score and Rank generator
License: MIT
Keywords: topsis,topsis score,rank,Thapar

# TOPSIS
Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is a multi-criteria decision making method. 
The method is based on finding an ideal and an anti-ideal solution and comparing the distance of each one of the alternatives to those.
TOPSIS chooses the alternative of shortest Euclidean distance from the ideal solution, and greatest distance from the negative-ideal solution.

## Package Usage
To install the package:  
**pip install topsis_tanisha_101803042**  
This is a package focusing on finding the topsis score and rank of a dataframe **(csv file)** with only numerical values.

## Python IDLE or any Editor   
> import topsis_tanisha_101803042.topsis  
> f = "input_csv_filepath"  
> w = "1,1,1,1"  
> im = "+,+,+,-"  
> r = "result_csv_filepath"  
> topsis_tanisha_101803042.topsis.rank(f,w,im,r)  
The final result can be seen in the result file given as r.
toggldash 1.0.6
plots data from toggl track
License: MIT
Requires Python: >=3.7

# Toggl Dashboard
#### This small project helps you run a Dash app on localhost, in which you can see where you time has been used using data from Toggl track. Its just a more comprehensive report of your data. 
#### You can see the the project on [PYPI](https://pypi.org/project/toggldash/) too. In order to run the program, install the package using the code below:

```
pip install toggldash
```
</br>

#### You can run the dashboard using the python code below:
```python
from toggldash import app
app.run()
```
</br>

#### The program then asks you your toggl credentials. It saves them in a file in your current directory called creds.txt. The file will look something like this
```

    email:yourawesome@email.com
    token:348975634875687ygegy85534653
    workspace_id:5525432
    
```

#### Or you can just create a file with the creds in it. The above creds won't work.
#### By default the app will run on http://127.0.0.1:8050/

</br>

![](https://github.com/bigpappathanos-web/Toggl-Dashboard/blob/main/toggldash/images/Peek%202020-10-12%2013-26.gif?raw=true )