Emphasized the small difference of windows and unix setup.

Used italics to express variables / input arguments. Added information about optional dependencies in the contributions part.

README.md

@@ -8,7 +8,8 @@ plotID is a program connected to Research Data Management (RDM). It has two main
 **Note:** To run plotID python version ≥ 3.10 is required.
 
 ## Installation
-Currently there are two options to run plotID. Either install it via pip from the Python Package Index (PyPi) or install plotID from the source code. Apart from setting up an optional virtual environment, installation is the same for Windows and Unix systems.
+Currently there are two options to run plotID. Either install it via pip from the Python Package Index (PyPi) or install plotID from the source code.   
+**Installation is the same for Windows and Unix systems, except** for the **optional** first set of setting up a virtual environment.
 
 1. [Optional] Create a virtual environment and activate it:  
 ```bash
@@ -47,19 +48,19 @@ Tag your figure/plot with an ID. It is possible to tag multiple figures at once.
 `tagplot(figures, plot_engine)`  
 The variable "figures" can be a single figure or a list of multiple figures.  
 The argument "plot_engine" defines which plot engine was used to create the figures. It also determines which plot engine plotID uses to place the ID on the plot. Currently supported plot engines are:
-- 'matplotlib', which processes figures created by matplotlib.
-- 'image', which processes pictures with common extensions (jpg, png, etc.).
+- *matplotlib*, which processes figures created by matplotlib.
+- *image*, which processes pictures files with common extensions (jpg, png, etc.).
 
 tagplot returns a PlotIDTransfer object that contains the tagged figures and the corresponding IDs as strings.
 
 Optional parameters can be used to customize the tag process.
-- prefix : str, optional
+- *prefix* : str, optional
         Will be added as prefix to the ID.
-- id_method : str, optional
+- *id_method* : str, optional
         id_method for creating the ID. Create an ID by Unix time is referenced as 'time', create a random ID with id_method='random'. The default is 'time'.
-- location : string, optional
+- *location* : string, optional
         Location for ID to be displayed on the plot. Default is 'east'.
-- qrcode : boolean, optional
+- *qrcode* : boolean, optional
         Experimental support for encoding the ID in a QR Code.
 
 Example:  
@@ -75,16 +76,16 @@ FIGS_AND_IDS = tagplot(FIGS_AS_LIST, 'matplotlib', prefix='XY23_', id_method='ra
 Save plot, data and measuring script. It is possible to export multiple figures at once.
 `publish(figs_and_ids, src_datapath, dst_path, plot_name)`  
   
-- "figs_and_ids" must be a PlotIDTransfer object. Therefore, it can be directly passed from tagplot() to publish().  
-- "src_datapath" specifies the path to (raw) data that should be published. It can be a string or a list of strings that specifies all files and directories which will be published.  
-- "dst_path" is the path to the destination directory, where all the data should be copied/exported to.  
-- "plot_names" will be the file names for the exported plots. If you give only one plot name but several figures, plotID will name the exported plots with an appended number, e.g. example_fig1.png, example_fig2.png, ...  
+- *figs_and_ids* must be a PlotIDTransfer object. Therefore, it can be directly passed from tagplot() to publish().  
+- *src_datapath* specifies the path to (raw) data that should be published. It can be a string or a list of strings that specifies all files and directories which will be published.  
+- *dst_path* is the path to the destination directory, where all the data should be copied/exported to.  
+- *plot_names* will be the file names for the exported plots. If you give only one plot name but several figures, plotID will name the exported plots with an appended number, e.g. example_fig1.png, example_fig2.png, ...  
 
 Optional parameters can be used to customize the publish process.
-- data_storage: str, optional  
+- *data_storage*: str, optional  
         Method how the data should be stored. Available options:  
-  - centralized: The raw data will copied only once. All other plots will reference this data via sym link.
-  - individual: The complete raw data will be copied to a folder for every plot, respectively.
+  - *centralized*: The raw data will copied only once. All other plots will reference this data via sym link.
+  - *individual*: The complete raw data will be copied to a folder for every plot, respectively.
 Example:
 `publish(figs_and_ids, '/home/user/Documents/research_data', '/home/user/Documents/exported_data', 'EnergyOverTime-Plot')`  
 
@@ -93,8 +94,8 @@ If you want to build plotID yourself, follow these steps:
 1. Download the source code from [Gitlab](https://git.rwth-aachen.de/plotid/plotid_python):  
 `git clone https://git.rwth-aachen.de/plotid/plotid_python.git`  
 `cd plotid_python`  
-2. [Optional] Create a virtual environment (see Installation).  
-3. [Optional] Run unittests and coverage:  
+2. *[Optional]* Create a virtual environment (see [Installation](#Installation)).  
+3. *[Optional]* Run unittests and coverage:  
 `python3 tests/runner_tests.py`
 4. Build the package
 `python3 -m build`
@@ -102,6 +103,8 @@ If you want to build plotID yourself, follow these steps:
 ## Contributing
 Contributions to plotID are very welcome. If you encounter any issues with plotID please report them in our [issue tracker](https://git.rwth-aachen.de/plotid/plotid_python/-/issues). Code contributions via merge request are also highly appreciated. Please have a look at [CONTRIBUTING](https://git.rwth-aachen.de/plotid/plotid_python/-/blob/main/CONTRIBUTING.md) first.
 
+To install all optional dependencies use `pip install .[test,docs]` or `pip install plotid[test,docs]` respectively.  
+
 
 ## Documentation
 If you have more questions about plotID, please have a look at the [documentation](https://plotid.pages.rwth-aachen.de/plotid_python).