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<h1>pathpy: path data analysis<a class="headerlink" href="#pathpy-path-data-analysis" title="Permalink to this headline">¶</a></h1>
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<div class="col-md-6"><p>pathpy is an OpenSource python package for the analysis of time series data on
networks using higher- and multi-order network models.</p>
<p>pathpy is specifically tailored to analyse temporal networks as well as time
series and sequence data that capture multiple short, independent paths observed
in an underlying graph or network. Examples for data that can be analysed with
pathpy include time-stamped social networks, user click streams in information
networks, biological pathways, citation networks, or information cascades in
social networks.</p>
<p>For a brief introduction to the ideas behind the library, you can read the
<a class="reference internal" href="introduction.html"><span class="doc">introductory notes</span></a>. Visit the <a class="reference internal" href="installation.html"><span class="doc">installation page</span></a> to see how you can download the package. You can browse the
<a class="reference internal" href="examples/index.html"><span class="doc">example gallery</span></a> to see what you can do with pathpy, and
then check out the <a class="reference internal" href="tutorial.html"><span class="doc">tutorial</span></a> and <a class="reference internal" href="api.html"><span class="doc">API reference</span></a> to
find out how.</p>
<p>To see the code or report a bug, please visit the <a class="reference external" href="https://github.com/pathpy/pathpy">github repository</a>. General support issues are most at home
on <a class="reference external" href="https://stackoverflow.com/">stackoverflow</a>, where there is a pathpy tag. This project is a community effort, and everyone is welcome to <a class="reference internal" href="contribution.html"><span class="doc">contribute</span></a>.</p>
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