semvec/pypi-packages huggingface dataset:
SoSciKit 0.4.0
Social Science Kit - Open Source Software for Social Science
License: MIT
Keywords: Social Science,Software,Data,Analysis


# SoSciKit
  ## Social Science Kit - Open Source Software for Social Science

  SoSciKit is a web application for simplified data analysis based on Python scientific libraries and Flask.
  The web application allows to use the python libraries through a graphical interface even to those who do not know programming language. At the moment the application allows to perform monovariate, bivariate, cross tabulation and k-mean classification operations. In addition, it allows to recode categorical variables and create typologies.

  [![Downloads](https://pepy.tech/badge/soscikit)](https://pepy.tech/project/soscikit)
  [![Downloads](https://pepy.tech/badge/soscikit/week)](https://pepy.tech/project/soscikit/week)

  ## Installation and dependencies
  You need a python interpeter installed on PC / Server. 
  You need Python 3 (tested 3.6 - 3.7) to run this package. Other dependencies can be found in the requirements files

  ### Using pip

  You can install using the pip package manager by running

      pip3.x install soscikit

  ## Usage

  You can start SoScikit by running

      python3.x -m soscikit

  it's start server and open your browser on localhost http://127.0.0.1:5555/


  ## How to contribute

  The package is actively maintained and developed as open-source software. If SoSciKit was helpful or interesting to you, you might want to get involved. There are several ways of contributing and helping. If you would like to be a industry partner or sponsor, please [drop us a line](mailto:scarselli@gmail.com).

  ## Demo

  You can try a [DEMO](http://soscikit.eu.pythonanywhere.com/)
keras-gym 0.2.17
Plug-n-play reinforcement learning with OpenAI Gym and Keras
License: MIT


keras-gym: Plug-n-play reinforcement learning in python with OpenAI Gym and
Keras.

For full documentation, go to:

    https://keras-gym.readthedocs.io

You can find the source code at:

    https://github.com/KristianHolsheimer/keras-gym