Metadata-Version: 1.0
Name: graphitty
Version: 0.0.1
Summary: A Python library that convert time series to direction Graph to discover the story within data.
Home-page: https://github.com/sketchytechky/graphitty
Author: Boris Lau
Author-email: boris@techie.im
License: UNKNOWN
Description: 
        # Graphitty
        
        [![Circle CI](https://circleci.com/gh/sketchytechky/graphitty.svg?style=svg&circle-token=<cirlce-ci-token>)](https://circleci.com/gh/sketchytechky/graphitty)
        
        [![Coverage Status](https://coveralls.io/repos/github/sketchytechky/graphitty/badge.svg?branch=master)](https://coveralls.io/github/sketchytechky/graphitty?branch=master)
        
        A Python library that convert time series to direction Graph to discover the story within data.
        
        
        ![Example graph](apollo.png)
        
        
        # Installing
        
        To install this package, runs:
        
            pip install git+https://github.com/sketchytechky/graphitty.git
        
        Remember to add the following line to `requirements.txt`
        
            git+https://github.com/sketchytechky/graphitty.git
        
        
        -----------
        
        
        # How to use
        
        ```
        from graphitty.graphitty import Graphitty
        import pandas as pd
        
        # Example input data - see test_simple.py for example
        df = pd.DataFrame(
                [...],
                columns=['timestamp','action', 'user_id'])
        
        # Parsing and outputting graph
        g = Graphitty(
            df,
            id_col='user_id',
            beahivour_col='action',
            ts_col='timestamp')
        nx_graph = g.render()
        
        # create the beautiful directional graph
        # see https://github.com/chebee7i/nxpd for usage
        import nxpd
        nxpd.draw(nx_graph, show='ipynb')
        ```
        
        # Running Tests
        
        Run test with
        
            py.test --pep8
        
        To run test in watch mode
        
            py.test.watch -- --pep8
            # same with: ptw -- --pep8
        
        
        -----------
        
        
        # Related research
        
        
        * Information Foraging Theory:Adaptive Interaction with Information - http://www.peterpirolli.com/Professional/About_Me_files/IFT%20Ch%201.pdf
        
        
        * Jakob Nielson example on how to apply information foraging theory to understand visitor's behaviour
          - http://www.useit.com/alertbox/scrolling-attention.html
          - https://www.nngroup.com/articles/information-scent/
        
        
Platform: UNKNOWN
