Code Editor for analysis.py

import pandas as pd
import numpy as np

def calculate_stats(data):
    """Calculate basic statistical measures for stock data"""
    
    current_price = data['Close'].iloc[-1]
    prev_price = data['Close'].iloc[-2] if len(data) > 1 else current_price
    
    daily_returns = data['Close'].pct_change().dropna()
    
    stats = {
        'current_price': current_price,
        'prev_price': prev_price,
        'mean_price': data['Close'].mean(),
        'max_price': data['High'].max(),
        'min_price': data['Low'].min(),
        'daily_return': ((current_price - prev_price) / prev_price) * 100,
        'volatility': daily_returns.std() * np.sqrt(252) * 100,  # Annualized volatility
        'avg_volume': data['Volume'].mean()
    }
    
    return stats

def calculate_moving_averages(data, periods):
    """Calculate moving averages for given periods"""
    
    result = data.copy()
    
    for period in periods:
        result[f'MA_{period}'] = data['Close'].rolling(window=period).mean()
    
    return result

def calculate_rsi(prices, period=14):
    """Calculate Relative Strength Index"""
    
    delta = prices.diff()
    gain = (delta.where(delta > 0, 0)).rolling(window=period).mean()
    loss = (-delta.where(delta < 0, 0)).rolling(window=period).mean()
    
    rs = gain / loss
    rsi = 100 - (100 / (1 + rs))
    
    return rsi

def calculate_bollinger_bands(prices, period=20, std_dev=2):
    """Calculate Bollinger Bands"""
    
    sma = prices.rolling(window=period).mean()
    std = prices.rolling(window=period).std()
    
    upper_band = sma + (std * std_dev)
    lower_band = sma - (std * std_dev)
    
    return upper_band, lower_band

def calculate_technical_indicators(data):
    """Calculate various technical indicators"""
    
    result = data.copy()
    
    # RSI
    result['RSI'] = calculate_rsi(data['Close'])
    
    # Bollinger Bands
    result['BB_Upper'], result['BB_Lower'] = calculate_bollinger_bands(data['Close'])
    result['BB_Middle'] = data['Close'].rolling(window=20).mean()
    
    # MACD
    exp1 = data['Close'].ewm(span=12, adjust=False).mean()
    exp2 = data['Close'].ewm(span=26, adjust=False).mean()
    result['MACD'] = exp1 - exp2
    result['MACD_Signal'] = result['MACD'].ewm(span=9, adjust=False).mean()
    result['MACD_Histogram'] = result['MACD'] - result['MACD_Signal']
    
    return result