Copying column values up based on other column values

[Jason Friedman]

>
> import numpy as np
> import pandas as pd
> from numpy.random import randn
> df=pd.DataFrame(randn(5,4),['A','B','C','D','E'],['W','X','Y','Z'])
>
> W X Y Z
> A -0.183141 -0.398652 0.909746 0.332105
> B -0.587611 -2.046930 1.446886 0.167606
> C 1.142661 -0.861617 -0.180631 1.650463
> D 1.174805 -0.957653 1.854577 0.335818
> E -0.680611 -1.051793 1.448004 -0.490869
>
> is there a way to create a column S - which will copy column column Y
> values UP- if values in column Y are above 1 - otherwise return new value
> above zero?.I made this manually:
>
> S:
>
> A 1.446886
> B 1.446886
> C 1.854577
> D 1.854577
> E 1.448004
>

Here's one solution. No consideration to performance.

import numpy as np
import pandas as pd
from numpy.random import randn
df=pd.DataFrame(randn(5,4),['A','B','C','D','E'],['W','X','Y','Z'])
print(df)

y_series = df["Y"]
for i in range(len(y_series)):
    if i == len(y_series) - 1:
        # Last one, nothing to copy
        break
    if y_series[i+1] > 1:
        y_series[i] = y_series[i+1]

df["Y"] = y_series
print(df)