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# Python code with various features
import numpy as np
import pandas as pd

def fibonacci(n):
    """Generate Fibonacci sequence up to n terms"""
    if n <= 0:
        return []
    elif n == 1:
        return [0]
    else:
        sequence = [0, 1]
        for i in range(2, n):
            sequence.append(sequence[i-1] + sequence[i-2])
        return sequence

# Generate and display Fibonacci sequence
fib_numbers = fibonacci(10)
print(f"First 10 Fibonacci numbers: {fib_numbers}")
print(f"Sum: {sum(fib_numbers)}")

# Create a DataFrame
df = pd.DataFrame({'fibonacci': fib_numbers})
print("\nDataFrame:")
print(df.head())

// JavaScript code with modern features
const data = [1, 2, 3, 4, 5];

// Arrow function with array methods
const processData = (arr) => {
    return arr
        .map(x => x * 2)
        .filter(x => x > 5)
        .reduce((sum, x) => sum + x, 0);
};

// Async function example
async function fetchData() {
    try {
        const result = processData(data);
        console.log(`Processed result: ${result}`);
        return result;
    } catch (error) {
        console.error('Error processing data:', error);
    }
}

// Execute the function
fetchData();

Configuration Example:

server:
  host: localhost
  port: 8080
  
database:
  url: postgresql://user:pass@localhost/db
  pool_size: 10
  
logging:
  level: INFO
  format: '%(asctime)s - %(name)s - %(levelname)s - %(message)s'

# R code for statistical analysis
library(ggplot2)

# Create sample data
set.seed(42)
data <- data.frame(
  x = rnorm(100, mean = 0, sd = 1),
  y = rnorm(100, mean = 0, sd = 1)
)

# Calculate correlation
correlation <- cor(data$x, data$y)
cat("Correlation between x and y:", correlation, "\n")

# Summary statistics
summary(data)

# Simple linear model
model <- lm(y ~ x, data = data)
print(summary(model))

-- SQL query example
SELECT 
    u.id,
    u.username,
    u.email,
    COUNT(p.id) as post_count,
    AVG(p.score) as avg_score
FROM users u
LEFT JOIN posts p ON u.id = p.user_id
WHERE u.created_at >= '2023-01-01'
GROUP BY u.id, u.username, u.email
HAVING COUNT(p.id) > 5
ORDER BY avg_score DESC
LIMIT 10;

-- Create index for optimization
CREATE INDEX idx_posts_user_created 
ON posts(user_id, created_at);