Update app.py

app.py

@@ -0,0 +1,149 @@
+import streamlit as st
+import pandas as pd
+import plotly.express as px
+import plotly.graph_objects as go
+
+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;
+            }
+    </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)  
+)
+
+# 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)