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"]
    
    if show_batting:
        col1, col2 = st.columns(2)
        
        with col1:
            # Bar Chart - 100s and 50s
            hundreds = [
                player_data.get("100s_Test", 0),
                player_data.get("100s_ODI", 0),
                player_data.get("100s_T20", 0),
                player_data.get("100s_IPL", 0)
            ]
            fifties = [
                player_data.get("50s_Test", 0),
                player_data.get("50s_ODI", 0),
                player_data.get("50s_T20", 0),
                player_data.get("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 col2:
            # Line Chart - Strike Rate & Average
            strike_rate = [
                player_data.get("SR_Test", 0),
                player_data.get("SR_ODI", 0),
                player_data.get("SR_T20", 0),
                player_data.get("SR_IPL", 0)
            ]
            batting_avg = [
                player_data.get("Avg_Test", 0),
                player_data.get("Avg_ODI", 0),
                player_data.get("Avg_T20", 0),
                player_data.get("Avg_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)
    
    if show_bowling:
        col1, col2 = st.columns(2)
        
        with col1:
            # Bar Chart - Economy Rate
            economy_rate = [
                player_data.get("Econ_Test", 0),
                player_data.get("Econ_ODI", 0),
                player_data.get("Econ_T20", 0),
                player_data.get("Econ_IPL", 0)
            ]
            fig, ax = plt.subplots()
            ax.bar(labels, economy_rate, color=["purple", "orange", "cyan", "brown"])
            ax.set_ylabel("Economy Rate")
            ax.set_title(f"Economy Rate of {selected_player}")
            st.pyplot(fig)
        
        with col2:
            # Scatter Plot - Bowling Average & Strike Rate
            bowling_avg = [
                player_data.get("Bowl_Avg_Test", 0),
                player_data.get("Bowl_Avg_ODI", 0),
                player_data.get("Bowl_Avg_T20", 0),
                player_data.get("Bowl_Avg_IPL", 0)
            ]
            bowling_sr = [
                player_data.get("Bowl_SR_Test", 0),
                player_data.get("Bowl_SR_ODI", 0),
                player_data.get("Bowl_SR_T20", 0),
                player_data.get("Bowl_SR_IPL", 0)
            ]
            fig, ax = plt.subplots()
            ax.scatter(labels, bowling_avg, color='blue', label="Bowling Average")
            ax.scatter(labels, bowling_sr, color='red', label="Bowling Strike Rate")
            ax.set_ylabel("Value")
            ax.set_title(f"Bowling Average & Strike Rate of {selected_player}")
            ax.legend()
            st.pyplot(fig)