pages/1player_information.py

import streamlit as st
import pandas as pd
import matplotlib.pyplot as plt

# Set page configuration
st.set_page_config(page_title="Career Insights", layout="wide")

# Load data
df = pd.read_csv("Team_Info.csv")

# Get unique player names
player_names = df["Player"].unique()

# Search box for filtering player names
search_query = st.text_input("Search Player Name:")
filtered_players = [name for name in player_names if search_query.lower() in name.lower()] if search_query else player_names

# Player selection dropdown
selected_player = st.selectbox("Select Player", filtered_players)

# Buttons for Batting and Bowling
show_batting = st.button("Show Batting Stats")
show_bowling = st.button("Show Bowling Stats")

if selected_player:
    player_data = df[df["Player"] == selected_player].iloc[0]
    labels = ["Test", "ODI", "T20", "IPL"]
    
    # **Batting Stats Section**
    if show_batting:
        st.subheader(f"Batting Statistics - {selected_player}")
        col1, col2 = st.columns(2)
        
        with col1:
            # Pie Chart - Matches Played Across Formats
            matches = [
                player_data.get("Matches_Test", 0),
                player_data.get("Matches_ODI", 0),
                player_data.get("Matches_T20", 0),
                player_data.get("Matches_IPL", 0)
            ]
            fig, ax = plt.subplots()
            ax.pie(matches, labels=labels, autopct="%1.1f%%", startangle=90)
            ax.set_title(f"Matches Played by {selected_player}")
            st.pyplot(fig)
        
        with col2:
            # Bar Chart - Runs Scored
            batting_runs = [
                player_data.get("batting_Runs_Test", 0),
                player_data.get("batting_Runs_ODI", 0),
                player_data.get("batting_Runs_T20", 0),
                player_data.get("batting_Runs_IPL", 0)
            ]
            fig, ax = plt.subplots()
            ax.bar(labels, batting_runs, color=["gold", "green", "blue", "red"])
            ax.set_ylabel("Runs Scored")
            ax.set_title(f"Runs Scored by {selected_player}")
            st.pyplot(fig)
        
        col3, col4 = st.columns(2)
        
        with col3:
            # Bar Chart - 100s and 50s
            hundreds = [
                player_data.get("batting_100s_Test", 0),
                player_data.get("batting_100s_ODI", 0),
                player_data.get("batting_100s_T20", 0),
                player_data.get("batting_100s_IPL", 0)
            ]
            fifties = [
                player_data.get("batting_50s_Test", 0),
                player_data.get("batting_50s_ODI", 0),
                player_data.get("batting_50s_T20", 0),
                player_data.get("batting_50s_IPL", 0)
            ]
            fig, ax = plt.subplots()
            ax.bar(labels, hundreds, label="100s", color="gold")
            ax.bar(labels, fifties, label="50s", color="blue", bottom=hundreds)
            ax.set_ylabel("Count")
            ax.set_title(f"Centuries & Fifties by {selected_player}")
            ax.legend()
            st.pyplot(fig)
        
        with col4:
            # Line Chart - Strike Rate & Average
            strike_rate = [
                player_data.get("batting_SR_Test", 0),
                player_data.get("batting_SR_ODI", 0),
                player_data.get("batting_SR_T20", 0),
                player_data.get("batting_SR_IPL", 0)
            ]
            batting_avg = [
                player_data.get("batting_Average_Test", 0),
                player_data.get("batting_Average_ODI", 0),
                player_data.get("batting_Average_T20", 0),
                player_data.get("batting_Average_IPL", 0)
            ]
            fig, ax = plt.subplots()
            ax.plot(labels, strike_rate, marker='o', linestyle='-', color='red', label="Strike Rate")
            ax.plot(labels, batting_avg, marker='s', linestyle='--', color='green', label="Batting Average")
            ax.set_ylabel("Value")
            ax.set_title(f"Strike Rate & Batting Average of {selected_player}")
            ax.legend()
            st.pyplot(fig)

    # **Bowling Stats Section**
    if show_bowling:
        st.subheader(f"Bowling Statistics - {selected_player}")
        col1, col2 = st.columns(2)

        with col1:
            # Pie Chart - Wickets Taken Across Formats
            wickets = [
                player_data.get("Wickets_Test", 0),
                player_data.get("Wickets_ODI", 0),
                player_data.get("Wickets_T20", 0),
                player_data.get("Wickets_IPL", 0)
            ]
            fig, ax = plt.subplots(figsize=(5, 3))
            ax.pie(wickets, labels=labels, autopct="%1.1f%%", startangle=90)
            ax.set_title(f"Wickets Taken by {selected_player}")
            st.pyplot(fig)

        with col2:
            # Bar Chart - Economy Rate
            economy_rate = [
                player_data.get("Economy_Test", 0),
                player_data.get("Economy_ODI", 0),
                player_data.get("Economy_T20", 0),
                player_data.get("Economy_IPL", 0)
            ]
            fig, ax = plt.subplots(figsize=(5, 3))
            ax.bar(labels, economy_rate, color=["gold", "green", "blue", "red"])
            ax.set_ylabel("Economy Rate")
            ax.set_title(f"Economy Rate of {selected_player}")
            st.pyplot(fig)

        col3, col4 = st.columns(2)

        with col3:
            # Bar Chart - Balls Bowled
            balls_bowled = [
                player_data.get("bowling_Balls_Test", 0),
                player_data.get("bowling_Balls_ODI", 0),
                player_data.get("bowling_Balls_T20", 0),
                player_data.get("bowling_Balls_IPL", 0)
            ]
            fig, ax = plt.subplots(figsize=(5, 3))
            ax.bar(labels, balls_bowled, color=["red", "green", "blue", "purple"])
            ax.set_ylabel("Balls Bowled")
            ax.set_title(f"Balls Bowled by {selected_player}")
            st.pyplot(fig)

        with col4:
            # Bar Chart - Maidens Bowled
            maidens_bowled = [
                player_data.get("bowling_Maidens_Test", 0),
                player_data.get("bowling_Maidens_ODI", 0),
                player_data.get("bowling_Maidens_T20", 0),
                player_data.get("bowling_Maidens_IPL", 0)
            ]
            fig, ax = plt.subplots(figsize=(5, 3))
            ax.bar(labels, maidens_bowled, color=["cyan", "magenta", "yellow", "black"])
            ax.set_ylabel("Maidens Bowled")
            ax.set_title(f"Maidens Bowled by {selected_player}")
            st.pyplot(fig)