why i am facing with problem when i try to change columns to 0 an 1?

Question

data.head()

experience	stay
No relevent experience	0
Has relevent experience	1
No relevent experience	0
Has relevent experience	1
No relevent experience	0

data['experience'] = data['experience'].map({'Has relevent experience':True, 'No relevent experience':False})
data.head()

experience	stay
NaN	0
NaN	1
NaN	0
NaN	1
NaN	0

Why shows NaN here???

score 0 · Answer 1 · answered Feb 05 '23 at 11:35

0

It seems you have some whitespaces in your column. Try to use .str.strip before the mapping:

data['experience'] = data['experience'].str.strip()
data['experience'] = data['experience'].map({'Has relevent experience':True, 'No relevent experience':False})
print(data)

Prints:

   experience  stay
0       False     0
1        True     1
2       False     0
3        True     1
4       False     0

answered Feb 05 '23 at 11:35

Andrej Kesely

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It only works for 'True' and 'False', what about 1 and 0? Is there any method that can work for all of them? – Ashraf Badalov Feb 05 '23 at 17:34
@AshrafBadalov Do you want to convert `True`/`False` to `0`/`1`? Then you can do `data['experience'] = data['experience'].astype(int)` as last command. – Andrej Kesely Feb 05 '23 at 18:13
It still shows NaN, anyway thank you for the help – Ashraf Badalov Feb 05 '23 at 18:50

why i am facing with problem when i try to change columns to 0 an 1?

1 Answers1