semvec/pypi-packages huggingface dataset:
standings 1.0.4
Python library to calculate standings for football and handball
Keywords: football soccer handball table match matches fixture fixtures

Standings
=========

Python library to calculate standings for football and handball

Getting Started
---------------

pip install standings

Alternatively: copy the standings package to your project.

Prerequisites
~~~~~~~~~~~~~

Should work with Python 2.7 and up or 3. Possibly other versions
(untested).

Usage
~~~~~

It’s best to see `standingstest.py <standingstest.py>`__ for reference.

Basic usage is as follows:

::

            # Handball 3. Liga Herren, Saison 2015/16, 17. Spieltag
            # Create ranking calculation oject with scope, sports type and mode
            t1 = Standings(TABLE_ALL, SPORTSTYPES.HANDBALL, CALCULATION_MODE_DIRECT_COMPARE)

            # add your matches / fixtures (upto desired match day or all)
            t1.add_match(_Match('DHK Flensborg', 35551, 'SC Magdeburg II', 35561, 41, 23))
            t1.add_match(_Match('SV Meck.-Schwerin', 35651, 'TS Großburgwedel', 35661, 26, 17))
            ...

            tb = t1.get_table()
            # tb is now the sorted table

\_Match may be replaced with your own object but as a minimum requires a
team name and id for both participiants and goals for the home and away
team.

The module supports two modes for calculation:
CALCULATION_MODE_GOAL_DIFFERENCE and CALCULATION_MODE_DIRECT_COMPARE.
The first one uses points, followed by goal difference and then goals
scored as sort order (as used in German Bundesliga for example).

CALCULATION_MODE_DIRECT_COMPARE will first sort by points, then the
result of direct comparison between teams with equal points (often used
in handball or the Spanish La Liga).

Tests
-----

Some tests are supplied and can be run like this:

::

    python -m unittest standings
    python -m unittest standings.teampoint

Authors
-------

-  **Marco Wilka** - *Initial work* -
   `marcowilka <https://github.com/marcowilka>`__

License
-------

This project is licensed under the MIT License - see the
`LICENSE.txt <LICENSE.txt>`__ file for details
PyWrangler 0.0.2
A python package containing some easy-to-use tools for data cleaning / Exploration and ML.

**PyWrangler:**

A python package containing some easy-to-use functions for cleaning data. 
The package contains functions that allow you explore your data easily to:

- Find missing/null values visually
- Remove missing values
- Find categorcial variables in your datatset
- Remove highly correlated values.
- Plot bar graphs and automatically add the percentages of variables.
- Plot twin axis bar graphs
- Adjust size of bars in bar graphs
- Machine Learning for classification problems.
tablecalculation 1.0.3
Python library to calculate tables for football and handball
Keywords: football soccer handball table match matches fixture fixtures

Project Title
=============

Python library to calculate tables for football and handball

Getting Started
---------------

pip install tablecalculation

Alternatively: copy the tablecalculation package to your project.

Prerequisites
~~~~~~~~~~~~~

Should work with Python 2.7 and up or 3. Possibly other versions
(untested).

Usage
~~~~~

It’s best to see `tablecalculationtest.py <tablecalculationtest.py>`__
for reference.

Basic usage is as follows:

::

            # Handball 3. Liga Herren, Saison 2015/16, 17. Spieltag
            # Create table calculation oject with scope, sports type and mode
            t1 = TableCalculation(TABLE_ALL, SPORTSTYPES.HANDBALL, CALCULATION_MODE_DIRECT_COMPARE)

            # add your matches / fixtures (upto desired match day or all)
            t1.add_match(_Match('DHK Flensborg', 35551, 'SC Magdeburg II', 35561, 41, 23))
            t1.add_match(_Match('SV Meck.-Schwerin', 35651, 'TS Großburgwedel', 35661, 26, 17))
            ...

            tb = t1.get_table()
            # tb is now the sorted table

\_Match may be replaced with your own object but as a minimum requires a
team name and id for both participiants and goals for the home and away
team.

The module supports two modes for calculation:
CALCULATION_MODE_GOAL_DIFFERENCE and CALCULATION_MODE_DIRECT_COMPARE.
The first one uses points, followed by goal difference and then goals
scored as sort order (as used in German Bundesliga for example).

CALCULATION_MODE_DIRECT_COMPARE will first sort by points, then the
result of direct comparison between teams with equal points (often used
in handball or the Spanish La Liga).

Tests
-----

Some tests are supplied and can be run like this:

::

    python -m unittest tablecalculation
    python -m unittest tablecalculation.teampoint

Authors
-------

-  **Marco Wilka** - *Initial work* -
   `marcowilka <https://github.com/marcowilka>`__

License
-------

This project is licensed under the MIT License - see the
`LICENSE.txt <LICENSE.txt>`__ file for details