Update pages/Introduction.py

pages/Introduction.py

@@ -69,7 +69,13 @@ st.write("**Document Frequency:** This tests the meaning of the text, which is v
 
 
 st.write("Inverse Document Frequency: Mainly, it tests how relevant the word is. The key aim of the search is to locate the appropriate records that fit the demand. Since tf considers all terms equally significant, it is therefore not only possible to use the term frequencies to measure the weight of the term in the paper. First, find the document frequency of a term t by counting the number of documents containing the term:\n df(t) = occurrence of t in documents")
-st.write("df(t) = N(t)\nwhere:\n df(t) = Document frequency of a term t\n N(t) = Number of documents containing the term t")
+
+st.write("""
+df(t) = N(t)  
+where:  
+- df(t) = Document frequency of a term t  
+- N(t) = Number of documents containing the term t
+""")