[DOCUMENTATION] FINAL for v1.1.0 (#1324)

* [DOCUMENTATION] PART1 for v1.1.0

[DOC PART2]

We then need to do the following tasks:
 - [ ] Remove the notebook archive, the script to generate the file due to the nested structure
 - [ ] Compile the doc

* Update user_guide_full_stack_complex_data_vmap.rst

* Update user_guide_full_stack_vdataframe_magic.rst

* Update user_guide_data_preparation_joins.rst

* removed default directory -> SPHINX_DIRECTORY

* removed notebooks

* Added whats new for 1.1.0

* added function for QueryProfilerComparison

* some corrections

* corrections

* Update whats_new_v1_1_0.rst

added a line for deprecations

* Update whats_new_v1_1_0.rst

added pls

* fixed customer testimonial heights

* multiple corrections

* corrections

* Fixed sizes of some RSTS

* Update _corr.py

added `with_numbers` parameter for correlation matrix

* Update examples_business.rst

* Update examples.rst

* done with example tiles

* adding images

---------

Co-authored-by: Umar Farooq Ghumman <umarfarooq.ghumman@vertica.com>

docs/source/_static/css/custom_styling.css

@@ -552,6 +552,11 @@ body {
   height: 370px; /* Adjust the desired height */
 }
 
+.custom-card-customer-test {
+  height: 520px; /* Adjust the desired height */
+}
+
+
 /* Cards on Machine Learning page */
 .custom-card-3 {
   height: 250px; /* Adjust the desired height */
@@ -1014,6 +1019,7 @@ article, article .align-default {
     height: 400px; /* Adjust the desired height */
     /* Add more styles as needed */
   }
+
 }
 
 @media (max-width: 36em) {
@@ -1054,6 +1060,7 @@ article, article .align-default {
 .custom-card-14 {
   height: 190px;
 }
+
 }
 
 @media (max-width: 62em) {
@@ -1081,6 +1088,7 @@ article, article .align-default {
 .custom-card-15 {
   height: 240px;
 }
+
 }
 @media (max-width: 90em) {
   .right-content {
@@ -1140,7 +1148,11 @@ article, article .align-default {
 @media (max-width: 40em) {
   .home_button_container{
     /* display: none */
-}
+  }
+  /* Cards on Index page */
+  .custom-card-customer-test {
+    height: 450px; /* Adjust the desired height */
+  }
 }
 
 /* Loader GIF for pages */

docs/source/chart_gallery_acf.rst

@@ -18,14 +18,14 @@ Auto-Correlation Plot
 General
 -------
 
-Let's begin by importing `VerticaPy`.
+Let's begin by importing ``verticapy``.
 
 .. ipython:: python
 
     import verticapy as vp
 
 
-Let's import the amazon dataset from `VerticaPy`.
+Let's import the amazon dataset from ``verticapy``.
 
 .. code-block:: python
         
@@ -41,7 +41,7 @@ In the context of data visualization, we have the flexibility to harness multipl
 
 .. note::
 
-    To select the desired plotting library, we simply need to use the `set_option` function. VerticaPy offers the flexibility to smoothly transition between different plotting libraries. In instances where a particular graphic is not supported by the chosen library or is not supported within the VerticaPy framework, the tool will automatically generate a warning and then switch to an alternative library where the graphic can be created.
+    To select the desired plotting library, we simply need to use the :py:func:`~verticapy.set_option` function. VerticaPy offers the flexibility to smoothly transition between different plotting libraries. In instances where a particular graphic is not supported by the chosen library or is not supported within the VerticaPy framework, the tool will automatically generate a warning and then switch to an alternative library where the graphic can be created.
 
 Please click on the tabs to view the various graphics generated by the different plotting libraries.
 
@@ -57,7 +57,7 @@ Please click on the tabs to view the various graphics generated by the different
 
         vp.set_option("plotting_lib", "plotly")
 
-    We can switch to using the `plotly` module.
+    We can switch to using the ``plotly`` module.
 
     .. code-block:: python
         
@@ -106,7 +106,7 @@ Please click on the tabs to view the various graphics generated by the different
 
         vp.set_option("plotting_lib", "highcharts")
 
-    We can switch to using the `highcharts` module.
+    We can switch to using the ``highcharts`` module.
 
     .. code-block:: python
         
@@ -159,7 +159,7 @@ Please click on the tabs to view the various graphics generated by the different
 
         vp.set_option("plotting_lib", "matplotlib")
 
-    We can switch to using the `matplotlib` module.
+    We can switch to using the ``matplotlib`` module.
 
