User Guide
==========

Comprehensive guides for using edaflow effectively in your data analysis workflows.

.. toctree::
   :maxdepth: 2

   data_quality
   visualization
   advanced_features
   best_practices

Overview
--------

The edaflow User Guide is organized into four main sections:

**Data Quality & Cleaning**
~~~~~~~~~~~~~~~~~~~~~~~~~~~
Learn how to assess data quality, handle missing values, convert data types, and prepare your data for analysis.

* Missing data analysis and visualization
* Categorical data insights and type conversion
* Data imputation strategies
* Outlier detection and handling

**Visualization & Analysis**
~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Explore edaflow's comprehensive visualization capabilities for understanding your data.

* Distribution analysis with boxplots and histograms
* Interactive visualizations with Plotly
* Correlation and relationship analysis
* Advanced scatter matrix analysis

**Advanced Features**
~~~~~~~~~~~~~~~~~~~~
Discover advanced features and customization options for power users.

* Custom thresholds and parameters
* Integration with other libraries
* Performance optimization tips
* Extension and customization

**Best Practices**
~~~~~~~~~~~~~~~~~~
Learn recommended workflows and best practices for effective EDA.

* Recommended EDA workflow
* Memory and performance considerations
* Jupyter notebook integration
* Troubleshooting common issues

Getting Started
---------------

If you're new to edaflow, we recommend starting with the :doc:`../quickstart` guide, then exploring each section of this user guide based on your specific needs.

For complete function documentation, see the :doc:`../api_reference/index`.
