Pandas transform series values until condition is met without for loop

Question

I have a pandas Series contain 0s and 1s. Now I want to convert all the 0s to 1s which come before the first 1, and rest of the 1s to 0s. I can achieve that using the below code:

import pandas as pd
a = [0,0,1,0,0,1]
df = pd.Series(a)
flag = True
for i in range(df.shape[0]):
 if (df[i]!=1) & flag:
 df[i]=1
 elif flag:
 flag=False
 else:
 df[i]=0
print(df)

Final dataframe:

[1,1,1,0,0,0]

But how can I optimize it? Perhaps by avoiding the for loop?

Answer 1

Use a combination of Series.cummax() and Series.shift()

a = pd.Series([0,0,1,0,0,1])
a.cummax() # [0,0,1,1,1,1]
a.cummax().shift(fill_value=0) # [0,0,0,1,1,1]

Then "invert" the 0's and 1's

df = 1 - a.cummax().shift(fill_value=0) # [1,1,1,0,0,0]