.. raw:: html
.. role:: orange
.. title:: Retentioneering Tools
retentioneering documentation
=============================
**Date:** May 03, 2023
.. grid:: 4
.. grid-item-card:: Descriptive methods
:img-top: _static/tool_icons/describe.png
:link: eventstream_descriptive_methods
:link-type: ref
.. grid-item-card:: Transition graph
:img-top: _static/tool_icons/transition_graph.png
:link: /user_guides/transition_graph
:link-type: doc
.. grid-item-card:: Step Sankey
:img-top: _static/tool_icons/step_sankey.png
:link: /user_guides/step_sankey
:link-type: doc
.. grid-item-card:: Step matrix
:img-top: _static/tool_icons/step_matrix.png
:link: /user_guides/step_matrix
:link-type: doc
.. grid:: 4
.. grid-item-card:: Clusters
:img-top: _static/tool_icons/clusters.png
:link: /user_guides/clusters
:link-type: doc
.. grid-item-card:: Cohorts
:img-top: _static/tool_icons/cohorts.png
:link: /user_guides/cohorts
:link-type: doc
.. grid-item-card:: Funnel
:img-top: _static/tool_icons/funnel.png
:link: /user_guides/funnel
:link-type: doc
.. grid-item-card:: Preprocessing Graph :orange:`(beta)`
:img-top: _static/tool_icons/preprocessing_graph.png
:link: /user_guides/preprocessing
:link-type: doc
Installation
============
Retentioneering can be installed via pip using `PyPI `_.
.. code-block:: python
pip install retentioneering
Or directly from Jupyter notebook or `google.colab `_.
.. code-block:: ipython
!pip install retentioneering
Contents
========
.. toctree::
:maxdepth: 1
Getting started
.. toctree::
:maxdepth: 1
User guide
.. toctree::
:maxdepth: 1
API reference
.. toctree::
:maxdepth: 1
Tutorials
.. toctree::
:maxdepth: 1
Datasets
.. toctree::
:maxdepth: 1
Release notes