semvec/pypi-packages huggingface dataset:
tseuler 0.0.4.dev0
A library for Time-Series exploration, analysis & modelling.
Requires Python: >=3.7

<img style="float: right;" src="examples/logo_big.png"  width='100%'>

# tseuler
A library for Time Series exploration, analysis & modelling. This includes -


As of now, this libray is in pre-alpha phase, i.e there is a lot of work still left before its first stable release.

### TSMAD - Time Series Mini Analysis DashBoard.
Functionalities Include

    - A mini Dashboard for Time Series Analysis, with multiple variations to each kind of analysis
    - Inbuilt Freqency Variation analysis
    - Intervention Analysis (In Future) 
    

### TSSTATS - Time Series Statistical & Modelling Functions
Functionalities Include:

    - Rolling Origin Framework (Currently Supports - statsmodels, sklearn, sklearn) for both multi-variate and uni-variate
    - Residual Diagnostics
    - Statistical Tests
    - Entropy Calculations
    - Intervention Analysis (In Future)

## Example
****
<img style="float: right;" src="examples/example_gif.gif"  width='100%'>

## Installation
****
Installation 
```py
pip install tseuler
```
## Usage
****
- ### Instantiating a DashBoard
    
    ```py
    import pandas as pd
    import tseuler as tse
    # Read the Time Series DataFrame
    dataDF = pd.read_csv('Raw Data/stocks_data.csv', index_col=0)
    tsmadObj = tse.TSMAD(tsdata = dataDF, data_desc = 'Stocks Data',
                     target_columns = ['close'], categorical_columns = ['Name'],
                     dt_format = '%Y-%m-%d', dt_freq = 'B',
                     how_aggregate = {'open':'first', 'high':'max', 'low':'min', 'close':'last'},
                     force_interactive = True)
    tsmadObj.get_board()
    ```

`tseuler` has been built upon:-
****
- pandas
- numpy
- panel
- altair
- matplotlib
- statsmodels



## History
****
<u>v0.0.4dev0 : Development Package</u>
- Added TSMAD
- Added TSSTATS
pomodoro-DEN-ik 0.0.2
Simple concentrator based on pomodoro technique
Requires Python: >=3.6

# Work Concentrator

[Web-page with examples](https://darkdream99.github.io/WorkConcentrator/)

Tool that helps you to keep your concentration on the important work

## Requirements

1. Python 3 interpreter;
2. `notify-send` lib for Linux (for notification features) 

## Installation

1. Clone this repository;
2. Select your python environment (via venv for example);
3. Double check that you use `python3` (you can run: `which python` on Unix)
4. Run: `python3 <path-to-work_concentrator.py>`


### Additional:
- For Linux users:
    - nothing

- For Windows users:
    - nothing

- For MacOS users:
    - nothing

## User guide

Working process are divided by short breaks on iterations. 

One iteration is:
- 25 min working
    - 5 min break
- 25 min working
    - 5 min break
- 25 min working
    - 5 min break
- 25 min working
- 20 min break

After last (20 min) break new iteration will be started.

To start timer you should click on the `Start` button.
If the work is finished you can click `Reset` to reset timer state or just close the application.

In the bottom you can see how many stages of the iteration were passed. One stage contains (`work` + `break`) time line.


## Versions

- 0.1.0 - Initial version:
    - Start looped iterations (25 5 25 5 25 5 25 20) mins
    - Reset timer