Update app.py

app.py

@@ -65,6 +65,7 @@ checking the frequency in list we come across a situtaion where we will find thr
 st.markdown(''':violet[Multi_Mode] \n  Let's understand why this situation raises for example let's take list of numbers [1,1,2,2,3,3,4,4,5]. here by
 checking the frequency in list we come across a situtaion where we will find more than three maximun frequecy repeated value hence the output will be Multi_Mode.
 ''')
+st.title("Mode")
 def mode(*args):
     list1 = list(args)
     dict1 = {}
@@ -113,22 +114,17 @@ st.latex(r'''
 \text{Median} = \frac{X_{\left(\frac{n}{2}\right)} + X_{\left(\frac{n}{2}+1\right)}}{2}
 ''')
 def median(list1):
-    list1.sort()  # Ensure the list is sorted
+    list1.sort()
     length = len(list1)
-    
     if length % 2 == 0:
-        # For even length, calculate the average of the two middle values
         mid1 = length // 2 - 1
         mid2 = length // 2
         return (list1[mid1] + list1[mid2]) / 2
     else:
-        # For odd length, return the middle value
         mid = length // 2
         return list1[mid]
-
 st.title("Calculate Median")
 numbers_input_1 = st.text_input("Enter a list of numbers separated by commas (e.g., 1, 2, 3, 4, 5):", key="numbers_input_1")
-
 if numbers_input_1:
     parts = numbers_input_1.split(',')
     list1 = []
@@ -142,5 +138,23 @@ if numbers_input_1:
         result = median(list1)
         st.write("Median result:", result)
     else:
-        st.write("No valid numbers provided.") 
+        st.write("No valid numbers provided.")
+st.subheader("Mean",divider=True)
+st.markdown("""
+Mean is one of the beautiful measurement of central tendency it invovles all the data present in it.The only drawback of mean is it is 
+effected by outliers.Based on the data we will compute the mean in three types""")
+st.subheader("Arthamatic Mean",divider=True)
+st.markdown("""Arthamatic Mean is used on data which have \n * Interval and Ratio Data \n * Symmetric Distributions \n * Data Without Outliers
+""")
+st.subheader("Population Mean Formula")
+st.latex(r'''
+    \mu = \frac{1}{N} \sum_{i=1}^{N} x_i
+''')
+st.subheader("Sample Mean Formula")
+st.latex(r'''
+    \bar{x} = \frac{1}{n} \sum_{i=1}^{n} x_i
+''')
+st.subheader("Geometric Mean",divider=True)
+st.subheader("Harmonic Mean",divider=True)
+