Update app.py

app.py

@@ -3,147 +3,124 @@ import pandas as pd
 import plotly.express as px
 import plotly.graph_objects as go
 
-st.markdown("""
+# --- Streamlit Page Styling ---
+st.set_page_config(page_title="Cricket Dashboard", layout="wide")
+
+st.markdown(
+    """
     <style>
-        .stApp {
-            background-color: #E3F2FD;  
-        }
-        .title {
-            text-align: center;
-            font-size: 28px;
-            font-weight: bold;
-            color: #2C3E50;
-        }
-        .subtitle {
-            text-align: center;
-            font-size: 30px;
-            font-weight: bold;
-            color: #003366;
-            margin-top: 10px;
-        }
-        .stButton > button {
-            width: 100%;
-            background-color: #1E88E5;
-            color: white;
-            font-size: 16px;
-            font-weight: bold;
-            border-radius: 6px;
-            padding: 8px;
-            transition: 0.3s;
-        }
-        .stButton > button:hover {
-            background-color: #1565C0; 
-        }
-        .result-box {
-            text-align: center;
-            font-size: 22px;
-            font-weight: bold;
-            color: white;
-            padding: 15px;
-            border-radius: 8px;
-            margin-top: 20px;
-            background-color: #388E3C;
-            }
+    .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)
-
-# Load dataset
-df = pd.read_csv("Cleaned_data.csv")
-
-st.markdown("<h1 class='title'>Player Performance Analysis</h1>", unsafe_allow_html=True)
-
-st.markdown("<hr style='border:1px solid #ddd;'>", unsafe_allow_html=True)
-
-default_player = "Virat Kohli"
-player_name = st.selectbox(
-    "Select a Player:", 
-    df['Player'].unique(), 
-    index=list(df['Player'].unique()).index(default_player)  
+    """,
+    unsafe_allow_html=True
 )
 
-# Filter data for selected player
-player_data = df[df['Player'] == player_name].iloc[0]
-formats = ['Test', 'ODI', 'T20', 'IPL']
-
-st.markdown("<br>", unsafe_allow_html=True)
-
-st.markdown("<h3 class='title'>Batting Career Summary</h3>", unsafe_allow_html=True)
-
-batting_summary = []
-
-for fmt in formats:
-    batting_summary.append([
-        fmt,
-        player_data[f'Matches_{fmt}'],
-        player_data[f'batting_Innings_{fmt}'],
-        player_data[f'batting_Runs_{fmt}'],
-        player_data[f'batting_Balls_{fmt}'],
-        player_data[f'batting_Highest_{fmt}'],
-        player_data[f'batting_Average_{fmt}'],
-        player_data[f'batting_SR_{fmt}'],
-        player_data[f'batting_Not Out_{fmt}'],
-        player_data[f'batting_Fours_{fmt}'],
-        player_data[f'batting_Sixes_{fmt}'],
-        player_data[f'batting_50s_{fmt}'],
-        player_data[f'batting_100s_{fmt}'],
-        player_data[f'batting_200s_{fmt}']
-    ])
-
-batting_df = pd.DataFrame(batting_summary, columns=[
-    'Format', 'M', 'Inn', 'Runs', 'BF', 'HS', 'Avg', 'SR', 'NO', 'Fours', 'Sixes', '50s', '100s', '200s'
-])
-
-st.dataframe(batting_df.style.set_properties(**{'text-align': 'center'}))
-
-st.markdown("<br>", unsafe_allow_html=True)
-
-st.markdown("<h3 class='title'>Bowling Career Summary</h3>", unsafe_allow_html=True)
-
-bowling_summary = []
-
-for fmt in formats:
-    bowling_summary.append([
-        fmt,
-        player_data[f'Matches_{fmt}'],
-        player_data[f'bowling_{fmt}_Innings'],
-        player_data[f'bowling_{fmt}_Balls'],
-        player_data[f'bowling_{fmt}_Runs'],
-        player_data[f'bowling_{fmt}_Wickets'],
-        player_data[f'bowling_{fmt}_Avg'],
-        player_data[f'bowling_{fmt}_Eco'],
-        player_data[f'bowling_{fmt}_SR'],
-        player_data[f'bowling_{fmt}_BBI'],
-        player_data[f'bowling_{fmt}_BBM'],
-        player_data[f'bowling_{fmt}_5w'],
-        player_data[f'bowling_{fmt}_10w']
-    ])
-
-bowling_df = pd.DataFrame(bowling_summary, columns=[
-    'Format', 'M', 'Inn', 'B', 'Runs', 'Wkts', 'Avg', 'Econ', 'SR', 'BBI', 'BBM', '5w', '10w'
-])
-
-st.dataframe(bowling_df.style.set_properties(**{'text-align': 'center'}))
-
-st.markdown("<hr style='border:1px solid #ddd;'>", unsafe_allow_html=True)
-
-st.markdown("<h2 class='title'>🌟 Advanced Performance Insights 🌟</h2>", unsafe_allow_html=True)
-
-fig1 = px.bar(
-    batting_df, x="Format", y="Runs", title="🏏 Total Runs per Format",
-    text_auto=True, color_discrete_sequence=["#1E90FF"], opacity=0.9
-)
-st.plotly_chart(fig1)
-
-fig2 = px.bar(
-    bowling_df, x="Format", y="Wkts", title="🎯 Total Wickets per Format",
-    text_auto=True, color_discrete_sequence=["#FF4500"], opacity=0.9
-)
-st.plotly_chart(fig2)
-
-fig3 = px.pie(
-    names=["Centuries", "Fifties"],
-    values=[batting_df["100s"].sum(), batting_df["50s"].sum()],
-    title="🏆 Centuries vs Fifties Contribution",
-    hole=0.3, color_discrete_sequence=["#5DADEC", "#FFB6C1", "#7FDBB6", "#FFD700", "#FFA07A", "#BA55D3"]
-)
-st.plotly_chart(fig3)
+st.markdown("<h1 class='stTitle'>Cricket Icons Dashboard</h1>", unsafe_allow_html=True)
+
+# --- 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)
+
+# --- 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'>{selected_player} - Batting Performance</h2>", unsafe_allow_html=True)
+st.dataframe(player_batting)
+
+st.markdown(f"<h2 class='stTitle'>{selected_player} - Bowling Performance</h2>", unsafe_allow_html=True)
+st.dataframe(player_bowling)
+
+st.markdown("<h2 class='stTitle'>Performance Insights</h2>", unsafe_allow_html=True)
+
+# --- Batting Performance Visualizations ---
+if not player_batting.empty:
+    fig_runs = px.bar(
+        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_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_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_batting["Cricket Matches"], y=player_batting["Sixes"],
+        marker=dict(color="purple", line=dict(width=2, color="black"))
+    ))
+    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_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)
+
+    # --- 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"
+            )
+        )
+        max_sr_idx = player_batting["SR"].idxmax()
+        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"
+        )
+        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(
+        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")
+            )
+        )
+        min_econ_idx = player_bowling["Econ"].idxmin()
+        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"
+        )
+        fig_econ.update_layout(title="🎯 Bowling Economy Comparison", xaxis_title="Matches", yaxis_title="Economy Rate")
+        st.plotly_chart(fig_econ)