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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 | |
file_path = "Teams.csv" | |
df = pd.read_csv(file_path) | |
# 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: | |
# 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) | |
if show_bowling: | |
col1, col2 = st.columns(2) | |
with col1: | |
# Calculate Overs Bowled | |
overs_bowled = [ | |
player_data.get("bowling_Test_Balls", 0) // 6, | |
player_data.get("bowling_ODI_Balls", 0) // 6, | |
player_data.get("bowling_T20_Balls", 0) // 6, | |
player_data.get("bowling_IPL_Balls", 0) // 6 | |
] | |
# Bar Chart - Overs Bowled | |
fig, ax = plt.subplots() | |
ax.bar(labels, overs_bowled, color=["purple", "orange", "cyan", "brown"]) | |
ax.set_ylabel("Overs Bowled") | |
ax.set_title(f"Overs Bowled by {selected_player}") | |
st.pyplot(fig) | |
with col2: | |
# Line Chart - Wickets Taken | |
wickets_taken = [ | |
player_data.get("bowling_Wickets_Test", 0), | |
player_data.get("bowling_Wickets_ODI", 0), | |
player_data.get("bowling_Wickets_T20", 0), | |
player_data.get("bowling_Wickets_IPL", 0) | |
] | |
fig, ax = plt.subplots() | |
ax.plot(labels, wickets_taken, marker='o', linestyle='-', color='red') | |
ax.set_ylabel("Wickets Taken") | |
ax.set_title(f"Wickets Taken by {selected_player}") | |
st.pyplot(fig) | |