timelyportfolio / seaborn

Statistical data visualization using matplotlib

Seaborn: statistical data visualization

Seaborn is a Python visualization library based on matplotlib. It provides a high-level interface for drawing attractive statistical graphics.

Documentation

Online documentation is available here.

Examples

The documentation has an example gallery with short scripts showing how to use different parts of the package. You can also check out the example notebooks:

• Controlling figure aesthetics in seaborn

• Graphical representations of linear models

• Visualizing distributions of data

• Plotting statistical timeseries data

Dependencies

• Python 2.7 or 3.3+

Mandatory

• numpy

• scipy

• matplotlib

• pandas

Recommended

• statsmodels

• patsy

Installation

To install the released version, just do

pip install seaborn

You may instead want to use the development version from Github, by running

pip install git+git://github.com/mwaskom/seaborn.git#egg=seaborn

Testing

To test seaborn, run make test in the source directory. This will run the unit-test suite (using nose). It will also execute the example notebooks and compare the outputs of each cell to the data in the stored versions.

Development

https://github.com/mwaskom/seaborn

Please submit any bugs you encounter to the Github issue tracker.

License

Released under a BSD (3-clause) license

Celebrity Endorsements

"Those are nice plots" -Hadley Wickham