Information:
System version : Windows 10 64-bit
Python version : Python 3.6.0 :: Anaconda 4.3.1 (64-bit)
Python version : Python 3.6.0 :: Anaconda 4.3.1 (64-bit)
Code:
import pandas as pd
import numpy as np
df1 = pd.DataFrame()
number = [1,2,3,4,5]
sex = ['male','male','female','female','female']
df1['number'] = number
df1['sex'] = sex
df1['income'] = [500,2000,500,2000,500]
print(df1)
print('='*45)
conditions = [
(df1['sex']=='male') & (df1['income']>1000),
(df1['sex']=='male') & (df1['income']<1000),
(df1['sex']=='female') & (df1['income']>1000)
]
choices = ['male-high_income','male-low_income', 'female-high_income']
df1['group'] = np.select(conditions, choices, default='no_group')
print(df1)
Result:
number sex income
0 1 male 500
1 2 male 2000
2 3 female 500
3 4 female 2000
4 5 female 500
=============================================
number sex income group
0 1 male 500 male-low_income
1 2 male 2000 male-high_income
2 3 female 500 no_group
3 4 female 2000 female-high_income
4 5 female 500 no_group
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