A Python library that convert time series to direction Graph to discover the story within data.
Project 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/
[![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/
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