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| import streamlit as st | |
| import pandas as pd | |
| import matplotlib.pyplot as plt | |
| import numpy as np | |
| # Load dataset | |
| Batting_Bowling = pd.read_csv("Final_Batting_Bowling (1).csv") | |
| Batting_Bowling.columns = Batting_Bowling.columns.str.strip() | |
| # Dropdown: Select Team | |
| team_option = st.selectbox("Select Team", sorted(Batting_Bowling['Final_Country'].dropna().unique())) | |
| # Filter dataset by team | |
| team_data = Batting_Bowling[Batting_Bowling['Final_Country'] == team_option] | |
| # Dropdown: Select Player | |
| player_option = st.selectbox("Select Player", sorted(team_data['name'].dropna().unique())) | |
| # Filter dataset by player | |
| player_data = team_data[team_data['name'] == player_option] | |
| # Dropdown: Select Category | |
| category = st.selectbox("Select Category", ["Batting", "Bowling"]) | |
| # Rename if needed | |
| if 'Categorey' in player_data.columns: | |
| player_data.rename(columns={'Categorey': 'Category'}, inplace=True) | |
| # Filter by selected category | |
| category_data = player_data[player_data['Category'].str.lower() == category.lower()] | |
| # Show stats | |
| st.subheader(f"{player_option}'s {category} Stats") | |
| st.write(category_data) | |
| # Columns to plot | |
| numeric_cols = ['Test', 'ODI', 'T20', 'IPL'] | |
| # Function to convert safely | |
| def clean_and_convert(val): | |
| if isinstance(val, str): | |
| if '/' in val or '-' in val or val.strip() in ['', '–', '-/-', 'nan']: | |
| return np.nan | |
| try: | |
| return float(val) | |
| except: | |
| return np.nan | |
| # Plotting | |
| if not category_data.empty: | |
| for i, (_, row) in enumerate(category_data.iterrows()): | |
| values = [clean_and_convert(row[col]) for col in numeric_cols] | |
| valid_data = [(col, v) for col, v in zip(numeric_cols, values) if not pd.isna(v)] | |
| if len(valid_data) == 0: | |
| continue # Skip if no numeric data | |
| formats, clean_vals = zip(*valid_data) | |
| # --- 1. Bar Chart --- | |
| st.markdown("### 📊 Bar Chart") | |
| fig_bar, ax_bar = plt.subplots() | |
| ax_bar.bar(formats, clean_vals, color='steelblue') | |
| ax_bar.set_ylabel("Values") | |
| ax_bar.set_title(f"{player_option}'s {category} Stats") | |
| st.pyplot(fig_bar) | |
| # --- 2. Line Chart --- | |
| st.markdown("### 📈 Line Chart") | |
| fig_line, ax_line = plt.subplots() | |
| ax_line.plot(formats, clean_vals, marker='o', linestyle='--', color='green') | |
| ax_line.set_ylabel("Values") | |
| ax_line.set_title(f"{category} Trends for {player_option}") | |
| st.pyplot(fig_line) | |
| # --- 3. Pie Chart --- | |
| st.markdown("### 🥧 Pie Chart") | |
| fig_pie, ax_pie = plt.subplots() | |
| ax_pie.pie(clean_vals, labels=formats, autopct='%1.1f%%', startangle=90) | |
| ax_pie.set_title(f"{category} Contribution by Format") | |
| st.pyplot(fig_pie) | |
| break # Show charts for just one valid row | |
| else: | |
| st.warning(f"No {category} stats found for {player_option}.") | |