diff --git a/src/EasyGA.py b/src/EasyGA.py
index 5b73dd2..b7530d5 100644
--- a/src/EasyGA.py
+++ b/src/EasyGA.py
@@ -24,6 +24,7 @@ from database import database
 from sqlite3 import Error
 
 # Graphing package
+from database import graph
 import matplotlib.pyplot as plt
 
 
@@ -157,34 +158,3 @@ class GA(Attributes):
         """Prints the best chromosome and its fitness"""
         print(f"Best Chromosome \t: {self.population.get_chromosome(0)}")
         print(f"Best Fitness    \t: {self.population.get_chromosome(0).get_fitness()}")
-
-    def graph_scatter(self):
-        """Show a scatter plot of the database information."""
-
-        # Query the X data
-        generations = self.database.query_one_item("SELECT COUNT(DISTINCT generation) FROM data;")
-
-        # Create the generations array
-        X = list(range(0, generations))
-
-        #Query the Y data
-        Y_data = self.database.query_all("SELECT SUM(fitness) FROM data GROUP BY generation;")
-
-        # Format the Y data so we can use it to plot
-        Y = [i[0] for i in Y_data]
-
-        # Set the plot size
-        plt.figure(figsize=[5, 5])
-
-        plt.scatter(X,Y)
-        # x and y labels
-        plt.xlabel('Generation')
-        plt.ylabel('Generation Total Fitness')
-        plt.title('Relationship Between Generations and Generation Total Fitness')
-
-        # Show the plot
-        plt.show()
-
-
-    def graph_line(self):
-        pass
diff --git a/src/attributes.py b/src/attributes.py
index ec5441a..94a8249 100644
--- a/src/attributes.py
+++ b/src/attributes.py
@@ -24,6 +24,10 @@ from crossover import Crossover_Methods
 from database import database
 from sqlite3 import Error
 
+# Graphing package
+from database import graph
+import matplotlib.pyplot as plt
+
 
 class Attributes:
     """Default GA attributes can be found here. If any attributes have not
@@ -66,7 +70,8 @@ class Attributes:
                                                 generation integer NOT NULL,
                                                 fitness DOUBLE,
                                                 chromosome text
-                                            ); """
+                                            ); """,
+            graph                       = graph.graph
         ):
 
         # Initilization variables
@@ -116,6 +121,8 @@ class Attributes:
         self.database_name = deepcopy(database_name)
         self.sql_create_data_structure = deepcopy(sql_create_data_structure)
 
+        # Graphing variables
+        self.graph = deepcopy(graph)
 
     # Getter and setters for all required varibles
     @property
diff --git a/src/database/graph.py b/src/database/graph.py
new file mode 100644
index 0000000..8ffe03f
--- /dev/null
+++ b/src/database/graph.py
@@ -0,0 +1,39 @@
+# Graphing package
+import matplotlib.pyplot as plt
+# Database class
+from database import database
+from sqlite3 import Error
+
+class graph:
+    """ """
+
+    def scatter(ga):
+        """Show a scatter plot of the database information."""
+
+        # Query the X data
+        generations = ga.database.query_one_item("SELECT COUNT(DISTINCT generation) FROM data;")
+
+        # Create the generations array
+        X = list(range(0, generations))
+
+        #Query the Y data
+        Y_data = ga.database.query_all("SELECT SUM(fitness) FROM data GROUP BY generation;")
+
+        # Format the Y data so we can use it to plot
+        Y = [i[0] for i in Y_data]
+
+        # Set the plot size
+        plt.figure(figsize=[5, 5])
+
+        plt.scatter(X,Y)
+        # x and y labels
+        plt.xlabel('Generation')
+        plt.ylabel('Generation Total Fitness')
+        plt.title('Relationship Between Generations and Generation Total Fitness')
+
+        # Show the plot
+        plt.show()
+
+
+    def line(ga):
+        pass
diff --git a/src/run_testing.py b/src/run_testing.py
index fae667b..d5f901c 100644
--- a/src/run_testing.py
+++ b/src/run_testing.py
@@ -7,7 +7,7 @@ ga = EasyGA.GA()
 # Create 25 chromosomes each with 10 genes and 200 generations
 ga.population_size = 25
 ga.chromosome_length = 10
-ga.generation_goal = 200
+ga.generation_goal = 150
 
 # Create random genes from 0 to 10
 ga.gene_impl = lambda: random.randint(0, 10)
@@ -18,4 +18,4 @@ ga.target_fitness_type = 'min'
 
 ga.evolve()
 
-ga.graph_scatter()
+ga.graph.scatter(ga)