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import streamlit as st | |
import pandas as pd | |
import matplotlib.pyplot as plt | |
import streamlit as st | |
# 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) |