Welcome to the crandas documentation!
==========================================

**Roseman Labs** is software for secure data collaboration, based on multi-party computation (MPC).
**Crandas** is a DataFrame library made to interact with the Roseman Labs cryptographic engine.
With crandas, users can interact with data using MPC in a way familiar to data scientists without having to worry about the underlying cryptography.

Crandas can do the following:
   - Data filtering and tabular manipulation
   - Combination of different data sources
   - Secure aggregations and other data analyses
Crandas also has an ever-growing library of privacy-preserving machine learning algorithms:
   - Linear and logistic regression
   - Random forests and k-nearest neighbors
   - Hypothesis testing and other descriptive statistics


If you are new to crandas, the :ref:`gettingstarted` guide will walk you through the process of installation up to basic data manipulation.
If you are familiar with other DataFrame libraries, such as pandas, you might want to read :ref:`this<crandasVpandas>` to find the essential differences.


For more in-depth information about functionalities, consult the :ref:`userguide`.
Additionally, you can go through some :ref:`tutorials` to familiarize yourself with the different features present in crandas.
Finally, for more generic information about Roseman Labs, the components it consists of and the role that crandas has as a part of this, visit the `product page <https://support.rosemanlabs.com/i-want-to-understand-the-product-better>`_ of the Roseman Labs Help Center.


.. toctree::
   :maxdepth: 1
   :caption: Getting started

   gettingstarted/index

.. toctree::
   :maxdepth: 1
   :caption: User Guide

   Introduction <guide/index>
   guide/index_data_manipulation
   guide/index_crlearn
   guide/index_authorization

.. toctree::
   :maxdepth: 1
   :caption: Reference

   api/index
   limitations.rst

.. toctree::
   :maxdepth: 1
   :caption: Tutorials
   :titlesonly:
   
   tutorials/index

.. Download the `zip file for tutorial data and notebooks (Jupyter) <_static/tutorial_data_notebooks.zip>`_.
   
   


Index
^^^^^^^^^^^^^^^
* :ref:`genindex`
* :ref:`funcindex`