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

Question

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?

Asked By: user3234242

||

Source

Answer 1

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

Answered By: mozway

Answer 2

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

Answered By: Andrej Kesely

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

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