How To Manipulate Data In Arrays Using Pandas (and Resetting Evaluations)

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Solution 1:

Try:

import pandas as pd
import numpy as np

df = pd.DataFrame({'col0':[1,2,3,4,5,6,7,8,9]
              ,'col1':[5,4.9,5.5,3.5,3.1,4.5,5.5,1.2,5.8]
              ,'col2':[2.5,2.45,2.75,1.75,1.55,2.25,2.75,0.6,2.9]
              ,'col3':[np.nan,2.45,2.75,2.75,2.75,2.75,2.75,2.75,2.9]
              })


threshold = 2.71

grp = df['col2'].ge(threshold).cumsum().shift().bfill()

df['col3'] = df['col2'].groupby(grp).transform(lambda x: x.shift(-1).cummax().shift())

print(df)

Output:

   col0  col1  col2  col3
015.02.50NaN124.92.452.45235.52.752.75343.51.75NaN453.11.551.55564.52.252.25675.52.752.75781.20.60NaN895.82.902.90

Details:

Create grouping using greater or equal to threshold, then apply the same logic to each group withn at the dataframe using groupby with transform.