Foreign key join 1

Task:Find out employees with couple salary more than 10000.

Python

1 import pandas as pd
2 emp_file = "E:\\txt\\Employees.txt"
3 rel_file = "E:\\txt\\EmpRel.txt"
4 emp_info = pd.read_csv(emp_file,sep='\t')
5 rel_info = pd.read_csv(rel_file,sep='\t')
6 rel_info = rel_info[rel_info['Relationship']=="Spouse"]
7 emp1_join = pd.merge(rel_info,emp_info,left_on='Emp1',right_on='ID')
8 emp2_join = pd.merge(emp1_join,emp_info,left_on='Emp2',right_on='ID')
9 res = emp2_join[emp2_join['BasePay_x']+emp2_join['BasePay_y']>=10000]
10 r = res[['Name_x','Name_x']]
11 print(r)

Pandas can only join twice to get two columns of information, and then filter.

esProc

  A
1 =file("E:\\txt\\Employees.txt").import@t().keys(ID)
2 =file("E:\\txt\\EmpRel.txt").import@t()
3 =A2.select(Relationship=="Spouse")
4 >A3.switch(Emp1,A1;Emp2,A1)
5 =A3.select(Emp1.BasePay+Emp2.BasePay>=10000)
6 >A5.run(Emp1=Emp1.Name,Emp2=Emp2.Name)

Through foreign key objectification, esProc converts the foreign key field into the corresponding reference in the foreign key table, so that it can be treated as a single table.