diff --git a/docs/source/adjusting.rst b/docs/source/customizing.rst
similarity index 88%
rename from docs/source/adjusting.rst
rename to docs/source/customizing.rst
index bb39d5c9..397997e9 100644
--- a/docs/source/adjusting.rst
+++ b/docs/source/customizing.rst
@@ -1,5 +1,5 @@
-Adjusting the visualization
-===========================
+Customizing the visualization
+=============================
 
 Once created, a :doc:`VisualizationGraph object <./api-reference/visualization-graph>` can be modified in various ways
 to adjust what the visualization looks like the next time you render it.
@@ -37,8 +37,18 @@ the first positional argument.
 By default the Neo4j color palette that works for both light and dark mode will be used.
 If you want to use a different color palette, you can pass a dictionary or iterable of colors as the ``colors``
 parameter.
-You can for example use the color palettes from the `palettable library <https://jiffyclub.github.io/palettable/>`_ as in
-the following example:
+A color value can for example be either strings like "blue", or hexadecimal color codes like "#FF0000", or even a tuple of RGB values like (255, 0, 255).
+Here is an example of providing a list of custom colors to the ``color_nodes`` method:
+
+.. code-block:: python
+
+    # VG is a VisualizationGraph object
+    VG.color_nodes("caption", ["red", "#7fffd4", (255, 255, 255, 0.5), "hsl(270, 60%, 70%)"])
+
+The full set of allowed values for colors are listed `here <https://docs.pydantic.dev/2.0/usage/types/extra_types/color_types/>`_.
+
+Instead of defining your own colors, you could also for example use the color palettes from the `palettable library <https://jiffyclub.github.io/palettable/>`_ as in
+this snippet:
 
 .. code-block:: python
 
diff --git a/docs/source/index.rst b/docs/source/index.rst
index 525e10be..09d3b06e 100644
--- a/docs/source/index.rst
+++ b/docs/source/index.rst
@@ -12,10 +12,10 @@ The library allows you to visualize graph data interactively in Python using a s
 The library wraps the `Neo4j Visualization JavaScript library (NVL) <https://neo4j.com/docs/nvl/current/>`_, and
 provides additional features for working with graph data in Python.
 Notably, there are convenience methods for importing data from `Pandas DataFrames <https://pandas.pydata.org/>`_,
-`Neo4j Graph Data Science <https://neo4j.com/docs/graph-data-science/current/>`_ and `Neo4j Database <https://neo4j.com/docs/python-manual/current/>`.
+`Neo4j Graph Data Science <https://neo4j.com/docs/graph-data-science/current/>`_ and `Neo4j Database <https://neo4j.com/docs/python-manual/current/>`_.
 
-The source code is available on https://github.com/neo4j/python-graph-visualization[GitHub].
-If you have a suggestion on how we can improve the library or want to report a problem, you can create a https://github.com/neo4j/python-graph-visualization/issues/new[new issue].
+The source code is available on `GitHub <https://github.com/neo4j/python-graph-visualization>`_.
+If you have a suggestion on how we can improve the library or want to report a problem, you can create a `new issue <https://github.com/neo4j/python-graph-visualization/issues/new>`_.
 
 
 .. toctree::
@@ -26,6 +26,6 @@ If you have a suggestion on how we can improve the library or want to report a p
    getting-started.nblink
    integration.rst
    rendering.rst
-   adjusting.rst
+   customizing.rst
    api-reference/index.rst
    tutorials/index.rst
diff --git a/docs/source/integration.rst b/docs/source/integration.rst
index 53ba45da..9e91a263 100644
--- a/docs/source/integration.rst
+++ b/docs/source/integration.rst
@@ -11,6 +11,7 @@ Pandas DataFrames
 -----------------
 
 The ``neo4j-viz`` library provides a convenience method for importing data from Pandas DataFrames.
+These DataFrames can be created from many sources, such as CSV files or :doc:`Snowflake tables<./tutorials/snowpark-example>`.
 It requires and additional dependency to be installed, which you can do by running:
 
 .. code-block:: bash
diff --git a/python-wrapper/src/neo4j_viz/node.py b/python-wrapper/src/neo4j_viz/node.py
index be1bf2e4..8718a497 100644
--- a/python-wrapper/src/neo4j_viz/node.py
+++ b/python-wrapper/src/neo4j_viz/node.py
@@ -37,7 +37,7 @@ class Node(BaseModel, extra="allow"):
     )
     #: The size of the node as radius in pixel
     size: Optional[RealNumber] = Field(None, ge=0, description="The size of the node as radius in pixel")
-    #: The color of the node
+    #: The color of the node. Allowed input is for example "#FF0000", "red" or (255, 0, 0)
     color: Optional[ColorType] = Field(None, description="The color of the node")
     #: Whether the node is pinned in the visualization
     pinned: Optional[bool] = Field(None, description="Whether the node is pinned in the visualization")
diff --git a/python-wrapper/src/neo4j_viz/relationship.py b/python-wrapper/src/neo4j_viz/relationship.py
index 040da1d9..b5f4c640 100644
--- a/python-wrapper/src/neo4j_viz/relationship.py
+++ b/python-wrapper/src/neo4j_viz/relationship.py
@@ -41,7 +41,7 @@ class Relationship(BaseModel, extra="allow"):
     caption_size: Optional[Union[int, float]] = Field(
         None, gt=0.0, serialization_alias="captionSize", description="The size of the caption text"
     )
-    #: The color of the relationship
+    #: The color of the relationship. Allowed input is for example "#FF0000", "red" or (255, 0, 0)
     color: Optional[ColorType] = Field(None, description="The color of the relationship")
 
     @field_serializer("color")
diff --git a/python-wrapper/src/neo4j_viz/visualization_graph.py b/python-wrapper/src/neo4j_viz/visualization_graph.py
index a017910c..a21bea32 100644
--- a/python-wrapper/src/neo4j_viz/visualization_graph.py
+++ b/python-wrapper/src/neo4j_viz/visualization_graph.py
@@ -205,6 +205,7 @@ def color_nodes(self, property: str, colors: Optional[ColorsType] = None, overri
         colors:
             The colors to use for the nodes. If a dictionary is given, it should map from property to color.
             If an iterable is given, the colors are used in order.
+            Allowed color values are for example “#FF0000”, “red” or (255, 0, 0) (full list: https://docs.pydantic.dev/2.0/usage/types/extra_types/color_types/).
             The default colors are the Neo4j graph colors.
         override:
             Whether to override existing colors of the nodes, if they have any.