docs: overhaul

An overhaul of the documentation -- almost a complete re-write.
Main differences:
* Added quick-start examples and other examples
* Added many internal and external links
* Changed structure (notably *getting started* and *advanced usage* sections transformed into *usage*)

docs/api_reference.rst

@@ -1,4 +1,4 @@
-API reference
+API Reference
 =============
 
 .. toctree::

docs/index.rst

@@ -1,15 +1,12 @@
 EDVART
 ================================
 
-Exploratory Data Analysis (EDA) is a very initial task a data scientist
-or data analyst does when he reaches new data.
-EDA refers to the critical process of performing
-initial investigations on data to discover patterns, to spot
-anomalies, to test hypothesis and to check assumptions with the help
-of summary statistics and graphical representations.
+Edvart is an open-source Python library designed to simplify and streamline
+your exploratory data analysis (EDA) process.
+Edvart supports different levels of customization:
+from a default report generated in one line of code to a fully-customized
+report down to the level of code generating the visualizations.
 
-EDVART serves for speeding up EDA and for
-creating Data analysis reports.
 
 Table of Contents
 -----------------
@@ -18,15 +15,16 @@ Table of Contents
   :maxdepth: 2
 
   installation.rst
-  getting_started.rst
-  advanced.rst
+  usage.rst
+  sections.rst
   api_reference.rst
 
 .. include:: installation.rst
-.. include:: getting_started.rst
+.. include:: usage.rst
+.. include:: sections.rst
 
 Links
------------
+-----
 * `GitHub repository <https://github.com/datamole-ai/edvart>`_
 
 * :ref:`modindex`

docs/installation.rst

@@ -1,14 +1,15 @@
 Installation
 ============
 
-edvart is distributed via PyPI.
-Example installation with pip:
+``edvart`` is distributed as a Python package via `PyPI <https://pypi.org/project/edvart/>`_.
+It can be installed using ``pip``:
 
 .. code-block:: console
 
    $ pip install edvart
 
-or you can add edvart into your environment file defined by `pyproject.toml`:
+We recommend using `Poetry <https://python-poetry.org/>` for dependency management.
+You can add ``edvart`` into your Poetry environment file defined by ``pyproject.toml``:
 
 .. parsed-literal::
 
@@ -17,54 +18,57 @@ or you can add edvart into your environment file defined by `pyproject.toml`:
    edvart = "|VERSION|"
 
 
+.. _extras:
+
 Extras
 ------
 
-edvart also has an optional dependency "umap", which adds a plot called UMAP
-(Universal Manifold Approximation) to Multivariate Analysis. To install edvart with the optional
-extra, replace the above snippet of the `pyproject.toml` environment file with the following
-snippet:
+The ``edvart`` package has an optional dependency ``umap``, which adds a plot called `UMAP <https://umap-learn.readthedocs.io/en/latest/>`_
+to :ref:`Multivariate Analysis <multivariate_analysis>`.
+
+To install edvart with the optional ``umap`` dependency via pip, run the following command:
+
+.. code-block:: console
+
+   $ pip install "edvart[umap]"
+
+To install edvart with the optional extra using Poetry, replace the snippet
+of the ``pyproject.toml`` environment file above with the following snippet:
 
 .. parsed-literal::
 
    [tool.poetry.dependencies]
    python = ">=3.8, <3.12"
    edvart = { version = "|VERSION|", extras = ["umap"] }
 
-To install edvart with the optional "umap" dependency via pip, run the following command:
+Rendering Plotly Interactive Plots
+----------------------------------
 
-.. code-block:: console
-
-   $ pip install "edvart[umap]"
-
-
-Plotly
-======
+Edvart uses
 
 JupyterLab
-----------
+~~~~~~~~~~
 
 To display interactive plots which use Plotly in JupyterLab, you need to install some JupyterLab
 extensions.
 
-To install the required extensions, you can follow the full guide at
-https://plot.ly/python/getting-started/ or simply run the following commands
-(inside the JupyterLab container if running in a container):
+You need to install the ``jupyter-dash`` extension to render Plotly plots in
+JupyterLab. You can simply install it as a Python package to your environment,
+e.g. via ``pip``:
 
 .. code-block:: console
 
-   jupyter labextension install @jupyter-widgets/[email protected] --no-build
-   jupyter labextension install [email protected] --no-build
-   jupyter labextension install [email protected] --no-build
-   jupyter lab build
+   pip install jupyter-dash
 
-Visual Studio Code
-------------------
-To display interactive plots which use Plotly in Visual Studio Code notebooks,
-you need to install the following extensions:
-
-* `Jupyter <https://marketplace.visualstudio.com/items?itemName=ms-toolsai.jupyter>`_ is required to
-  run Jupyter notebooks in Visual Studio Code.
-* `Jupyter Notebook Renderers <https://marketplace.visualstudio.com/items?itemName=ms-toolsai.jupyter-renderers>`_ is required
-  to render Plotly plots in Visual Studio Code notebooks.
+See https://plot.ly/python/getting-started/ for more information.
 
+Visual Studio Code
+~~~~~~~~~~~~~~~~~~
+The following extensions need to be installed to display Plotly
+interactive plots in Visual Studio Code notebooks:
+
+* `Jupyter <https://marketplace.visualstudio.com/items?itemName=ms-toolsai.jupyter>`_
+   is required to
+   run Jupyter notebooks in Visual Studio Code.
+* `Jupyter Notebook Renderers <https://marketplace.visualstudio.com/items?itemName=ms-toolsai.jupyter-renderers>`_
+   is required to render Plotly plots in Visual Studio Code notebooks.