pycatflow 0.0.1

A tool for visualizing temporal developments of categorical data.

PyCatFlow

This package is a visualization tool which allows the representation of temporal developments, based on categorical data.

Install

PyCatFlow is available on PyPi:

$ pip3 install pycatflow

Alternatively you can download the repository and install the package by running the setup.py install routine. Make sure to install the requirements as well:

pip3 install -r requirements.txt
python3 setup.py install

Additional Requirements: The visualization and export is based on the drawSvg package that in turn requires cairo to be installed as an external requirement. Platform-specific instructions for installing cairo are available on the cairo homepage.

On macOS cairo can be installed easily using homebrew:

$ brew install cairo

Basic usage

The visualization library provides many functionalities for adjusting the visual output. It's simplest use is however as follows:

import pycatflow as pcf

# Loading and parsing data:
data = pcf.read_file("sample_data.tsv", columns="versions", nodes="permissions", categories="app_review",
                     column_order="col_order")

# Generating the visualization
viz = pcf.visualize(data, 35, 10, width=1200, height=250, label_size=4, label_shortening="resize")
viz.savePng('sample_viz.png')
viz.saveSvg('sample_viz.svg')
viz

The code and sample data are provided in the example folder. Running it creates this visualization:

Credits

PyCatFlow was conceptualized by Marcus Burkhardt and implemented by Herbert Natta (@herbertmn). It is inspired by the Rankflow visualization tool develped by Bernhard Rieder.