diff --git a/s1_a51.py b/s1_a51.py
index bea90cd..9b91ba6 100644
--- a/s1_a51.py
+++ b/s1_a51.py
@@ -1,5 +1,4 @@
 import collections
-
 import numpy as np
 from scipy import sparse
 
@@ -8,16 +7,16 @@ class Matrix:
     def __init__(self):
         self.__matrix = collections.defaultdict(dict)
 
-    def set(self, column, row, value):
-        if value == 0:
-            if self.__matrix.get(column) and self.__matrix.get(column).get(row):
-                del self.__matrix[column][row]
+    def set(self, row, column, value):
+        if value != 0:
+            self.__matrix[row][column] = value
         else:
-            self.__matrix[column][row] = value
+            if self.__matrix.get(row) and self.__matrix.get(row).get(column):
+                del self.__matrix[row][column]
 
-    def get(self, column, row):
-        if self.__matrix.get(column) and self.__matrix.get(column).get(row):
-            return self.__matrix[column][row]
+    def get(self, row, column):
+        if self.__matrix.get(row) and self.__matrix.get(row).get(column):
+            return self.__matrix[row][column]
         else:
             return 0
 
@@ -31,15 +30,25 @@ if __name__ == "__main__":
                     [0, 0, 9, 0],
                     [0, 7, 0, 0],
                     [0, 0, 0, 0]]
-    sparse_matrix = Matrix()
-    for column in range(len(input_matrix)):
-        for row in range(len(input_matrix[0])):
-            sparse_matrix.set(column, row, input_matrix[row][column])
 
-    sparse_matrix.print()
+    # sparse_matrix = Matrix()
+    #
+    # for row in range(len(input_matrix)):
+    #     for column in range(len(input_matrix[0])):
+    #         sparse_matrix.set(row, column, input_matrix[row][column])
+
+    sparce_matrix = {}
+    rows = len(input_matrix)
+    columns = len(input_matrix[0])
+
+    for row in range(rows):
+        for column in range(columns):
+            if input_matrix[row][column] != 0:
+                sparce_matrix[(row, column)] = input_matrix[row][column]
+
     # Aufgabe 1c
-    # print("\nThe sparce matrix computed without numpy\n" + str(sparse_matrix))
-
+    print("\n The sparce matrix without numpy\n" + str(sparce_matrix))
+    # sparse_matrix.print()
     # faster way with numpy
     input_matrix = np.array(input_matrix)
     rows, columns = input_matrix.shape
diff --git a/s1_a53_6.py b/s1_a53_6.py
index edc0f27..144b10e 100644
--- a/s1_a53_6.py
+++ b/s1_a53_6.py
@@ -16,6 +16,7 @@ if __name__ == "__main__":
         print("Length of the string-list without duplicates: " + str(len(string_list)))
         print(string_list)
 
+
     string = "Donaudampfschiffahrtsgesellschaftsstewardess"
     split_chars_and_remove_duplicates(string)
 
@@ -28,9 +29,11 @@ if __name__ == "__main__":
 
     print("The sorted list" + str(list_to_sort))
 
+
     # Aufgabe 6
     def get_the_animal_sound(name_of_animal: str):
         animal_dictionary = {"Lion": "Growl!", "Dog": "Barks!", "Cat": "Meow!"}
         return animal_dictionary.get(name_of_animal, "Animal sound not available")
 
+
     print(get_the_animal_sound("Dog"))