enhanced documentation

modules/multimatch_result_table.py

@@ -1,14 +1,24 @@
 import streamlit as st
 import pandas as pd
 
+"""
+Result table of the Multi Project Matching
+"""
+
 def show_multi_table(p1_df, p2_df):
+        """
+        p1_df & p2_df from functions/multi_project_matching
+        """
+
         st.write("------------------")
 
         p1_df = p1_df.reset_index(drop=True)
         p2_df = p2_df.reset_index(drop=True)
 
         actual_ind = 0
-        for i in range(len(p1_df) - 1, -1, -2): # stepsize because project matchs in both ways and it should only display a match one time
+
+        # Loop to displaye every matching pair from p1 and p2 dfs
+        for i in range(len(p1_df) - 1, -1, -2): # stepsize 2 to not display duplicates
             actual_ind += 1
             match_df = pd.DataFrame()
             row_from_p1 = p1_df.iloc[[i]]
@@ -16,6 +26,12 @@ def show_multi_table(p1_df, p2_df):
 
             # INTEGRATE IN PREPROCESSING !!!
             # transform strings to list
+            """
+            Add this to preprocessing
+            - flag url
+            - crs code lists
+            """
+
             try:
                 row_from_p1["crs_3_code_list"] = [row_from_p1['crs_3_name'].item().split(";")[:-1]]
                 row_from_p2["crs_3_code_list"] = [row_from_p2['crs_3_name'].item().split(";")[:-1]]
@@ -40,14 +56,13 @@ def show_multi_table(p1_df, p2_df):
                 row_from_p1["flag"] = "https://flagicons.lipis.dev/flags/4x3/xx.svg"
                 row_from_p2["flag"] = "https://flagicons.lipis.dev/flags/4x3/xx.svg"
             
-            #print(row_from_p1["flag"].item())
 
-            # append rows to match_df
-            #st.subheader(f"#{actual_ind}")
-            #st.caption(f"Similarity: {round(row_from_p1['similarity'].item(), 4) * 100}%")
+            # concat p1_df and p2_df rows 
             match_df = pd.concat([row_from_p1, row_from_p2], ignore_index=True)
             
             col1, col2 = st.columns([1, 12])
+
+            # MATCHING INFOS
             with col1:
                 
                 # remove arrow from standart st.metric()
@@ -64,6 +79,7 @@ def show_multi_table(p1_df, p2_df):
 
                 st.metric(label="Match", value=f"{actual_ind}", delta=f"~ {str(round(row_from_p1['similarity'].item(), 5) * 100)[:4]} %")
 
+            # MATCHING Project Informations as table
             with col2:
                 st.write("    ")
                 st.dataframe(