semvec/pypi-packages huggingface dataset:
uncleschool 0.3
OOP Learning Example by Uncle Engineer
License: MIT
Keywords: OOP Python,THAI,Uncle Engineer

นี่คือตัวอย่างโปรแกรมสำหรับการเรียน OOP
=======================================

วิธีติดตั้ง
~~~~~~~~~~~

เปิด CMD / Terminal

.. code:: python

    pip install uncleschool

วิธีเล่น
~~~~~~~~

เปิด IDLE ขึ้นมาแล้วพิมพ์...

.. code:: python

    from uncleschool import Student, SpecialStudent

    print('========1 Jan========')
    student0 = SpecialStudent('Mark Zuckerberg','Bill Gates')
    student0.AskEXP()
    student0.ShowEXP()
    student1 = Student('Albert')
    print(student1.name)
    student1.Hello()

    print('------------')
    student2 = Student('Steve')
    print(student2.name)
    student2.Hello()
    print('========2 Jan========')
    print('------uncle: ใครอยากเรียนโค้ดดิ้ง?---(ให้ 10 exp)----')
    student1.AddEXP(10)

    print('========3 Jan========')
    student1.name = 'Albert Einstein'
    print('ตอนนี้ exp ของแต่ละคนได้เท่าไรกันแล้ว')

    print(student1.name, student1.exp)
    print(student2.name, student2.exp)
    print('========4 Jan========')

    for i in range(5):
        student2.Coding()

    student1.ShowEXP()
    student2.ShowEXP()

พัฒนาโดย: ลุงวิศวกร สอนคำนวณ FB: https://www.facebook.com/UncleEngineer
YouTube: https://www.youtube.com/UncleEngineer
splitio-requests 1.2.1
Split.io Admin API wrapper
License: MIT
Requires Python: >=3.6, <4
Keywords: Split.io,split,API wrapper,api,requests

********************************************
Split.io Admin API wrapper
********************************************

.. image:: https://img.shields.io/pypi/v/splitio-requests.svg
   :alt: Current version

.. image:: https://img.shields.io/pypi/l/splitio-requests.svg
   :alt: License

.. image:: https://img.shields.io/pypi/pyversions/splitio-requests.svg
   :alt: PyPI - Python Version

.. image:: https://static.pepy.tech/personalized-badge/splitio-requests?period=total&units=international_system&left_color=black&right_color=orange&left_text=Downloads
   :target: https://pepy.tech/project/splitio-requests
   :alt: Downloads count


Split.io is feature experimentation platform and it has it's public API,
allowing it's customers to interact with their resources.

splitio-requests package makes it easy to interact with Admin API by wrapping endpoint requests and providing
simplified way to access response data and much more.

-------------------

**Quick example on how to use it**

.. code-block:: python

    >>> admin_api = AdminAPI("ADMIN_API_TOKEN")
    >>> resp = admin_api.splits.get_split("awesome_split", "wsid-123")
    >>> resp.status_code
    200
    >>> resp.json()
    {"name": "awesome_split","description": "Great feature",...
    >>> resp.url
    'https://api.split.io/internal/api/v2/splits/ws/wsid-123/'
    >>> resp.headers
    '{"X-RATE-LIMIT":"12"...'
    >>> bool(resp) # When request was successful
    True


What's great about splitio-requests is that it handles Split.io Admin API throttling system with polling and retires.

Those functionalities are configured by default but changes can be made by the user if necessary.

**Other key features**

* Model classes for resources
* Schemas and serializers for payload data validation
pylaxz 0.1.3
A small until for my needs.
License: MIT
Requires Python: >=3.5, <4
Keywords: sample,setuptools,development,pylaxz

#### My Python Utils. TODO


### IF you dont have time.
```
>>> import pylaxz
>>> help(pylaxz)
```
### ELSE
```
python3 -m pylaxz help
```
1. __logxs__
```
>>> from pylaxz.utils.logxs import *
>>> printf(anything) 
```
2. __check__
```
>>> from pylaxz.utils.check import *
>>> speed()
>>> internet()
>>> ip()
```
2. alternative
```
>>> from pylaxz.utils import check as ck
>>> ck.speed()
>>> ck.internet()
>>> ck.ip()
```
2. is equvalient with 
```
>>> import pylaxz
>>> pylaxz.internet()
``` 
so on
 + printf is logger function and works well with python's data types
 + and also with numpy's data shapes.
DescTC 0.1.1
The package includes methods that condense large amounts of information about each variable of your dataset into easy-to-understand formats (table and charts) that clearly and effectively communicate important points.
License: MIT
Requires Python: >=3.6
Keywords: describe,table,chart

# DescTC

When it comes to real-world-data, very often it needs some sort of cleansing job to be done. Missing values and syntax errors are commonly found on databases and we spend most of our time trying to fix them up. 

In order to reduce this time spent, I decided to design a tool that provides you with a wider and quicker vision of the variables that need to be adjusted before you start your own analysis.

Methods provided:

 *DescTC.table( )* 

    Offers you the following information of each quantitative/qualitative variable:

    - Type 
    - Quantity of zero numbers
    - Quantity of NaN's
    - % of NaN's 
    - Quantity of uniques values 
    - Quantity of outliers 
    - Min value / Lowest category 
    - Mean
    - Median
    - Mode
    - Max value / Highest category
    

 *DescTC.chart( )*

    Condense large amounts of information of each variable into easy-to-understand formats 
    that clearly and effectively communicate important points:

    - Plot the distribution of each variable 
    - Box plot of each quantitative variables
    - Plot the correlation between quantitative variables
    
Please be aware that your data must be converted to a pandas DataFrame with column names.

 *DescTC.printfullTable( )* 
    
    - Useful to see the entire outcome independently on which environment you are executing the package.
    
    
# Installation

    - pip install DescTC