chart_builder.py

import matplotlib.pyplot as plt
from collections import Counter

# Data (including محمد زناتي)
data = {
    "Eyad Ahmed Farouk": ["Customization (Rice)", "Command-Line Tools (CLI)", "AI", "DevOps"],
    "Azad Mohamed": ["DevOps", "Filesystem"],
    "Mariam Sayed": ["Cybersecurity"],
    "omnia ibrahim": ["AI", "DevOps"],
    "Samir Ahmed Morse Ahmed": ["Cybersecurity", "Customization (Rice)", "Command-Line Tools (CLI)", "AI"],
    "Bishoy Ehab": ["Command-Line Tools (CLI)"],
    "Amna": ["Command-Line Tools (CLI)", "AI", "DevOps"],
    "Roqaya": ["Command-Line Tools (CLI)", "AI"],
    "محمد زناتي": ["Customization (Rice)", "Command-Line Tools (CLI)", "AI"],
}

# Flatten all topics into a single list
all_topics = [topic for topics in data.values() for topic in topics]

# Count frequency of each topic
topic_counts = Counter(all_topics)

# Sort by frequency (most common first)
topics, counts = zip(*topic_counts.most_common())

# Plot the data
plt.figure(figsize=(8, 5))
# plt.barh(topics, counts, color='skyblue')
plt.pie(counts, labels=topics, autopct='%1.1f%%', startangle=140)
plt.title("Topic Distribution")
plt.gca().invert_yaxis()
plt.tight_layout()
plt.savefig("chart.png")