[DOCS] Revamp SedonaKepler and SedonaPyDeck documentation

docs/api/sql/Visualization_SedonaKepler.md

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+SedonaKepler offers a number of APIs which aid in quick and interactive visualization of a geospatial data in a Jupyter notebook/lab environment.
+
+Inorder to start using SedonaKepler, simply import Sedona using:
+```python
+from sedona.spark import *
+```
+
+Alternatively it can also be imported using:
+```python
+from sedona.maps.SedonaKepler import SedonaKepler
+```
+
+Following are details on all the APIs exposed via SedonaKepler:
+
+
+### **Creating a map object using SedonaKepler.create_map**
+
+SedonaKepler exposes a create_map API with the following signature:
+
+```python
+create_map(df: SedonaDataFrame=None, name: str='unnamed', config: dict=None) -> map
+```
+
+
+The parameter 'name' is used to associate the passed SedonaDataFrame in the map object and any config applied to the map is linked to this name. It is recommended you pass a unique identifier to the dataframe here.
+
+If no SedonaDataFrame object is passed, an empty map (with config applied if passed) is returned. A SedonaDataFrame can be added later using the method `add_df`
+
+A map config can be passed optionally to apply pre-apply customizations to the map.
+
+!!!Note
+    The map config references every customization with the name assigned to the SedonaDataFrame being displayed, if there is a mismatch in the name, the config will not be applied to the map object.
+
+
+!!! abstract "Example usage (Referenced from Sedona Jupyter examples)"
+
+	=== "Python"
+		```python
+		map = SedonaKepler.create_map(df=groupedresult, name="AirportCount")
+		map
+		```
+
+### **Adding SedonaDataFrame to a map object using SedonaKepler.add_df**
+SedonaKepler exposes a add_df API with the following signature:
+
+```python
+add_df(map, df: SedonaDataFrame, name: str='unnamed')
+```
+
+This API can be used to add a SedonaDataFrame to an already created map object. The map object passed is directly mutated and nothing is returned.
+
+The parameters name has the same conditions as 'create_map'
+
+!!!Tip
+    This method can be used to add multiple dataframes to a map object to be able to visualize them together.
+
+!!! abstract "Example usage (Referenced from Sedona Jupyter examples)"
+    === "Python"
+    ```python
+    map = SedonaKepler.create_map()
+    SedonaKepler.add_df(map, groupedresult, name="AirportCount")
+    map
+    ```
+
+### **Setting a config via the map**
+A map rendered by accessing the map object created by SedonaKepler includes a config panel which can be used to customize the map
+
+
+### **Saving and setting config**
+
+A map object's current config can be accessed by accessing its 'config' attribute like `map.config`. This config can be saved for future use or use across notebooks if the exact same map is to be rendered every time.
+
+!!!Note
+    The map config references each applied customization with the name given to the dataframe and hence will work only on maps with the same name of dataframe supplied.
+    For more details refer to keplerGl documentation [here](https://docs.kepler.gl/docs/keplergl-jupyter#6.-match-config-with-data)

