diff --git a/doc.zih.tu-dresden.de/docs/software/data_analytics_with_python.md b/doc.zih.tu-dresden.de/docs/software/data_analytics_with_python.md
index 965abe37c45c0b127c954eb35a29fd83a04ac814..daeb10254959a282d161c054b3121309812b162e 100644
--- a/doc.zih.tu-dresden.de/docs/software/data_analytics_with_python.md
+++ b/doc.zih.tu-dresden.de/docs/software/data_analytics_with_python.md
@@ -151,9 +151,9 @@ command displays short information and included extensions of the
 module.
 
 Dask is installed by default in
-[Anaconda](https://www.anaconda.com/download/). Moreover, 
-it is possible to install and use Dask in your local virtualenv 
-(recommended) or [conda](https://www.anaconda.com/download/) virtual environment. 
+[Anaconda](https://www.anaconda.com/download/). Moreover,
+it is possible to install and use Dask in your local virtualenv
+(recommended) or [conda](https://www.anaconda.com/download/) virtual environment.
 More information you can find  
 in the [Python Virtual Environments page](python_virtual_environments.md).
 
@@ -288,8 +288,8 @@ The Python code for setting up Slurm clusters
 and scaling clusters can be run by the `srun`
 (but remember that using `srun` directly on the shell
 blocks the shell and launches an
-interactive job) or batch jobs or 
-[JupyterHub](../access/jupyterhub.md) with loaded Dask 
+interactive job) or batch jobs or
+[JupyterHub](../access/jupyterhub.md) with loaded Dask
 (by module or by Python virtual environment).
 
 **Note**: The job to run original code (de facto an interface) with
@@ -392,9 +392,9 @@ for the Monte-Carlo estimation of Pi.
       print_pi_stats(size, pi, time_delta=elaps, num_workers=len(cluster.scheduler.workers))
     ```
 
-Please check the availability of resources that you want to allocate 
-by the script for the example above. 
-You can do it with `sinfo` command. The script doesn't work 
+Please check the availability of resources that you want to allocate
+by the script for the example above.
+You can do it with `sinfo` command. The script doesn't work
 without available cluster resources.
 
 ### Mpi4py -  MPI for Python