Update pages/Automatic_Machine_learning_app.py

pages/Automatic_Machine_learning_app.py

@@ -3,27 +3,16 @@ import pandas as pd
 import plotly.express as px
 import plotly.graph_objects as go
 
+# --- Streamlit Page Styling ---
+st.set_page_config(page_title="Cricket Dashboard", layout="wide")
+
 st.markdown(
     """
     <style>
-    .stApp {
-        background: linear-gradient(to right, #eef2ff, #c7d2fe);
-        color: #1f2937;
-    }
-    .stTitle {
-        text-align: center;
-        color: #374151;
-        font-size: 28px;
-        font-weight: bold;
-    }
-    .stSelectbox {
-        background-color: white;
-        border-radius: 8px;
-        padding: 5px;
-    }
-    .css-1cpxqw2 {
-        border-radius: 12px;
-    }
+    .stApp { background: linear-gradient(to right, #eef2ff, #c7d2fe); color: #1f2937; }
+    .stTitle { text-align: center; color: #374151; font-size: 28px; font-weight: bold; }
+    .stSelectbox { background-color: white; border-radius: 8px; padding: 5px; }
+    .css-1cpxqw2 { border-radius: 12px; }
     </style>
     """,
     unsafe_allow_html=True
@@ -31,65 +20,129 @@ st.markdown(
 
 st.markdown("<h1 class='stTitle'>Cricket Icons Dashboard</h1>", unsafe_allow_html=True)
 
-# Load dataset
-data = pd.read_csv("Teams_batting.csv")
-data1 = pd.read_csv("team_bowling.csv")
+# --- Load Datasets ---
+batting_df = pd.read_csv("Teams_batting.csv")
+bowling_df = pd.read_csv("team_bowling.csv")
+
+# --- User Selection ---
+teams = batting_df["Team"].unique()
+selected_team = st.selectbox("Select a Team:", teams)
+players = batting_df[batting_df["Team"] == selected_team]["Player"].unique()
+selected_player = st.selectbox("Select a Player:", players)
 
-option1 = st.selectbox("Select a Team:", data["Team"].unique())
-option = st.selectbox("Select a Player:", data[data["Team"] == option1]["Player"].unique())
+# --- Filter Player Data ---
+player_batting = batting_df[batting_df["Player"] == selected_player]
+player_bowling = bowling_df[bowling_df["Player"] == selected_player]
 
-st.markdown(f"<h2 class='stTitle'>{option} - Batting Performance</h2>", unsafe_allow_html=True)
-player = data[data["Player"] == option]
-st.dataframe(player)
+st.markdown(f"<h2 class='stTitle'>{selected_player} - Batting Performance</h2>", unsafe_allow_html=True)
+st.dataframe(player_batting)
 
-st.markdown(f"<h2 class='stTitle'>{option} - Bowling Performance</h2>", unsafe_allow_html=True)
-player1 = data1[data1["Player"] == option]
-st.dataframe(player1)
+st.markdown(f"<h2 class='stTitle'>{selected_player} - Bowling Performance</h2>", unsafe_allow_html=True)
+st.dataframe(player_bowling)
 
-# Visualizations
 st.markdown("<h2 class='stTitle'>Performance Insights</h2>", unsafe_allow_html=True)
 
-# Batting Performance Visuals
-if not player.empty:
+# --- Batting Performance Visualizations ---
+if not player_batting.empty:
     fig_runs = px.bar(
-        player, x="Cricket Matches", y=["Matches", "Innings"], 
-        title=f"{option} - Matches & Innings", barmode="group", text_auto=True,
+        player_batting, x="Cricket Matches", y=["Matches", "Innings"], 
+        title=f"{selected_player} - Matches & Innings", barmode="group", text_auto=True,
         color_discrete_sequence=["#1E90FF"]
     )
     st.plotly_chart(fig_runs)
 
     fig_scores = px.bar(
-        player, x="Cricket Matches", y=["Runs", "Balls"], 
-        title=f"{option} - Runs & Balls Faced", barmode="group", text_auto=True,
+        player_batting, x="Cricket Matches", y=["Runs", "Balls"], 
+        title=f"{selected_player} - Runs & Balls Faced", barmode="group", text_auto=True,
         color_discrete_sequence=["#FFA500"]
     )
     st.plotly_chart(fig_scores)
 
     fig_boundaries = go.Figure()
     fig_boundaries.add_trace(go.Bar(
-        name="Fours", x=player["Cricket Matches"], y=player["Fours"], 
+        name="Fours", x=player_batting["Cricket Matches"], y=player_batting["Fours"],
         marker=dict(color="lime", line=dict(width=2, color="black"))
     ))
     fig_boundaries.add_trace(go.Bar(
-        name="Sixes", x=player["Cricket Matches"], y=player["Sixes"], 
+        name="Sixes", x=player_batting["Cricket Matches"], y=player_batting["Sixes"],
         marker=dict(color="purple", line=dict(width=2, color="black"))
     ))
-    fig_boundaries.update_layout(title=f"{option} - Fours & Sixes", barmode="group")
+    fig_boundaries.update_layout(title=f"{selected_player} - Fours & Sixes", barmode="group")
     st.plotly_chart(fig_boundaries)
 