docs/api/sql/Visualization_SedonaPyDeck.md

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+SedonaPyDeck offers a number of APIs which aid in quick and interactive visualization of a geospatial data in a Jupyter notebook/lab environment.
+
+Inorder to start using SedonaPyDeck, simply import Sedona using:
+```python
+from sedona.spark import *
+```
+
+Alternatively it can also be imported using:
+```python
+from sedona.maps.SedonaPyDeck import SedonaPyDeck
+```
+
+Following are details on all the APIs exposed via SedonaPyDeck:
+
+### **Geometry Map**
+
+```python
+def create_geometry_map(df, fill_color="[85, 183, 177, 255]", line_color="[85, 183, 177, 255]",
+                   elevation_col=0, initial_view_state=None,
+                   map_style=None, map_provider=None):
+```
+
+
+The parameter `fill_color` can be given a list of RGB/RGBA values, or a string that contains RGB/RGBA values based on a column, and is used to color polygons or point geometries in the map
+
+The parameter `line_color` can be given a list of RGB/RGBA values, or a string that contains RGB/RGBA values based on a column, and is used to color the line geometries in the map.
+
+The parameter `elevation_col` can be given a static elevation or elevation based on column values like `fill_color`, this only works for the polygon geometries in the map.
+
+Optionally, parameters `initial_view_state`, `map_style`, `map_provider` can be passed to configure the map as per user's liking.
+More details on the parameters and their default values can be found on the pydeck website as well by deck.gl [here](https://github.com/visgl/deck.gl/blob/8.9-release/docs/api-reference/layers/geojson-layer.md)
+
+
+### **Choropleth Map**
+
+```python
+def create_choropleth_map(df, fill_color=None, plot_col=None, initial_view_state=None, map_style=None,
+						  map_provider=None, elevation_col=0)
+```
+
+The parameter `fill_color` can be given a list of RGB/RGBA values, or a string that contains RGB/RGBA values based on a column.
+
+For example, all these are valid values of fill_color:
+```python
+fill_color=[255, 12, 250]
+fill_color=[0, 12, 250, 255]
+fill_color='[0, 12, 240, AirportCount * 10]' ## AirportCount is a column in the passed df
+```
+
+Instead of giving a `fill_color` parameter, a 'plot_col' can be passed which specifies the column to decide the choropleth.
+SedonaPyDeck then creates a default color scheme based on the values of the column passed.
+
+The parameter `elevation_col` can be given a numeric or a string value (containing the column with/without operations on it) to set a 3D elevation to the plotted polygons if any.
+
+
+Optionally, parameters `initial_view_state`, `map_style`, `map_provider` can be passed to configure the map as per user's liking.
+More details on the parameters and their default values can be found on the pydeck website.
+
+### **Scatterplot**
+
+```python
+def create_scatterplot_map(df, fill_color="[255, 140, 0]", radius_col=1, radius_min_pixels = 1, radius_max_pixels = 10, radius_scale=1, initial_view_state=None, map_style=None, map_provider=None)
+```
+
+The parameter `fill_color` can be given a list of RGB/RGBA values, or a string that contains RGB/RGBA values based on a column.
+
+The parameter `radius_col` can be given a numeric value or a string value consisting of any operations on the column, in order to specify the radius of the plotted point.
+
+The parameter `radius_min_pixels` can be given a numeric value that would set the minimum radius in pixels. This can be used to prevent the plotted circle from getting too small when zoomed out.
+
+The parameter `radius_max_pixels` can be given a numeric value that would set the maximum radius in pixels. This can be used to prevent the circle from getting too big when zoomed in.
+
+The parameter `radius_scale` can be given a numeric value that sets a global radius multiplier for all points.
+
+Optionally, parameters `initial_view_state`, `map_style`, `map_provider` can be passed to configure the map as per user's liking.
+More details on the parameters and their default values can be found on the pydeck website as well by deck.gl [here](https://github.com/visgl/deck.gl/blob/8.9-release/docs/api-reference/layers/scatterplot-layer.md)
+
+
+### **Heatmap**
+
+
+```python
+def create_heatmap(df, color_range=None, weight=1, aggregation="SUM", initial_view_state=None, map_style=None,
+                map_provider=None)
+```
+
+The parameter `color_range` can be optionally given a list of RGB values, SedonaPyDeck by default uses `6-class YlOrRd` as color_range.
+More examples can be found on [colorbrewer](https://colorbrewer2.org/#type=sequential&scheme=YlOrRd&n=6)
+
+The parameter `weight` can be given a numeric value or a string with column and operations on it to determine weight of each point while plotting a heatmap.
+By default, SedonaPyDeck assigns a weight of 1 to each point
+
+The parameter `aggregation` can be used to define aggregation strategy to use when aggregating heatmap to a lower resolution (zooming out).
+One of "MEAN" or "SUM" can be provided. By default, SedonaPyDeck uses "MEAN" as the aggregation strategy.
+
+Optionally, parameters `initial_view_state`, `map_style`, `map_provider` can be passed to configure the map as per user's liking.
+More details on the parameters and their default values can be found on the pydeck website as well by deck.gl [here](https://github.com/visgl/deck.gl/blob/8.9-release/docs/api-reference/aggregation-layers/heatmap-layer.md)