     .. code-block:: python
         

docs/source/chart_gallery_animated.rst

@@ -23,7 +23,7 @@ Animated Plots
 General
 -------
 
-Let's begin by importing the dataset module of `VerticaPy`. It provides a range of datasets for both training and exploring VerticaPy's capabilities.
+Let's begin by importing the dataset module of ``verticapy``. It provides a range of datasets for both training and exploring VerticaPy's capabilities.
 
 .. ipython:: python
 
@@ -60,7 +60,7 @@ VerticaPy's animated charts, including bar races, bubble animations, pie chart t
 
         vp.set_option("plotting_lib", "matplotlib")
 
-    We can switch to using the `matplotlib` module.
+    We can switch to using the ``matplotlib`` module.
 
     .. code-block:: python
         

docs/source/chart_gallery_area.rst

@@ -24,7 +24,7 @@ Area Plots
 General
 -------
 
-Let's begin by importing `VerticaPy`.
+Let's begin by importing ``verticapy``.
 
 .. ipython:: python
 
@@ -51,7 +51,7 @@ In the context of data visualization, we have the flexibility to harness multipl
 
 .. note::
 
-    To select the desired plotting library, we simply need to use the `set_option` function. VerticaPy offers the flexibility to smoothly transition between different plotting libraries. In instances where a particular graphic is not supported by the chosen library or is not supported within the VerticaPy framework, the tool will automatically generate a warning and then switch to an alternative library where the graphic can be created.
+    To select the desired plotting library, we simply need to use the :py:func:`~verticapy.set_option` function. VerticaPy offers the flexibility to smoothly transition between different plotting libraries. In instances where a particular graphic is not supported by the chosen library or is not supported within the VerticaPy framework, the tool will automatically generate a warning and then switch to an alternative library where the graphic can be created.
 
 Please click on the tabs to view the various graphics generated by the different plotting libraries.
 
@@ -67,7 +67,7 @@ Please click on the tabs to view the various graphics generated by the different
 
         vp.set_option("plotting_lib", "plotly")
 
-    We can switch to using the `plotly` module.
+    We can switch to using the ``plotly`` module.
 
     .. code-block:: python
         
@@ -186,7 +186,7 @@ Please click on the tabs to view the various graphics generated by the different
 
         vp.set_option("plotting_lib", "highcharts")
 
-    We can switch to using the `highcharts` module.
+    We can switch to using the ``highcharts`` module.
 
     .. code-block:: python
         
@@ -316,7 +316,7 @@ Please click on the tabs to view the various graphics generated by the different
 
         vp.set_option("plotting_lib", "matplotlib")
 
-    We can switch to using the `matplotlib` module.
+    We can switch to using the ``matplotlib`` module.
 
     .. code-block:: python
         

docs/source/chart_gallery_bar.rst

@@ -23,7 +23,7 @@ Bar Chart
 General
 -------
 
-Let's begin by importing `VerticaPy`.
+Let's begin by importing ``verticapy``.
 
 .. ipython:: python
 
@@ -49,7 +49,7 @@ In the context of data visualization, we have the flexibility to harness multipl
 
 .. note::
 
-    To select the desired plotting library, we simply need to use the `set_option` function. VerticaPy offers the flexibility to smoothly transition between different plotting libraries. In instances where a particular graphic is not supported by the chosen library or is not supported within the VerticaPy framework, the tool will automatically generate a warning and then switch to an alternative library where the graphic can be created.
+    To select the desired plotting library, we simply need to use the :py:func:`~verticapy.set_option` function. VerticaPy offers the flexibility to smoothly transition between different plotting libraries. In instances where a particular graphic is not supported by the chosen library or is not supported within the VerticaPy framework, the tool will automatically generate a warning and then switch to an alternative library where the graphic can be created.
 
 Please click on the tabs to view the various graphics generated by the different plotting libraries.
 
@@ -65,7 +65,7 @@ Please click on the tabs to view the various graphics generated by the different
 
         vp.set_option("plotting_lib", "plotly")
 
-    We can switch to using the `plotly` module.
+    We can switch to using the ``plotly`` module.
 
     .. code-block:: python
         
@@ -344,7 +344,7 @@ Please click on the tabs to view the various graphics generated by the different
 
         vp.set_option("plotting_lib", "highcharts")
 
-    We can switch to using the `highcharts` module.
+    We can switch to using the ``highcharts`` module.
 