     fig_centuries = px.pie(
         names=["50s", "100s", "200s", "300s", "400s"],
-        values=[player["50s"].sum(), player["100s"].sum(), player["200s"].sum(), player["300s"].sum(), player["400s"].sum()],
-        title=f"{option} - Milestone Contributions",
+        values=[player_batting["50s"].sum(), player_batting["100s"].sum(), player_batting["200s"].sum(), player_batting["300s"].sum(), player_batting["400s"].sum()],
+        title=f"{selected_player} - Milestone Contributions",
         hole=0.3, color_discrete_sequence=["#5DADEC", "#FFB6C1", "#FFD700", "#BA55D3", "#FFA07A"]
     )
     st.plotly_chart(fig_centuries)
 
-# Bowling Performance Visuals
-if not player1.empty:
+    # --- Strike Rate Chart ---
+    if "SR" in player_batting.columns:
+        fig_sr = go.Figure()
+        fig_sr.add_trace(
+            go.Scatter(
+                x=player_batting["Cricket Matches"], y=player_batting["SR"], mode='lines+markers',
+                marker=dict(size=10, color='blue', symbol="diamond", line=dict(color='black', width=2)),
+                line=dict(width=3, dash="dashdot", color='blue'), name="Strike Rate"
+            )
+        )
+
+        # Check if there are valid values in 'SR' column
+        if not player_batting["SR"].isna().all():
+            # Find the index of the maximum strike rate
+            max_sr_idx = player_batting["SR"].idxmax()
+            
+            # Ensure the index is valid and within bounds
+            if 0 <= max_sr_idx < len(player_batting):
+                fig_sr.add_annotation(
+                    x=player_batting["Cricket Matches"].iloc[max_sr_idx], 
+                    y=player_batting["SR"].iloc[max_sr_idx],
+                    text=f"🔥 Highest SR: {player_batting['SR'].iloc[max_sr_idx]:.2f}",
+                    showarrow=True, arrowhead=2, bgcolor="white"
+                )
+            else:
+                st.write("Error: Invalid index for highest strike rate.")
+        
+        fig_sr.update_layout(title="🚀 Strike Rate in Different Matches", xaxis_title="Matches", yaxis_title="Strike Rate")
+        st.plotly_chart(fig_sr)
+
+# --- Bowling Performance Visualizations ---
+if not player_bowling.empty:
     fig_wickets = px.bar(
-        player1, x="Cricket Matches", y=["Balls", "Maidens", "Wickets", "4w", "5w", "10w"],
-        title=f"{option} - Bowling Statistics", barmode="group", text_auto=True,
+        player_bowling, x="Cricket Matches", y=["Balls", "Maidens", "Wickets", "4w", "5w", "10w"],
+        title=f"{selected_player} - Bowling Statistics", barmode="group", text_auto=True,
         color_discrete_sequence=["#FF4500"]
     )
     st.plotly_chart(fig_wickets)
+
+    # --- Bowling Economy Chart ---
+    if "Econ" in player_bowling.columns:
+        fig_econ = go.Figure()
+        fig_econ.add_trace(
+            go.Scatter(
+                name="Economy Rate", x=player_bowling["Cricket Matches"], y=player_bowling["Econ"], mode="lines+markers",
+                marker=dict(color="red", size=12, symbol="star", line=dict(color="black", width=2)),
+                line=dict(width=3, dash="dot", color="red")
+            )
+        )
+
+        # Check if there are valid values in 'Econ' column
+        if not player_bowling["Econ"].isna().all():
+            # Find the index of the minimum economy rate
+            min_econ_idx = player_bowling["Econ"].idxmin()
+            
+            # Ensure the index is valid and within bounds
+            if 0 <= min_econ_idx < len(player_bowling):
+                fig_econ.add_annotation(
+                    x=player_bowling["Cricket Matches"].iloc[min_econ_idx], 
+                    y=player_bowling["Econ"].iloc[min_econ_idx],
+                    text=f"🎯 Best Economy: {player_bowling['Econ'].iloc[min_econ_idx]:.2f}",
+                    showarrow=True, arrowhead=2, bgcolor="white"
+                )
+            else:
+                st.write("Error: Invalid index for best economy rate.")
+        
+        fig_econ.update_layout(title="🎯 Bowling Economy Comparison", xaxis_title="Matches", yaxis_title="Economy Rate")
+        st.plotly_chart(fig_econ)