How to deal with this complex logic in python pandas？

Question

I have some data like follow structure. It used in python pandas Data Frame and I named it df.

Data1,Data2,Flag
2016-04-29,00:40:15,1
2016-04-29,00:40:24,2
2         


        

Answer 1

I built a generator to produce the rows then used pd.concat

def get_row(df):
    ref = None
    for i, row in df.iterrows():
        if ref is not None:
            cond1 = (row.Data2.total_seconds() - 
                     ref.Data2.total_seconds() > 18)
            cond2 = row.Flag != ref.Flag
        if ref is None or cond1 or cond2:
            yield row
            ref = row

pd.concat([r for r in get_row(df)], axis=1).T

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Timing

Because @Kartik insisted :-)