code for goal keeper.txt

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np

# Load the dataset
df = pd.read_csv('/content/goalkeeper.csv')

# Find the goalkeeper with the most clean sheets
most_clean_sheets = df.loc[df['Clean Sheets'].idxmax()]

# Find the goalkeeper with the fewest goals conceded
fewest_goals_conceded = df.loc[df['Goals Conceded'].idxmin()]

# Find the goalkeeper with the most penalties saved
most_penalties_saved = df.loc[df['Penalties Saved'].idxmax()]

# Print analysis results
print(f"Goalkeeper with the most clean sheets: {most_clean_sheets['Goalkeeper Name']} ({most_clean_sheets['Clean Sheets']} clean sheets)")
print(f"Goalkeeper with the fewest goals conceded: {fewest_goals_conceded['Goalkeeper Name']} ({fewest_goals_conceded['Goals Conceded']} goals conceded)")
print(f"Goalkeeper with the most penalties saved: {most_penalties_saved['Goalkeeper Name']} ({most_penalties_saved['Penalties Saved']} penalties saved)")

# Set the figure size
plt.figure(figsize=(12, 8))

# Set the position of bars on the x-axis
bar_width = 0.2
positions = np.arange(len(df))

# Create bars with some offset for side-by-side display
plt.bar(positions - bar_width, df['Clean Sheets'], width=bar_width, color='green', label='Clean Sheets')
plt.bar(positions, df['Goals Conceded'], width=bar_width, color='red', label='Goals Conceded')
plt.bar(positions + bar_width, df['Penalties Saved'], width=bar_width, color='blue', label='Penalties Saved')

# Add labels and title
plt.xlabel('Goalkeeper Name')
plt.ylabel('Count')
plt.title('Goalkeeper Performance Analysis')
plt.xticks(positions, df['Goalkeeper Name'], rotation=45, ha='right')
plt.legend()

# Show the plot
plt.tight_layout()
plt.show()