semvec/pypi-packages huggingface dataset:
dumbledore 0.0.5
a python package to visvalize features of data and observe relation without writing lots of codes
Requires Python: >=3.6

# Dumbledore
this is a python module which is intended for data scientist and statistician to visualize features and understand relationships between different features without writing lots of codes. <br>
This module is like an aggregator which combines multiple functionalities of different modules and brings them together to keep you out of trouble

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__installation__
```
pip install dumbledore
```

__requirements__ <br>
this module depends on all most of scientific libraries like `pandas` , `matplotlib` , `seaborn`, `numpy` etc. all of which you must have already installed if you are a data scientist or statistician but don't worry if you haven't the pip command will automatically install all the dependencies.

__examples__ <br>
the  `vis_feature()` function helps you understand and visualize between different types of variables
1. for a continuous feature and categorical target variable
```python
import dumbledore as db
import pandas as pd
...
# load data
...
db.basics.vis_feature((data , 'gender' , 'tenure', 'gist_earth_r' , target_continous=True , jitter=0.3)
```
![data](https://github.com/imZain448/dumbledore/blob/master/images/data11.png?raw=true)
![plot](https://github.com/imZain448/dumbledore/blob/master/images/plot1.png?raw=true)

1. when your feature and target both are continous
```python
db.basics.vis_feature((data , 'tenure' , 'MonthlyCharges', 'gist_earth_r' , continous=True , target_continous=True )
```
![data2](https://github.com/imZain448/dumbledore/blob/master/images/data22.PNG?raw=true)
![plot2](https://github.com/imZain448/dumbledore/blob/master/images/plot2.png?raw=true)

similarly you can feed in categorical target or categorical feature you have to keep in mind the two arguements
>__continous__ : True if feature is continous, False if feature categorical<br> 
>__target_continous__ : True if target variable is continous , False if target variable is categorical


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__note__ : this module is still under development and has been released as alpha. so if you get any bug please open a issue without hesitation. or if you want a new feature please make a feature request

> _THIS PRODUCT IS DISTRIBUTED UNDER GNU GPLv3 WHICH CAN BE FOUND IN THE LICENSE FILE_

__developed by__ : [imzain448](https://github.com/imZain448) <br>
meet me on
- [Linkedin](https://www.linkedin.com/in/zain-ahmad-15aa25162/)
- [Instagram](https://www.instagram.com/imzain448/?hl=en)
- Gmail : ahmadzain.448@gmail.com
ettuparser-DJENTELMAN 1.0
This package parses ETTU site for mass transit schedule.
Requires Python: >=3.6

# ETTUParser

*DISCLAIMER: Корректная работа модуля не гарантируется, так как возможны ~~изменения сайта ETTU~~ второе пришествие и судный день.*

This project parses ETTU(Ekaterinburg Tram and Trolley Administration) site for mass transit schedule. 

Этот проект парсит сайт ЕТТУ(Екатеринбургское трамвайно-троллейбусное управление) на предмет времени до прибытия троллейбуса/трамвая на остановку.

*The documentation for this repository is written in Russian, cause a problem that this project solves is applicable only to Yekaterinburg.*

## Использование
Данный модуль зависит от `lxml` и `pandas`.

Единственной функцией данного модуля(на данный момент) является `ettuparser.parseStation(stationID)`. Параметр `stationID` можно взять из URL остановки, информацию о которой требуется получить. К примеру: ht<span>tps://</span>mobile.ettu.ru/station/***3431*** ~~(на разных остановках разное количество символов, возможно, зависит от вида транспорта)~~ (неважно). Возвращает данная функция `pandas.DataFrame`.
DbObjectCreator 1.0.14
A database object creator
Requires Python: >=3.7

# Database Object Creator (D.O.C.)
This library provides a method of creating database connector objects for quick and easy access to multiple
databases (both types and servers).

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## DOC Setup
This library can be installed via Pypi.org[https://pypi.org/project/DbObjectCreator/] or locally:

Run `pip install Cython` before proceeding with either install. This package is required prior to installing this library.
This library can now be installed by running `pip install DbObjectCreator`

## DOC Usage
1. Import the library into your project using `from DbObjectCreator import DbObjectCreator`
2. Create a new DbObject using `new_db = DbObjectCreator.DbObject()`
3. new_db can now be used to call multiple methods against the database.


This library supports both Windows and OSX architecture. If installing on OSX you will need FreeTDS installed.