df looks like this:
| description and keybenefits (14) | brand_cooltouch (1711) | brand_easylogic (1712) |
|---|---|---|
| Lorem Ipsum cooltouch Lorem Ipsum | ||
| Lorem Ipsum easylogic Lorem Ipsum | ||
| Lorem Ipsum Lorem Ipsum |
What I want:
When Column description and keybenefits (14) contains the value ‘cooltouch’ columm brand_cooltouch (1711) needs to be set to value 1 (int).
When Column description and keybenefits (14) contains the value ‘easylogic’ columm brand_easylogic (1712) needs to be set to value 1 (int).
Output that I want:
| description and keybenefits (14) | brand_cooltouch (1711) | brand_easylogic (1712) |
|---|---|---|
| Lorem Ipsum cooltouch Lorem Ipsum | 1 | |
| Lorem Ipsum Lorem Ipsum easylogic | 1 | |
| Lorem Ipsum Lorem Ipsum |
Any help is very much appreciated.
>Solution :
One can use pandas.Series.str.contains.
For the string cooltouch do the following
df['brand_cooltouch (1711)'] = df['description and keybenefits (14)'].str.contains('cooltouch', case=False).astype(int)
[Out]:
description and keybenefits (14) brand_cooltouch (1711) brand_easylogic (1712)
0 Lorem Ipsum cooltouch Lorem Ipsum 1 None
1 Lorem Ipsum easylogic Lorem Ipsum 0 None
2 Lorem Ipsum Lorem Ipsum 0 None
For the string easylogic, do the following
df['brand_easylogic (1712)'] = df['description and keybenefits (14)'].str.contains('easylogic', case=False).astype(int)
[Out]:
description and keybenefits (14) brand_cooltouch (1711) brand_easylogic (1712)
0 Lorem Ipsum cooltouch Lorem Ipsum 1 0
1 Lorem Ipsum easylogic Lorem Ipsum 0 1
2 Lorem Ipsum Lorem Ipsum 0 0
Notes:
case=Falseis to make it case insensitive.