Update app.py

app.py

@@ -46,25 +46,31 @@ the key points of descriptive statistics are stated below.\n KEY COCEPTS\n * Mea
 st.subheader("Measure Of Central Tendency",divider=True)
 st.markdown("""The measure of central tendency is used to find the central average value of the data.The central tendency can be computed by 
 useing three ways \n * Mode \n * Median \n * Mean""")
-def mode(list1):
-    dict1={}
-    dict2={}
-    set1=set(list1)
-    for i in list1:
-        for j in set1:
-            dict1[j]=list1.count(j)
-    max_value=max(dict1.values())
-    count = [key for key, value in dict1.items() if value==max_value]
-    if max_value==1:
-        print('no mode')
-    elif len(count)==len(set1):
-        print('no mode')
-    elif len(count)==1:
-        dict2[count[0]]= dict1.get(count[0])
-        print(dict2)
-    elif len(count)==2:
-        print('bi mode')
-    elif len(count)==3:
-        print('tri mode')
+def mode(*args):
+    list1 = list(args)
+    dict1 = {}
+    dict2 = {}
+    set1 = set(list1)
+    for j in set1:
+        dict1[j] = list1.count(j)
+    max_value = max(dict1.values())
+    count = [key for key, value in dict1.items() if value == max_value]
+    if max_value == 1:
+        return 'no mode'
+    elif len(count) == len(set1):
+        return 'no mode'
+    elif len(count) == 1:
+        dict2[count[0]] = dict1.get(count[0])
+        return dict2
+    elif len(count) == 2:
+        return 'bi mode'
+    elif len(count) == 3:
+        return 'tri mode'
     else:
-        print('multimode')
+        return 'multimode'
+
+# Call the mode function with specific arguments
+result = mode(1, 2, 3, 3, 3)
+
+# Display the result
+st.write("Mode result:", result)