Pandas SQL Query: Display the name, salary and department number for employees who works either in department 70 or 90

Last update on September 12 2025 12:52:59 (UTC/GMT +8 hours)

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.

Go to:

PREV : Employees with First Name Ending in d, n, or s (Desc).
NEXT : Display Employees Whose Managers Have IDs 120, 103, or 145.

Python Code Editor:

Structure of HR database :

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