Time-Series: Resampling and Rolling

Welcome to **Day 115**. Today we do advanced time-series math.

Resampling: The Time-Based GroupBy

If شما have daily data but want a monthly report, use `.resample()`. (Note: The date must be the Index).

# Group by Month and get the Sum

monthly_data = df.resample('M').sum()

Rolling: Moving Averages (Day 66 in SQL!)

Remember our SQL window functions? Here is the Pandas version:

# 7-day moving average of sales

df['7day_avg'] = df['sales'].rolling(window=7).mean()

Why this is powerful

You can see "Trends" instantly. By resampling to a 'W' (Weekly) or 'M' (Monthly) frequency, you remove the noise of individual days and see the actual growth of your business.

Your Task for Today

Calculate a 30-day rolling average for a stock price dataset.

*Day 116: Applying Custom Functions with .apply().*