import matplotlib.pyplot as plt
import numpy as np

# Sample survey responses with updated skills
survey_responses = {
    'Python': 3,  # Intermediate
    'Java/Scala': 2,  # Beginner
    'SQL': 4,  # Advanced
    'Shell Scripting': 1,  # No Experience
    'Relational Database Design': 3,  # Intermediate
    'Data Warehousing Concepts': 2,  # Beginner
    'Data Lake Architecture': 3,  # Intermediate
    'ETL Tools': 1,  # No Experience
    'Data Transformation Techniques': 4,  # Advanced
    'Hadoop Ecosystem': 2,  # Beginner
    'Apache Spark': 3,  # Intermediate
    'Kafka': 1,  # No Experience
    'AWS': 4,  # Advanced
    'Google Cloud Platform': 2,  # Beginner
    'Azure': 3,  # Intermediate
    'Data Privacy Regulations': 3,  # Intermediate
    'Data Encryption and Security Protocols': 2,  # Beginner
    'Machine Learning Algorithms': 3,  # Intermediate
    'Analytical Tools': 4,  # Advanced
    'Agile Methodologies': 2,  # Beginner
    'Team Collaboration Tools': 3,  # Intermediate
    'Documentation Skills': 4,  # Advanced
    'Troubleshooting Data Pipeline Issues': 3,  # Intermediate
    'Optimizing Data Storage and Retrieval': 4,  # Advanced
    'Keeping Up with Industry Trends': 3,  # Intermediate
    'Professional Development': 2  # Beginner
}

# List of skills
labels = list(survey_responses.keys())
num_vars = len(labels)

# Compute angle for each axis
angles = np.linspace(0, 2 * np.pi, num_vars, endpoint=False).tolist()

# The plot is a circle, so we need to "complete the loop"
# and append the start to the end.
values = list(survey_responses.values())
values += values[:1]
angles += angles[:1]

# Setup the radar chart
fig, ax = plt.subplots(figsize=(10, 10), subplot_kw=dict(polar=True))

# Draw the outline of the spider diagram
ax.fill(angles, values, color='blue', alpha=0.25)
ax.plot(angles, values, color='blue', linewidth=2)

# Draw one axe per variable and add labels
ax.set_yticklabels([])
ax.set_xticks(angles[:-1])
ax.set_xticklabels(labels)

# Show the radar chart
plt.title('Data Engineer Skills Assessment', size=20, color='blue', y=1.1)
plt.show()