pd.Grouper creates full-length bins, even when there’s no data in the tail bin (like 16:00–16:30). This is normal behavior for time-based grouping.

Try using the label and closed parameters.

filtered = self.df.groupby(
    pd.Grouper(key='Datetime', freq='30min', origin='start', label='right', closed='left')
)

or simply drop the nulls when you aggragte/get the mean

self.other_df['Avg_volatility'] = filtered['volatility'].mean().dropna()

pd.Grouper creates full-length bins, even when there’s no data in the tail bin (like 16:00–16:30). This is normal behavior for time-based grouping.

Try using the closed parameters.

filtered = self.df.groupby(
    pd.Grouper(key='Datetime', freq='30min', origin='start', closed='left')
).mean().reset_index()

or simply drop the nulls when you aggragte/get the mean

self.other_df['Avg_volatility'] = filtered['volatility'].mean().dropna()