Update app.py

app.py

@@ -140,38 +140,18 @@ from langchain_core.output_parsers import StrOutputParser
 # Set page config
 st.set_page_config(page_title="🏏 Ultimate Cricket Analytics", layout="wide")
 
-# Ensure data folder exists
-DATA_DIR = "data"
-os.makedirs(DATA_DIR, exist_ok=True)
-
-# Helper function to load Excel file with error handling
-@st.cache_data
-def load_excel_file(filename):
-    filepath = os.path.join(DATA_DIR, filename)
-    try:
-        df = pd.read_excel(filepath, engine='xlrd')  # Use xlrd for .xls files
-        return df
-    except FileNotFoundError:
-        st.error(f"File `{filename}` not found in `{DATA_DIR}/`. Please upload it.")
-        return pd.DataFrame()
-    except ValueError:
-        st.error(f"File `{filename}` is not a valid Excel file. Please check the format.")
-        return pd.DataFrame()
-    except Exception as e:
-        st.error(f"Error loading `{filename}`: {e}")
-        return pd.DataFrame()
+# Create a folder to save CSVs if not exists
+data_folder = "data"
+os.makedirs(data_folder, exist_ok=True)
 
-# Load all three formats
-odi_df = load_excel_file("odi.xls")
-t20_df = load_excel_file("t20.xls")
-test_df = load_excel_file("test.xls")
+#]
 
-# Check if all loaded correctly
-if not odi_df.empty and not t20_df.empty and not test_df.empty:
-    st.success("All Excel files loaded successfully!")
-else:
-    st.warning("Please ensure all Excel files (odi.xls, t20.xls, test.xls) are present in `data/` folder.")
+# Load all three formats
+odi_df = pd.read_csv("odi.xls")
+t20_df = pd.read_csv("t20.xls")
+test_df = pd.read_csv("test.xls")
 
+]
 
 # Load CSV files
 batting_df = pd.read_csv("Batting_10_Teams_Final.csv")
@@ -236,67 +216,76 @@ with tab1:
             st.plotly_chart(px.line(player_bowling, x='Format', y='Eco'))
         st.plotly_chart(px.pie(player_bowling, values='Wickets', names='Format'))
 
+# ---------------- TAB 2: Team Comparison ----------------
 # ---------------- TAB 2: Team Comparison ----------------
 # ---------------- TAB 2: Team Comparison ----------------
 with tab2:
     st.title("📊 Team Comparison")
 
-    # Add Format column to all datasets
     try:
+        # Tag the format for clarity
         odi_df['Format'] = 'ODI'
         t20_df['Format'] = 'T20'
         test_df['Format'] = 'Test'
 
+        # Combine all formats
         combined_df = pd.concat([odi_df, t20_df, test_df], ignore_index=True)
 
-        # Check team column name
-        team_column = 'Country' if 'Country' in combined_df.columns else 'Team' if 'Team' in combined_df.columns else None
-
-        if team_column:
-            # Select teams and stat
-            selected_teams = st.multiselect("Select Teams to Compare (up to 3)", combined_df[team_column].unique(), max_selections=3)
-
-            if selected_teams:
-                selected_data = combined_df[combined_df[team_column].isin(selected_teams)]
-
-                stat = st.selectbox("Select Stat to Compare", ['Matches', 'Win%', 'Runs', 'Wickets', 'SR', 'Eco'])
-
-                # Bar chart
-                st.subheader(f"{stat} Comparison")
-                fig = px.bar(
-                    selected_data,
-                    x=team_column,
-                    y=stat,
-                    color='Format',
-                    barmode='group',
-                    title=f"{stat} by Team and Format"
-                )
-                st.plotly_chart(fig, use_container_width=True)
-
-                # Optional: Show raw comparison data
-                if st.checkbox("Show Data Table"):
-                    st.dataframe(selected_data.reset_index(drop=True))
-
-                # GenAI Team Bio
-                st.subheader("📘 GenAI Team Summary")
-
-                for team in selected_teams:
-                    st.markdown(f"#### {team}")
-                    team_prompt = ChatPromptTemplate.from_messages([
-                        ("system", "You are an AI cricket historian. Provide a brief yet detailed overview of the team."),
-                        ("human", "{team_name}")
-                    ])
-                    team_chain = team_prompt | model | out_par
-                    team_bio = team_chain.invoke({"team_name": team})
-                    st.write(team_bio)
-            else:
-                st.info("Please select at least one team to compare.")
+        # Columns as per your data
+        team_column = 'Team'
+
+        # Team selection
+        selected_teams = st.multiselect("Select Teams to Compare (up to 3)", combined_df[team_column].unique(), max_selections=3)
+
+        if selected_teams:
+            selected_data = combined_df[combined_df[team_column].isin(selected_teams)]
+
+            # Map column names to user-friendly labels
+            stat_options = {
+                'Mat': 'Matches',
+                'Won': 'Wins',
+                'Lost': 'Losses',
+                'Draw': 'Draws',
+                'Tied': 'Ties',
+                'W/L': 'Win/Loss Ratio',
+                '%W': 'Win %',
+                '%L': 'Loss %',
+                '%D': 'Draw %'
+            }
+
+            stat_choice = st.selectbox("Select Stat to Compare", list(stat_options.keys()), format_func=lambda x: stat_options[x])
+
+            st.subheader(f"{stat_options[stat_choice]} Comparison")
+
+            fig = px.bar(
+                selected_data,
+                x='Team',
+                y=stat_choice,
+                color='Format',
+                barmode='group',
+                title=f"{stat_options[stat_choice]} by Team and Format"
+            )
+            st.plotly_chart(fig, use_container_width=True)
+
+            if st.checkbox("Show Raw Team Data Table"):
+                st.dataframe(selected_data.reset_index(drop=True))
+
+            # GenAI Team Summary
+            st.subheader("📘 GenAI Team Summary")
+            for team in selected_teams:
+                st.markdown(f"#### {team}")
+                team_prompt = ChatPromptTemplate.from_messages([
+                    ("system", "You are an AI cricket historian. Provide a brief yet detailed overview of the team."),
+                    ("human", "{team_name}")
+                ])
+                team_chain = team_prompt | model | out_par
+                bio = team_chain.invoke({"team_name": team})
+                st.write(bio)
         else:
-            st.error("Could not find 'Team' or 'Country' column in the Excel data.")
+            st.info("Please select at least one team to compare.")
 
     except Exception as e:
-        st.error(f"Error processing data: {e}")
-
+        st.error(f"Error loading team data: {e}")
 
 # ---------------- TAB 3: Team GenAI Bio ----------------
 with tab3: