diff --git a/src/data_preparation.py b/src/data_preparation.py
index bbd306d87ae9ef9530d6691d56a6d9318c239de8..6da63d3ad1bfc5089f63fbfea129fa2694c9d3e7 100644
--- a/src/data_preparation.py
+++ b/src/data_preparation.py
@@ -9,7 +9,7 @@ import logging
 import os
 from src import join, helpers
 from src import statistics
-from typing import Union, List, Dict, Iterable
+from typing import Union, List, Iterable
 import datetime as dt
 
 
@@ -18,6 +18,15 @@ date = Union[dt.date, dt.datetime]
 
 
 class DataPrep(object):
+    """
+    This class prepares data to be used in neural networks. Especially the following steps can be performed
+    - interpolate: interpolate between data points by using xarray's interpolation method
+    - standardise: standardise data to mean=1 and std=1, or just centralise to mean=0
+    - make window history: to present the history (time steps before) for training/ testing; X
+    - make labels: create target vector for training/ testing; y
+    - remove Nans jointly from desired input and output, only keeps time steps where no NaNs are present in X AND y
+    - some other methods to ensure that the functions above are working properly
+    """
 
     def __init__(self, path: str, network: str, station: Union[str, List[str]], variables: List[str], **kwargs):
         self.path = os.path.abspath(path)