diff --git a/src/back/clustering_csv.py b/src/back/clustering_csv.py
index fb93b4e..4b3b6fb 100644
--- a/src/back/clustering_csv.py
+++ b/src/back/clustering_csv.py
@@ -24,7 +24,7 @@ def visualize_clusters_3d(X, labels, centers=None, title="Clusters"):
     ax.set_xlabel("Feature 1")
     ax.set_ylabel("Feature 2")
     ax.set_zlabel("Feature 3")
-    plt.show()
+    return plt.gcf()
 
 def calculate_cluster_statistics_kmeans(X, labels, centers):
     unique_labels = np.unique(labels)
diff --git a/src/back/managing_missing_values.py b/src/back/managing_missing_values.py
index b12c463..2ecdb28 100644
--- a/src/back/managing_missing_values.py
+++ b/src/back/managing_missing_values.py
@@ -18,7 +18,6 @@ def drop_high_null_percentage(data, threshold=0.5):
     data = data.loc[:, missing_percentage <= threshold]
     return data
 
-
 def replace_with_mean(data):
     return data.apply(lambda col: col.fillna(col.mean()) if col.dtype.kind in 'biufc' else col)
 
@@ -52,7 +51,6 @@ def impute_with_regression(data):
         
     return data
 
-
 """    
     Parameters:
     - data: Pandas DataFrame with the data