Объединение данных

import csv
 
employees_file = 'employees.csv'
salary_file = 'salary.csv'
 
salary_data = {}
 
file = open(salary_file, 'r', encoding='utf-8')
reader = csv.DictReader(file)
for row in reader:
    salary_data[row['full_name']] = row['salary']
 
employees_full = []
 
file = open(employees_file, 'r', encoding='utf-8')
reader = csv.DictReader(file)
for row in reader:
    full_name = row['full_name']
    employee_data = {
        'full_name': full_name,
        'profession': row['profession'],
        'grade': row['grade'],
        'salary': salary_data[full_name]
    }
    employees_full.append(employee_data)
 
output_file = open('employees_full.csv', 'a', encoding='utf-8')
fieldnames = ['full_name', 'profession', 'grade', 'salary']
writer = csv.DictWriter(output_file, fieldnames=fieldnames)
 
writer.writeheader()
writer.writerows(employees_full)

import subprocess
 
sql3_commands = """
.separator ','
.import employees.csv employees
.import salary.csv    salary
select e.full_name, profession, grade, salary from salary s, employees e where e.full_name = s.full_name;
"""
 
process = subprocess.Popen(['sqlite3', 'my_database.db'], stdin=subprocess.PIPE)
process.communicate(input=sql3_commands.encode())

import pandas as pd
 
employees_df = pd.read_csv('employees.csv')
salary_df = pd.read_csv('salary.csv')
merged_df = pd.merge(employees_df, salary_df, on='full_name', how='left')
merged_df = merged_df.rename(columns={'salary_x': 'salary'})
merged_df.to_csv('employees_full.csv', index=False, columns=['full_name', 'profession', 'grade', 'salary'])