.. 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