diff --git a/scripts/README.md b/scripts/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..5c32ea2a2ab6a445208fe0d91e0adef91d055b49
--- /dev/null
+++ b/scripts/README.md
@@ -0,0 +1,23 @@
+This is the description how to connect to the LabKey through API:
+1. Create a file named ".netrc" in your home directory. This file must include the following three lines:
+machine <remote-instance-of-labkey-server>
+login <user-email>
+password <user-password>
+
+E.g.:
+
+machine labkey.scicore.unibas.ch
+login eva.pujadas@unibas.ch
+password xxxxx
+
+To secure the file, set permissions in a way that only you can see the content of the file
+$ chmod 400 .netrc
+
+2. For running the script labkey_api.py libraries "labkey" and "pandas" are required. Either you install them and run the script with the standard python or you use the module "labkey-api-python/1.1.0-foss-2018b-Python-3.6.6" provided by SciCore. Execute the following command:
+python labkey_api.py arg1 arg2
+Here, arg1 stands for the project name, arg2 stands for the name of the LabKey table.
+
+E.g.:
+python labkey_api.py TEST_ABOERSCH RNA_Seq_data_template
+
+The script outputs the complete LabKey table in the form of pandas data frame.
diff --git a/scripts/labkey_api.py b/scripts/labkey_api.py
index b9f24e80d5f94e42758f6e23ad192acc5a83dc81..759acb4a90bd3ed933eca74dcd32fede71a6ef83 100644
--- a/scripts/labkey_api.py
+++ b/scripts/labkey_api.py
@@ -14,14 +14,14 @@ import sys
 from labkey.query import QueryFilter
 
 if __name__ == "__main__":
-  #project_name = "TEST_ABOERSCH"
-  #query_name = "RNA_Seq_data_template"
+  # These are values of variables for which the script works
+  # project_name = "TEST_ABOERSCH"
+  # query_name = "RNA_Seq_data_template"
   project_name = sys.argv[1]
   query_name = sys.argv[2]
   server_context = labkey.utils.create_server_context('labkey.scicore.unibas.ch', '/Zavolan Group/'+project_name, 'labkey', use_ssl=True)
   schema_name = "lists"
   results = labkey.query.select_rows(server_context,schema_name,query_name)
-  print(results)
   table_of_data = pd.DataFrame(results["rows"])
   print(table_of_data)