Pandas SQL Query: Display the name, salary and department number for employees who works either in department 70 or 90
17. Display Employees Working in Department 70 or 90
Write a Pandas program to display the first name, last name, salary and department number for employees who works either in department 70 or 90.
EMPLOYEES.csv
Sample Solution :
Python Code :
import pandas as pd
employees = pd.read_csv(r"EMPLOYEES.csv")
departments = pd.read_csv(r"DEPARTMENTS.csv")
job_history = pd.read_csv(r"JOB_HISTORY.csv")
jobs = pd.read_csv(r"JOBS.csv")
countries = pd.read_csv(r"COUNTRIES.csv")
regions = pd.read_csv(r"REGIONS.csv")
locations = pd.read_csv(r"LOCATIONS.csv")
print("First name Last name Salary Department ID")
result = employees[employees['department_id'].isin([70, 90])]
for index, row in result.iterrows():
print(row['first_name'].ljust(15),row['last_name'].ljust(15),str(row['salary']).ljust(9),row['department_id'])
Sample Output:
First name Last name Salary Department ID Steven King 24000 90.0 Neena Kochhar 17000 90.0 Lex De Haan 17000 90.0 Hermann Baer 10000 70.0
Equivalent SQL Syntax:
SELECT first_name, last_name, salary, department_id FROM employees WHERE department_id IN (70 , 90);
Click to view the table contain:
For more Practice: Solve these Related Problems:
- Write a Pandas program to display the first name, last name, salary, and department number for employees whose department is either 70 or 90 using the isin() method.
- Write a Pandas program to filter EMPLOYEES.csv for records where the department number is in [70, 90] and then sort the results by first name.
- Write a Pandas program to display employees working in department 70 or 90 and then compute the average salary for each of these departments.
- Write a Pandas program to display the specified fields for employees in departments 70 or 90 and then export the result to a new CSV file.
Python Code Editor:
Structure of HR database :

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