Skip to main content

Make simple, pretty Sankey Diagrams (Beta version)

Project description

pySankey

Uses matplotlib to create simple Sankey diagrams flowing only from left to right.

PyPI version Build Status Coverage Status Code style: black License: GPL v3

Requirements

Requires python-tk (for python 2.7) or python3-tk (for python 3.x) install with apt-get or your package manager.

You can install the other requirements with:

    pip install -r requirements.txt

Example

With fruits.txt :

true predicted
0 blueberry orange
1 lime orange
2 blueberry lime
3 apple orange
... ... ...
996 lime orange
997 blueberry orange
998 orange banana
999 apple lime

1000 rows × 2 columns

You can generate a sankey's diagram with this code:

import pandas as pd
from pysankey import sankey

df = pd.read_csv(
    'pysankey/fruits.txt', sep=' ', names=['true', 'predicted']
)
colorDict = {
    'apple':'#f71b1b',
    'blueberry':'#1b7ef7',
    'banana':'#f3f71b',
    'lime':'#12e23f',
    'orange':'#f78c1b',
    'kiwi':'#9BD937'
}

ax = sankey(
    df['true'], df['predicted'], aspect=20, colorDict=colorDict,
    leftLabels=['banana','orange','blueberry','apple','lime'],
    rightLabels=['orange','banana','blueberry','apple','lime','kiwi'],
    fontsize=12
)
plt.show() # to display
plt.savefig('fruit.png', bbox_inches='tight') # to save

Fruity Alchemy

You could also use weight:

,customer,good,revenue
0,John,fruit,5.5
1,Mike,meat,11.0
2,Betty,drinks,7.0
3,Ben,fruit,4.0
4,Betty,bread,2.0
5,John,bread,2.5
6,John,drinks,8.0
7,Ben,bread,2.0
8,Mike,bread,3.5
9,John,meat,13.0
import pandas as pd
from pysankey import sankey

df = pd.read_csv(
    'pysankey/customers-goods.csv', sep=',',
    names=['id', 'customer', 'good', 'revenue']
)
weight = df['revenue'].values[1:].astype(float)

ax = sankey(
      left=df['customer'].values[1:], right=df['good'].values[1:],
      rightWeight=weight, leftWeight=weight, aspect=20, fontsize=20
)
plt.show() # to display
plt.savefig('customers-goods.png', bbox_inches='tight') # to save

Customer goods

Similar to seaborn, you can pass a matplotlib Axes to sankey function:

import pandas as pd
from pysankey import sankey
import matplotlib.pyplot as plt

df = pd.read_csv(
        'pysankey/fruits.txt',
        sep=' ', names=['true', 'predicted']
)
colorDict = {
    'apple': '#f71b1b',
    'blueberry': '#1b7ef7',
    'banana': '#f3f71b',
    'lime': '#12e23f',
    'orange': '#f78c1b'
}

ax1 = plt.axes()

sankey(
      df['true'], df['predicted'], aspect=20, colorDict=colorDict,
      fontsize=12, ax=ax1
)

plt.show()

Important informations

Use of figureName, closePlot, figSize in sankey() is deprecated and will be remove in a future version. This is done so matplotlib is used more transparently as this issue on the original github repo suggested.

Now, sankey does less of the customization and let the user do it to their liking by returning a matplotlib Axes object, which mean the user also has access to the Figure to customise. Then they can choose what to do with it - showing it, saving it with much more flexibility.

Recommended changes to your code

  • To save a figure, one can simply do:
  plt.savefig("<figureName>.png", bbox_inches="tight", dpi=150)
  • The closePlot is not needed anymore because without plt.show() after sankey(), no plot is displayed. You can still do plt.close() to be sure to not display this plot if you display other plots afterwards.

  • You can modify the sankey size by changing the one from the matplotlib figure.

      plt.gcf().set_size_inches(figSize)
    

Package development

Lint

pylint pysankey

Testing

python -m unittest

Coverage

coverage run -m unittest
coverage html
# Open htmlcov/index.html in a navigator

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for pySankeyBeta, version 1.1.0
Filename, size File type Python version Upload date Hashes
Filename, size pySankeyBeta-1.1.0.tar.gz (537.9 kB) File type Source Python version None Upload date Hashes View hashes

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page