s = pd.Series({0: 'registration address-complement-insert-confirmation input',
1: 'decision-tree first-interaction-validation options',
2: 'decision-tree invalid-format-validation options',
3: 'decision-tree first-interaction-validation options',
4: 'registration address-complement-request view',
5: 'onboarding return-start origin',
6: 'registration address-complement-request origin',
7: 'decision-tree identified-regex options',
8: 'decision-tree first-interaction-validation options',
9: 'decision-tree first-interaction-validation options'})
I have the following series object. What I want to do is to map it and mark every single string after 'onboarding return-start origin' as true. Any ideas on how I could build this condition?
Wanted result
s = pd.Series({0: False,
1: False,
2: False,
3: False,
4: False,
5: True,
6: True,
7: True,
8: True,
9: True})
CodePudding user response:
Use Series.cummax
with test first matched value by Series.eq
:
s = s.eq('onboarding return-start origin').cummax()
print (s)
0 False
1 False
2 False
3 False
4 False
5 True
6 True
7 True
8 True
9 True
dtype: bool