Python - compare previous row value and fill upwards when max is reached-CodePudding

I have this dataset:

col1 = [1,2,3,4,5,6,7,8]
col2 = [2,3,5,1,4,3,4,5]

df = pd.DataFrame({'Column1': col1, 'Column2': col2})

Column1 Column2
1       2
2       3
3       5
4       1
5       4
6       3
7       4
8       5

I am trying to get it so when the Column2 has stopped increasing that it fills the previous values so the expected output would be:


Column1 Column2
1       5
2       5
3       5
4       4
5       4
6       5
7       5
8       5

I tried doing this by a for loop comparing the previous to the current, but this would require lots of for loops. Is there an efficient way of doing this?

CodePudding user response：

groupby increasing stretches and transform with the last value:

df['Column2'] = (df.groupby(df['Column2'].diff().lt(0).cumsum())['Column2']
                   .transform('last')
                 )

output:

   Column1  Column2
0        1        5
1        2        5
2        3        5
3        4        4
4        5        4
5        6        5
6        7        5
7        8        5

intermediate to define the group:

df['Column2'].diff().lt(0).cumsum()

0    0
1    0
2    0
3    1
4    1
5    2
6    2
7    2
Name: Column2, dtype: int64

CodePudding user response：

Another solution:

df.Column2 = df.Column2[(df.Column2.diff() <= 0).shift(-1).fillna(True)]
df.Column2 = df.Column2.bfill()
print(df)

Prints:

   Column1  Column2
0        1      5.0
1        2      5.0
2        3      5.0
3        4      4.0
4        5      4.0
5        6      5.0
6        7      5.0
7        8      5.0