     .. code-block:: python
         
@@ -707,7 +707,7 @@ Please click on the tabs to view the various graphics generated by the different
 
         vp.set_option("plotting_lib", "matplotlib")
 
-    We can switch to using the `matplotlib` module.
+    We can switch to using the ``matplotlib`` module.
 
     .. code-block:: python
         

docs/source/chart_gallery_boxplot.rst

@@ -26,13 +26,13 @@ Boxplot
 General
 -------
 
-Let's begin by importing `VerticaPy`.
+Let's begin by importing ``verticapy``.
 
 .. ipython:: python
 
     import verticapy as vp
 
-Let's also import `numpy` to create a random dataset.
+Let's also import ``numpy`` to create a random dataset.
 
 .. ipython:: python
 
@@ -59,7 +59,7 @@ In the context of data visualization, we have the flexibility to harness multipl
 
 .. note::
 
-    To select the desired plotting library, we simply need to use the `set_option` function. VerticaPy offers the flexibility to smoothly transition between different plotting libraries. In instances where a particular graphic is not supported by the chosen library or is not supported within the VerticaPy framework, the tool will automatically generate a warning and then switch to an alternative library where the graphic can be created.
+    To select the desired plotting library, we simply need to use the :py:func:`~verticapy.set_option` function. VerticaPy offers the flexibility to smoothly transition between different plotting libraries. In instances where a particular graphic is not supported by the chosen library or is not supported within the VerticaPy framework, the tool will automatically generate a warning and then switch to an alternative library where the graphic can be created.
 
 Please click on the tabs to view the various graphics generated by the different plotting libraries.
 
@@ -75,7 +75,7 @@ Please click on the tabs to view the various graphics generated by the different
 
         vp.set_option("plotting_lib", "plotly")
 
-    We can switch to using the `plotly` module.
+    We can switch to using the ``plotly`` module.
 
     .. code-block:: python
         
@@ -156,7 +156,7 @@ Please click on the tabs to view the various graphics generated by the different
 
         vp.set_option("plotting_lib", "highcharts")
 
-    We can switch to using the `highcharts` module.
+    We can switch to using the ``highcharts`` module.
 
     .. code-block:: python
         
@@ -239,7 +239,7 @@ Please click on the tabs to view the various graphics generated by the different
 
         vp.set_option("plotting_lib", "matplotlib")
 
-    We can switch to using the `matplotlib` module.
+    We can switch to using the ``matplotlib`` module.
 
     .. code-block:: python
         

docs/source/chart_gallery_candlestick.rst

@@ -22,7 +22,7 @@ Candlestick
 General
 -------
 
-Let's begin by importing `VerticaPy`.
+Let's begin by importing ``verticapy``.
 
 .. ipython:: python
 
@@ -47,7 +47,7 @@ In the context of data visualization, we have the flexibility to harness multipl
 
 .. note::
 
-    To select the desired plotting library, we simply need to use the `set_option` function. VerticaPy offers the flexibility to smoothly transition between different plotting libraries. In instances where a particular graphic is not supported by the chosen library or is not supported within the VerticaPy framework, the tool will automatically generate a warning and then switch to an alternative library where the graphic can be created.
+    To select the desired plotting library, we simply need to use the :py:func:`~verticapy.set_option` function. VerticaPy offers the flexibility to smoothly transition between different plotting libraries. In instances where a particular graphic is not supported by the chosen library or is not supported within the VerticaPy framework, the tool will automatically generate a warning and then switch to an alternative library where the graphic can be created.
 
 Please click on the tabs to view the various graphics generated by the different plotting libraries.
 
@@ -63,7 +63,7 @@ Please click on the tabs to view the various graphics generated by the different
 
         vp.set_option("plotting_lib", "plotly")
 
-    We can switch to using the `plotly` module.
+    We can switch to using the ``plotly`` module.
 
     .. code-block:: python
         
@@ -123,7 +123,7 @@ Please click on the tabs to view the various graphics generated by the different
 
         vp.set_option("plotting_lib", "highcharts")
 
-    We can switch to using the `highcharts` module.
+    We can switch to using the ``highcharts`` module.
 
     .. code-block:: python
         
@@ -185,7 +185,7 @@ Please click on the tabs to view the various graphics generated by the different
 
         vp.set_option("plotting_lib", "matplotlib")
 
-    We can switch to using the `matplotlib` module.
+    We can switch to using the ``matplotlib`` module.
 
