diff --git a/public/css/style.css b/public/css/style.css
index 44929dd8..a952854e 100644
--- a/public/css/style.css
+++ b/public/css/style.css
@@ -2802,35 +2802,41 @@ button:disabled{
   }
 
   #newsletter {
-    padding: 10px;
-  }
+    display: flex;
+    flex-direction: column; /* Arrange items vertically */
+    height: auto; /* Allow height to adjust based on content */
+    padding: 20px; /* Optional padding for spacing */
+}
 
-  #newsletter .news-text {
-    width: 50%;
-  }
+#newsletter .news-text {
+    margin-bottom: 20px; /* Space between text and form */
+}
 
-  #newsletter .news-text h4 {
-    font-size: 18px;
-  }
+#newsletter .news-text h4 {
+    font-size: 22px;
+}
 
-  #newsletter .news-text p {
-    font-size: 16px;
-  }
+#newsletter .news-text p {
+    font-size: 18px;
+}
 
-  #newsletter .news-form {
-    width: 48%;
-  }
+#newsletter .news-form {
+    display: flex;
+    flex-direction: column; 
+    width: 100%; 
+}
 
-  #newsletter .news-form input {
-    padding: 0px 2px;
-    height: 20px;
-    font-size: 12px;
-  }
+#newsletter .news-form input {
+    height: 2rem;
+    font-size: 14px;
+    margin-bottom: 10px; 
+}
 
-  #newsletter .news-form button {
-    font-size: 8px;
-    padding: 0px 6px;
-  }
+#newsletter .news-form button {
+    width: 100%;
+    text-align: center;
+    font-size: 10px;
+    padding: 2px 6px;
 }
 
 @media (max-width: 400px) {
diff --git a/tempCodeRunnerFile.python b/tempCodeRunnerFile.python
new file mode 100644
index 00000000..6fbfc862
--- /dev/null
+++ b/tempCodeRunnerFile.python
@@ -0,0 +1,47 @@
+import math
+
+def classifyAPoint(points,p,k=3):
+    distance=[]
+    for group in points:
+        for feature in points[group]:
+
+            #calculate the euclidean distance of p from training points 
+            euclidean_distance = math.sqrt((feature[0]-p[0])**2 +(feature[1]-p[1])**2)
+
+            # Add a tuple of form (distance,group) in the distance list
+            distance.append((euclidean_distance,group))
+
+    # sort the distance list in ascending order
+    # and select first k distances
+    distance = sorted(distance)[:k]
+
+    freq1 = 0 
+    freq2 = 0 
+
+    for d in distance:
+        if d[1] == 0:
+            freq1 += 1
+        elif d[1] == 1:
+            freq2 += 1
+
+    return 0 if freq1>freq2 else 1
+
+# driver function
+def main():
+
+
+
+    points = {0:[(1,12),(2,5),(3,6),(3,10),(3.5,8),(2,11),(2,9),(1,7)],
+              1:[(5,3),(3,2),(1.5,9),(7,2),(6,1),(3.8,1),(5.6,4),(4,2),(2,5)]}
+
+    # testing point p(x,y)
+    p = (2.5,7)
+
+    # Number of neighbours 
+    k = 3
+
+    print("The value classified to unknown point is: {}".\
+          format(classifyAPoint(points,p,k)))
+
+if __name__ == '__main__':
+    main()