pages/1player_information.py

import streamlit as st
import pandas as pd
import matplotlib.pyplot as plt
import streamlit as st
import base64  

from streamlit_extras.switch_page_button import switch_page

# Load and encode background image
def get_base64_bg(image_path):
    with open(image_path, "rb") as img_file:
        encoded = base64.b64encode(img_file.read()).decode()
    return f"data:image/jpg;base64,{encoded}"

background_img = get_base64_bg("background.jpg")

# Inject custom CSS with background
st.markdown(
    f"""
    <style>
        .stApp {{
            background-image: url("{background_img}");
            background-size: cover;
            background-repeat: no-repeat;
            background-attachment: fixed;
        }}
        .header {{
            text-align: center;
            color: red;
            font-size: 30px;
            font-weight: bold;
            display: flex;
            justify-content: center;
            align-items: center;
            position: relative;
            padding-top: 20px;
        }}
        .logo {{
            position: absolute;
            right: 20px;
            top: 10px;
            width: 80px;
            height: auto;
        }}
        .sub-header {{
            color: darkorange;
            font-size: 26px;
            font-weight: bold;
            margin-top: 30px;
        }}
        .text {{
            font-size: 17px;
            color: black;
            font-style: italic;
            background-color: rgba(255, 255, 255, 0.75);
            padding: 15px;
            border-radius: 10px;
            margin-bottom: 20px;
        }}
        .footer {{
            font-size: 14px;
            color: #333;
            margin-top: 50px;
            text-align: center;
            font-style: italic;
        }}
    </style>
    """,
    unsafe_allow_html=True
)

# App Header with Logo
st.markdown(
    """
    <div class='header'>
        🏏 Cric Metrics - AI-Powered Cricket Insights 🏏
        <img src='1.png' class='logo'>
    </div>
    """,
    unsafe_allow_html=True
)

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

# Load data
df = pd.read_csv("Reduced_final_teams.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
if len(filtered_players) == 0:
    st.warning("Player not found. Please try a different name.")

# 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:
        st.subheader(f"Batting Stats for {selected_player}")

        col1, col2 = st.columns(2)
        with col1:
            # Pie Chart - Matches Played
            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:
            # Stacked 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)

        # Bar Chart - Balls Faced
        batting_balls = [
            player_data.get("batting_Balls_Test", 0),
            player_data.get("batting_Balls_ODI", 0),
            player_data.get("batting_Balls_T20", 0),
            player_data.get("batting_Balls_IPL", 0)
        ]
        fig, ax = plt.subplots(figsize=(5,3))
        ax.bar(labels, batting_balls, color=["red", "green", "blue", "purple"])
        ax.set_ylabel("Balls Faced")
        ax.set_title(f"Balls Faced by {selected_player}")
        st.pyplot(fig)

    if show_bowling:
        st.subheader(f"Bowling Stats for {selected_player}")

        col1, col2 = st.columns(2)
        with col1:
            # Pie Chart - Bowling Averages
            bowling_avg = [
                0 if pd.isna(player_data.get("bowling_Test_Avg", 0)) else float(player_data.get("bowling_Test_Avg", 0)),
                0 if pd.isna(player_data.get("bowling_ODI_Avg", 0)) else float(player_data.get("bowling_ODI_Avg", 0)),
                0 if pd.isna(player_data.get("bowling_T20_Avg", 0)) else float(player_data.get("bowling_T20_Avg", 0)),
                0 if pd.isna(player_data.get("bowling_IPL_Avg", 0)) else float(player_data.get("bowling_IPL_Avg", 0))
            ]
            fig, ax = plt.subplots()
            ax.pie(bowling_avg, labels=labels, autopct="%1.1f%%", startangle=90)
            ax.set_title(f"Bowling Averages of {selected_player}")
            st.pyplot(fig)

        with col2:
            # Bar Chart - Bowling Innings
            bowling_innings = [
                player_data.get("bowling_Test_Innings", 0),
                player_data.get("bowling_ODI_Innings", 0),
                player_data.get("bowling_T20_Innings", 0),
                player_data.get("bowling_IPL_Innings", 0)
            ]
            fig, ax = plt.subplots()
            ax.bar(labels, bowling_innings, color=["blue", "green", "purple", "orange"])
            ax.set_ylabel("Innings Bowled")
            ax.set_title(f"Bowling Innings of {selected_player}")
            st.pyplot(fig)

        # Balls Bowled
        balls_bowled = [
            player_data.get("bowling_Test_Balls", 0),
            player_data.get("bowling_ODI_Balls", 0),
            player_data.get("bowling_T20_Balls", 0),
            player_data.get("bowling_IPL_Balls", 0)
        ]
        fig, ax = plt.subplots(figsize=(5, 3))
        ax.bar(labels, balls_bowled, color=["red", "yellow", "blue", "green"])
        ax.set_ylabel("Balls Bowled")
        ax.set_title(f"Balls Bowled by {selected_player}")
        st.pyplot(fig)