Advanced Time Series & Resampling

Resampling (Change Data Frequency)

Convert daily data to weekly, hourly to daily, etc.

# Aggregate (downsample)
daily_data.resample('W').sum()   # Daily → Weekly
daily_data.resample('M').mean()  # Daily → Monthly

# Interpolate (upsample)
monthly_data.resample('D').interpolate()  # Monthly → Daily

Rolling Windows (Moving Statistics)

Compute statistics over sliding windows — great for smoothing and trend detection.

df['MA_7'] = df['price'].rolling(window=7).mean()
df['volatility'] = df['price'].rolling(window=30).std()
df['max_30'] = df['price'].rolling(window=30).max()

Common Rolling Operations

• `.mean()" — Moving average
• `.std()" — Volatility
• `.min()/.max()" — Bounds
• `.sum()" — Cumulative