Metadata-Version: 2.1
Name: datasist
Version: 1.0
Summary: A Machine learning library that abstracts repetitve functions used by data scientist and machine learning engineers
Home-page: https://github.com/risenW/datasist
Author: Rising Odegua
Author-email: risingodegua@gmail.com
License: MIT
Download-URL: https://github.com/risenW/datasist/archive/1.0.tar.gz
Description: <div align="center">
          <img src='datasist.png' alt="datasist" style="width: 500px; height: 350px; margin-left: 200px;">
        </div>
        
        # datasist: Python library for easy data modeling, visualization, exploration and analysis.
        <table>
        <tr>
          <td>Latest Release</td>
          <td>
            <a href="https://pypi.org/project/datasist/">
            <img src="https://img.shields.io/badge/pip-v0.1-blue.svg" alt="latest release" />
            </a>
          </td>
        </tr>
        <tr>
          <td>Release Status</td>
          <td>
            <a>
            <img src="https://img.shields.io/badge/status-alpha-brightgreen.svg" alt="status" />
            </a>
          </td>
        </tr>
        <tr>
          <td>License</td>
          <td>
            <a>
            <img src="https://img.shields.io/badge/license-MIT-orange.svg" alt="license" />
                 </a>
        </td>
        </tr>
          
        <tr>
          <td>Build Status</td>
          <td>
            <a>
            <img src="https://travis-ci.org/risenW/datasist.svg?branch=master" alt="build status" />
                 </a>
        </td>
          
        </tr>
        
        </table>
        
        ## What is it?
        
        **datasist** is a python package providing fast, quick, and an abstracted interface to 
        popular and frequently used functions or techniques relating to data analysis, visualization, data exploration,
        feature engineering, Computer, NLP, Deep Learning, modeling, model deployment etc.
        
        ## Install
        ```sh
        pip install datasist
        ```
        
        ## Dependencies
        - Numpy
        - pandas
        - seaborn
        - matplotlib
        - scikit-learn
        
        
        ## Installation from source
        To install datasist from source you need python 3.6> in addition to the normal
        dependencies above. 
        
        Run the following command in a terminal/command prompt
        
        ```sh
        git clone https://github.com/risenW/datasist.git
        cd datasist
        python setup.py install
        ```
        
        Alternatively, you can use install with `pip` after cloning, if you want all the dependencies pulled
        in automatically (the `-e` option is for installing it in [development
        mode]:
        
        ```sh
        git clone https://github.com/risenW/datasist.git
        cd datasist
        pip install -e .
        ```
        
        ## Documentation
        API documentation can be found [here](https://risenw.github.io/datasist/index.html)
        
        ## Contributing to datasist
        
        All contributions, bug reports, bug fixes, documentation improvements, enhancements and ideas are welcome.
        
        A detailed overview on how to contribute can be found in the **[contributing guide](https://risenw.github.io/datasist/contributing.html)**.
        
        If you are simply looking to start working with the datasist codebase, navigate to the [GitHub "issues"tab](https://github.com/risenW/datasist/issues) and start looking through interesting issues. There are a number of issues listed under good first issue where you could start out.
        
        
        ### Example Usage
        
        [Classification problem using Xente fraud dataset](https://risenw.github.io/datasist/classification_example.html)
        
        [Basic example using the Iris dataset](https://github.com/risenW/datasist/blob/master/datasist/examples/Example_irisdata.ipynb)
        
Keywords: Data Analysis,Feature Engineering,Visualization
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Build Tools
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Description-Content-Type: text/markdown
