diff --git a/pywatts/predict_for_json.py b/pywatts/photovoltaic_gruppe1.py
similarity index 69%
rename from pywatts/predict_for_json.py
rename to pywatts/photovoltaic_gruppe1.py
index 98f666f..3889f6c 100644
--- a/pywatts/predict_for_json.py
+++ b/pywatts/photovoltaic_gruppe1.py
@@ -9,21 +9,20 @@ from pywatts.routines import *
 # get rid of TF debug message
 os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
 
-if len(sys.argv) != 3:
-    print("Usage: python predict_for_json.py 24h|1h <file.json>")
+if len(sys.argv) != 2:
+    print("Usage: python photovoltaic_gruppe1.py <file.json>")
     exit(1)
 
-type = sys.argv[1]  # '1h' or '24h'
-json_file = sys.argv[2]  # json file
+json_file = sys.argv[1]  # json file
 
-queries = input_queries(json_file)
+oneH, queries = input_queries(json_file)
 
 feature_col = [tf.feature_column.numeric_column(str(idx)) for idx in range(336)]
 n = pywatts.neural.Net(feature_cols=feature_col)
 
 predictions = []
 for query in queries:
-    if type == '1h':
+    if oneH:
         predictions.extend(predict(n, query).astype('Float64').tolist())
     else:
         predictions.append(predict24h(n, query))
diff --git a/pywatts/routines.py b/pywatts/routines.py
index bf3919f..54e3beb 100644
--- a/pywatts/routines.py
+++ b/pywatts/routines.py
@@ -39,6 +39,12 @@ def input_query(json_str, idx=0):
 def input_queries(json_str):
     tmp_df = pandas.read_json(json_str)
 
+    oneH = False
+    try:
+        s = tmp_df['max_temp'][0]
+    except KeyError:
+        oneH = True
+
     queries = []
     for i in range(len(tmp_df)):
         queries.append(pandas.DataFrame.from_dict(
@@ -46,7 +52,7 @@ def input_queries(json_str):
              'temp': tmp_df['temp'][i],
              'wind': tmp_df['wind'][i]}
         ))
-    return queries
+    return oneH, queries
 
 
 def input_result(json_str, idx=0):