Separating unique, stable, samples using pandas

[keithpfio]

For future googlers, here's the method I figured out:

df['InputStable'] = df['InputBus'] == df['InputBus'].shift(periods=1, fill_value=0) & df['InputBus'].shift(periods=2, fill_value=0)

This creates a new boolean column, which contains true/false based on whether the current value equals the previous value and the one before that.

I think I'm binary bitwise ANDing two integers here and then comparing that result, which is probably breaking a thousand rules, but it seems to be working just fine in practice.

This utilizes the shift() function in pandas.

I also used drop() and drop_duplicates() to get rid repeated rows.