I would like to create a new column with a numerical value based on the following conditions:
a. if gender is male & pet1==pet2, points = 5
b. if gender is female & (pet1 is 'cat' or pet1 is 'dog'), points = 5
c. all other combinations, points = 0
gender pet1 pet2
0 male dog dog
1 male cat cat
2 male dog cat
3 female cat squirrel
4 female dog dog
5 female squirrel cat
6 squirrel dog cat
I would like the end result to be as follows:
gender pet1 pet2 points
0 male dog dog 5
1 male cat cat 5
2 male dog cat 0
3 female cat squirrel 5
4 female dog dog 5
5 female squirrel cat 0
6 squirrel dog cat 0
How do I accomplish this?
You can do this using np.where, the conditions use bitwise & and | for and and or with parentheses around the multiple conditions due to operator precedence. So where the condition is true 5 is returned and 0 otherwise:
In [29]:
df['points'] = np.where( ( (df['gender'] == 'male') & (df['pet1'] == df['pet2'] ) ) | ( (df['gender'] == 'female') & (df['pet1'].isin(['cat','dog'] ) ) ), 5, 0)
df
Out[29]:
gender pet1 pet2 points
0 male dog dog 5
1 male cat cat 5
2 male dog cat 0
3 female cat squirrel 5
4 female dog dog 5
5 female squirrel cat 0
6 squirrel dog cat 0