A tool for visualizing temporal developments of categorical data.
Project description
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.
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