We introduce the pyunicorn (Pythonic unified complex network and recurrence analysis
toolbox) open source software package for applying and combining modern methods of data
analysis and modeling from complex network theory and nonlinear time series analysis.
pyunicorn is a fully object-oriented and easily parallelizable package written in the language
Python. It allows for the construction of functional networks such as climate networks in climatology
or functional brain networks in neuroscience representing the structure of statistical interrelationships
in large data sets of time series and, subsequently, investigating this structure using
advanced methods of complex network theory such as measures and models for spatial networks,
networks of interacting networks, node-weighted statistics, or network surrogates. Additionally,
pyunicorn provides insights into the nonlinear dynamics of complex systems as recorded in
uni- and multivariate time series from a non-traditional perspective by means of recurrence quanti-
fication analysis, recurrence networks, visibility graphs, and construction of surrogate time series.
The range of possible applications of the library is outlined, drawing on several examples mainly
from the field of climatology