     .. code-block:: python
         

docs/source/chart_gallery_champion_challenger.rst

@@ -42,7 +42,7 @@ General
 
 VerticaPy's AutoML (Automated Machine Learning) feature is a robust and user-friendly tool that simplifies the complex process of machine learning model development. It automates critical tasks such as algorithm selection, hyperparameter tuning, feature engineering, and cross-validation, significantly reducing the time and effort required to build high-performing predictive models. With its scalability, transparency, and ease of use, VerticaPy's AutoML empowers data analysts and scientists to efficiently harness the potential of machine learning, even in large-scale and complex data environments, enabling organizations to make data-driven decisions with confidence and precision.
 
-Let's begin by importing `VerticaPy`.
+Let's begin by importing ``verticapy``.
 
 .. ipython:: python
 
@@ -89,7 +89,7 @@ In the context of data visualization, we have the flexibility to harness multipl
 
 .. note::
 
-    To select the desired plotting library, we simply need to use the `set_option` function. VerticaPy offers the flexibility to smoothly transition between different plotting libraries. In instances where a particular graphic is not supported by the chosen library or is not supported within the VerticaPy framework, the tool will automatically generate a warning and then switch to an alternative library where the graphic can be created.
+    To select the desired plotting library, we simply need to use the :py:func:`~verticapy.set_option` function. VerticaPy offers the flexibility to smoothly transition between different plotting libraries. In instances where a particular graphic is not supported by the chosen library or is not supported within the VerticaPy framework, the tool will automatically generate a warning and then switch to an alternative library where the graphic can be created.
 
 Please click on the tabs to view the various graphics generated by the different plotting libraries.
 
@@ -105,7 +105,7 @@ Please click on the tabs to view the various graphics generated by the different
 
         vp.set_option("plotting_lib", "plotly")
 
-    We can switch to using the `plotly` module.
+    We can switch to using the ``plotly`` module.
 
     .. code-block:: python
         
@@ -134,7 +134,7 @@ Please click on the tabs to view the various graphics generated by the different
 
         vp.set_option("plotting_lib", "highcharts")
 
-    We can switch to using the `highcharts` module.
+    We can switch to using the ``highcharts`` module.
 
     .. code-block:: python
         
@@ -165,7 +165,7 @@ Please click on the tabs to view the various graphics generated by the different
 
         vp.set_option("plotting_lib", "matplotlib")
 
-    We can switch to using the `matplotlib` module.
+    We can switch to using the ``matplotlib`` module.
 
     .. code-block:: python
         

docs/source/chart_gallery_classification_curve.rst

@@ -31,7 +31,7 @@ In this classification example, our goal is to develop a predictive model that c
 The objective is to demonstrate how to plot ROC curves, Precision-Recall curves, or even gain curves by building a logistic regression model. 
 Furthermore, we will illustrate how to create these curves using just two columns: one for probabilities and one for predictions.
 
-Let's begin by importing `VerticaPy`.
+Let's begin by importing ``verticapy``.
 
 .. ipython:: python
 
@@ -80,7 +80,7 @@ In the context of data visualization, we have the flexibility to harness multipl
 
 .. note::
 
-    To select the desired plotting library, we simply need to use the `set_option` function. VerticaPy offers the flexibility to smoothly transition between different plotting libraries. In instances where a particular graphic is not supported by the chosen library or is not supported within the VerticaPy framework, the tool will automatically generate a warning and then switch to an alternative library where the graphic can be created.
+    To select the desired plotting library, we simply need to use the :py:func:`~verticapy.set_option` function. VerticaPy offers the flexibility to smoothly transition between different plotting libraries. In instances where a particular graphic is not supported by the chosen library or is not supported within the VerticaPy framework, the tool will automatically generate a warning and then switch to an alternative library where the graphic can be created.
 
 Please click on the tabs to view the various graphics generated by the different plotting libraries.
 
@@ -96,7 +96,7 @@ Please click on the tabs to view the various graphics generated by the different
 
         vp.set_option("plotting_lib", "plotly")
 
-    We can switch to using the `plotly` module.
+    We can switch to using the ``plotly`` module.
 
     .. code-block:: python
         
@@ -201,7 +201,7 @@ Please click on the tabs to view the various graphics generated by the different
 
         vp.set_option("plotting_lib", "highcharts")
 
-    We can switch to using the `highcharts` module.
+    We can switch to using the ``highcharts`` module.
 
     .. code-block:: python
         
@@ -318,7 +318,7 @@ Please click on the tabs to view the various graphics generated by the different
 
         vp.set_option("plotting_lib", "matplotlib")
 
-    We can switch to using the `matplotlib` module.
+    We can switch to using the ``matplotlib`` module.
 
     .. code-block:: python