Suppose you have a time series dataset with temperature readings collected every hour. Explain how you would handle missing data points using Pandas, discussing not only the techniques you would use but also the implications of those choices.

def handle_missing_temperatures(df): # Option 1: Forward fill to propagate the last valid observation df['temperature'] = df['temperature'].fillna(method='ffill') # Option 2: Interpolation for a more accurate trend # df['temperature'] = df['temperature'].interpolate(method='linear') return df