Update pages/Automatic_Machine_learning_app.py

pages/Automatic_Machine_learning_app.py

@@ -1,4 +1,3 @@
-
 import streamlit as st
 import pandas as pd
 import plotly.express as px
@@ -45,56 +44,57 @@ st.markdown("""
         font-weight: bold;
         margin: 0;
     }
-    .stTabs [data-baseweb="tab-list"] {
-        gap: 10px;
-    }
-    .stTabs [data-baseweb="tab"] {
-        background-color: #F0F3F4;
-        border-radius: 5px;
-        padding: 10px 20px;
-        color: #1A5276;
-    }
-    .stTabs [data-baseweb="tab"][aria-selected="true"] {
-        background-color: #2E86C1;
-        color: white;
-    }
     </style>
 """, unsafe_allow_html=True)
 
-# Data Directory Setup
-data_folder = "cricket_data"
-os.makedirs(data_folder, exist_ok=True)
-
-# File Paths
-batting_path = "Teams_batting.csv"
-bowling_path = "team_bowling.csv"
-
 # Load Data
+batting_path = "Batting_10_Teams_Final.csv"
+bowling_path = "Bowling_10_Teams_Final.csv"
+
 try:
     batting_df = pd.read_csv(batting_path)
     bowling_df = pd.read_csv(bowling_path)
 except FileNotFoundError:
-    st.error("CSV files not found. Please ensure 'Batting_10_Teams_Final.csv' and 'Bowling_10_Teams_Final.csv' are in the correct directory.")
+    st.error("CSV files not found. Please ensure the correct files are in the directory.")
+    st.stop()
+
+# Debugging: Display available columns
+st.write("Batting Data Columns:", batting_df.columns.tolist())
+st.write("Bowling Data Columns:", bowling_df.columns.tolist())
+
+# Normalize column names to lowercase
+batting_df.columns = batting_df.columns.str.lower()
+bowling_df.columns = bowling_df.columns.str.lower()
+
+# Check if 'country' or 'team' column exists
+if "country" in batting_df.columns:
+    team_column = "country"
+elif "team" in batting_df.columns:
+    team_column = "team"
+else:
+    st.error("Neither 'Country' nor 'Team' column found in the dataset.")
     st.stop()
 
 # Sidebar Configuration
 with st.sidebar:
     st.image("https://cdn-icons-png.flaticon.com/512/1099/1099640.png", width=100)
     st.markdown("### Team Selection")
-    teams = sorted(set(batting_df['Country'].unique()).union(bowling_df['Country'].unique()))
+
+    # Extract unique teams
+    teams = sorted(set(batting_df[team_column].unique()).union(bowling_df[team_column].unique()))
     selected_team = st.selectbox("Choose a Team", teams, format_func=lambda x: x.upper())
-    
+
     # Player Selection
-    batting_players = batting_df[batting_df['Country'] == selected_team]['player_name'].unique()
-    bowling_players = bowling_df[bowling_df['Country'] == selected_team]['player_name'].unique()
+    batting_players = batting_df[batting_df[team_column] == selected_team]['player_name'].unique()
+    bowling_players = bowling_df[bowling_df[team_column] == selected_team]['player_name'].unique()
     players = sorted(set(batting_players).union(bowling_players))
     selected_player = st.selectbox("Choose a Player", players)
 
 # Filter Player Data
 player_batting = batting_df[(batting_df['player_name'] == selected_player) & 
-                          (batting_df['Country'] == selected_team)]
+                          (batting_df[team_column] == selected_team)]
 player_bowling = bowling_df[(bowling_df['player_name'] == selected_player) & 
-                          (bowling_df['Country'] == selected_team)]
+                          (bowling_df[team_column] == selected_team)]
 
 # Main Dashboard
 st.markdown(f'<div class="main-title">{selected_player}\'s Cricket Analytics</div>', unsafe_allow_html=True)
@@ -104,10 +104,10 @@ st.markdown('<div class="section-header">Key Performance Metrics</div>', unsafe_
 if not player_batting.empty:
     col1, col2, col3 = st.columns(3)
     with col1:
-        total_runs = player_batting['Runs'].sum()
+        total_runs = player_batting['runs'].sum()
         st.markdown(f'<div class="metric-card"><h3>Total Runs</h3><p>{total_runs}</p></div>', unsafe_allow_html=True)
     with col2:
-        avg_sr = player_batting['SR'].mean().round(2)
+        avg_sr = player_batting['sr'].mean().round(2)
         st.markdown(f'<div class="metric-card"><h3>Avg Strike Rate</h3><p>{avg_sr}</p></div>', unsafe_allow_html=True)
     with col3:
         matches = len(player_batting)
@@ -124,17 +124,17 @@ with tab1:
         col1, col2 = st.columns(2)
         
         with col1:
-            fig_runs = px.pie(player_batting, values='Runs', names='Format', 
+            fig_runs = px.pie(player_batting, values='runs', names='format', 
                             title='Runs Distribution by Format',
                             color_discrete_sequence=px.colors.sequential.Blues)
             fig_runs.update_layout(title_x=0.5)
             st.plotly_chart(fig_runs, use_container_width=True)
         
         with col2:
-            fig_sr = px.scatter(player_batting, x='Format', y='SR', 
-                              size='Runs', color='Format',
+            fig_sr = px.scatter(player_batting, x='format', y='sr', 
+                              size='runs', color='format',
                               title='Strike Rate Analysis',
-                              hover_data=['Runs'])
+                              hover_data=['runs'])
             fig_sr.update_layout(title_x=0.5)
             st.plotly_chart(fig_sr, use_container_width=True)
     else:
@@ -146,15 +146,15 @@ with tab2:
         col3, col4 = st.columns(2)
         
         with col3:
-            fig_wickets = px.bar(player_bowling, x='Format', y='Wickets',
-                               color='Format', 
+            fig_wickets = px.bar(player_bowling, x='format', y='wickets',
+                               color='format', 
                                title='Wickets by Format',
                                color_discrete_sequence=px.colors.sequential.Reds)
             fig_wickets.update_layout(title_x=0.5)
             st.plotly_chart(fig_wickets, use_container_width=True)
         
         with col4:
-            fig_eco = px.area(player_bowling, x='Format', y='Eco',
+            fig_eco = px.area(player_bowling, x='format', y='eco',
                             title='Economy Rate Trend',
                             color_discrete_sequence=['#2ECC71'])
             fig_eco.update_layout(title_x=0.5)