adjusting documentation

README.md

@@ -16,7 +16,7 @@ In addition to [ipywidgets](https://ipywidgets.readthedocs.io/en/latest/) for an
 
 Data structure is provided by [xarray](http://xarray.pydata.org/en/stable/) (see [Why xarray?](http://xarray.pydata.org/en/stable/why-xarray.html)), that introduces labels in the form of dimensions, coordinates and attributes on top of raw [NumPy](https://numpy.org/)-like arrays, which allows for a more intuitive, more concise, and less error-prone developer experience. It integrates tightly with [dask](https://dask.org/) for parallel computing and [hvplot](https://hvplot.holoviz.org/user_guide/Gridded_Data.html) for interactive data visualization.
 
-Finally, Xcompact3d Toolbox is fully integrated with the new *Sandbox Flow Configuration*.
+Finally, Xcompact3d-toolbox is fully integrated with the new *Sandbox Flow Configuration*.
 The idea is to easily provide everything that XCompact3d needs from a [Jupyter Notebook](https://jupyter.org/), like initial conditions, solid geometry, boundary conditions, and the parameters ([see examples](https://xcompact3d-toolbox.readthedocs.io/en/latest/tutorial.html#sandbox-examples)).
 It makes life easier for beginners, that can run any new flow configuration without worrying about Fortran and [2decomp](http://www.2decomp.org/).
 For developers, it works as a rapid prototyping tool, to test concepts and then compare results to validate any future Fortran implementation.
@@ -142,8 +142,7 @@ Now, any change you make at the source code will be available at your local inst
 * [Documentation](https://xcompact3d-toolbox.readthedocs.io/);
 * [Suggestions for new features and bug report](https://github.com/fschuch/xcompact3d_toolbox/issues);
 * [See what is coming next (Project page)](https://github.com/fschuch/xcompact3d_toolbox/projects/1);
-* [Xcompact3d's repository](https://github.com/xcompact3d/Incompact3d);
-* [My fork from Xcompact3d's repository](https://github.com/fschuch/Xcompact3d/);
+* [Xcompact3d's repository](https://github.com/xcompact3d/Incompact3d).
 
 ## Try it Online
 

docs/index.rst

@@ -19,9 +19,10 @@ In addition to ipywidgets_ for an user friendly interface.
 Data structure is provided by xarray_ (see `Why xarray?`_), that introduces labels
 in the form of dimensions, coordinates and attributes on top of raw NumPy_-like
 arrays, which allows for a more intuitive, more concise, and less error-prone
-developer experience. It integrates tightly with dask_ for parallel computing.
+developer experience. It integrates tightly with dask_ for parallel computing and
+hvplot_ for interactive data visualization.
 
-Finally, Xcompact3d Toolbox is fully integrated with the new *Sandbox Flow Configuration*.
+Finally, Xcompact3d-toolbox is fully integrated with the new *Sandbox Flow Configuration*.
 The idea is to easily provide everything that Xcompact3d needs
 from a `Jupyter Notebook`_, like initial conditions, solid geometry, boundary
 conditions, and the parameters. It makes life easier for beginners, that can run
@@ -104,7 +105,7 @@ Examples
 Installation
 ------------
 
-It is possible to instal using pip::
+It is possible to install using pip::
 
    pip install xcompact3d-toolbox
 
@@ -134,6 +135,7 @@ Useful links
 
 .. _2decomp: http://www.2decomp.org/
 .. _dask: https://dask.org/
+.. _hvplot: https://hvplot.holoviz.org/user_guide/Gridded_Data.html
 .. _ipywidgets: https://ipywidgets.readthedocs.io/en/latest/
 .. _`Jupyter Notebook`: https://jupyter.org/
 .. _Numpy: https://numpy.org/