display the first and last name, department, city, and state province for each employee.
SELECT T1.first_name, T1.last_name, T2.department_name, T3.city, T3.state_province FROM employees AS T1 JOIN departments AS T2 ON T1.department_id = T2.department_id JOIN locations AS T3 ON T2.location_id = T3.location_id
``` yaml
departments: # name of dataframe
- DEPARTMENT_ID:
    dtype: int64
    sample_values: 10, 20, 30
- DEPARTMENT_NAME:
    dtype: string
    sample_values: Administration, Marketing, Purchasing
- MANAGER_ID:
    dtype: int64
    sample_values: 200, 201, 114
- LOCATION_ID:
    dtype: int64
    sample_values: 1700, 1800, 1700

employees: # name of dataframe
- EMPLOYEE_ID:
    dtype: int64
    sample_values: 100, 101, 102
- FIRST_NAME:
    dtype: string
    sample_values: Steven, Neena, Lex
- LAST_NAME:
    dtype: string
    sample_values: King, Kochhar, De Haan
- EMAIL:
    dtype: string
    sample_values: SKING, NKOCHHAR, LDEHAAN
- PHONE_NUMBER:
    dtype: string
    sample_values: 515.123.4567, 515.123.4568, 515.123.4569
- HIRE_DATE:
    dtype: datetime
    sample_values: 1987-06-17, 1987-06-18, 1987-06-19
- JOB_ID:
    dtype: string
    sample_values: AD_PRES, AD_VP, AD_VP
- SALARY:
    dtype: int64
    sample_values: 24000, 17000, 17000
- COMMISSION_PCT:
    dtype: float64
    sample_values: 0.0, 0.0, 0.0
- MANAGER_ID:
    dtype: int64
    sample_values: 0, 100, 100
- DEPARTMENT_ID:
    dtype: int64
    sample_values: 90, 90, 90

locations: # name of dataframe
- LOCATION_ID:
    dtype: int64
    sample_values: 1000, 1100, 1200
- STREET_ADDRESS:
    dtype: string
    sample_values: 1297 Via Cola di Rie, 93091 Calle della Testa, 2017 Shinjuku-ku
- POSTAL_CODE:
    dtype: numeric
    sample_values: 989, 10934, 1689
- CITY:
    dtype: string
    sample_values: Roma, Venice, Tokyo
- STATE_PROVINCE:
    dtype: string
    sample_values: ', , Tokyo Prefecture'
- COUNTRY_ID:
    dtype: string
    sample_values: IT, IT, JP

```
Foreign Key constraints:
Column 'department_id' in dataframe 'employees' has a foreign key relation to column 'department_id' in dataframe 'departments'.

FIRST_NAME,LAST_NAME,DEPARTMENT_NAME,CITY,STATE_PROVINCE
Steven,King,Executive,Seattle,Washington
Neena,Kochhar,Executive,Seattle,Washington
Lex,De Haan,Executive,Seattle,Washington
Alexander,Hunold,IT,Southlake,Texas
Bruce,Ernst,IT,Southlake,Texas
David,Austin,IT,Southlake,Texas
Valli,Pataballa,IT,Southlake,Texas
Diana,Lorentz,IT,Southlake,Texas
Nancy,Greenberg,Finance,Seattle,Washington
Daniel,Faviet,Finance,Seattle,Washington
John,Chen,Finance,Seattle,Washington
Ismael,Sciarra,Finance,Seattle,Washington
Jose Manuel,Urman,Finance,Seattle,Washington
Luis,Popp,Finance,Seattle,Washington
Den,Raphaely,Purchasing,Seattle,Washington
Alexander,Khoo,Purchasing,Seattle,Washington
Shelli,Baida,Purchasing,Seattle,Washington
Sigal,Tobias,Purchasing,Seattle,Washington
Guy,Himuro,Purchasing,Seattle,Washington
Karen,Colmenares,Purchasing,Seattle,Washington
Matthew,Weiss,Shipping,South San Francisco,California
Adam,Fripp,Shipping,South San Francisco,California
Payam,Kaufling,Shipping,South San Francisco,California
Shanta,Vollman,Shipping,South San Francisco,California
Kevin,Mourgos,Shipping,South San Francisco,California
Julia,Nayer,Shipping,South San Francisco,California
Irene,Mikkilineni,Shipping,South San Francisco,California
James,Landry,Shipping,South San Francisco,California
Steven,Markle,Shipping,South San Francisco,California
Laura,Bissot,Shipping,South San Francisco,California
Mozhe,Atkinson,Shipping,South San Francisco,California
James,Marlow,Shipping,South San Francisco,California
TJ,Olson,Shipping,South San Francisco,California
Jason,Mallin,Shipping,South San Francisco,California
Michael,Rogers,Shipping,South San Francisco,California
Ki,Gee,Shipping,South San Francisco,California
Hazel,Philtanker,Shipping,South San Francisco,California
Renske,Ladwig,Shipping,South San Francisco,California
Stephen,Stiles,Shipping,South San Francisco,California
John,Seo,Shipping,South San Francisco,California
Joshua,Patel,Shipping,South San Francisco,California
Trenna,Rajs,Shipping,South San Francisco,California
Curtis,Davies,Shipping,South San Francisco,California
Randall,Matos,Shipping,South San Francisco,California
Peter,Vargas,Shipping,South San Francisco,California
John,Russell,Sales,OX9 9ZB,Oxford
Karen,Partners,Sales,OX9 9ZB,Oxford
Alberto,Errazuriz,Sales,OX9 9ZB,Oxford
Gerald,Cambrault,Sales,OX9 9ZB,Oxford
Eleni,Zlotkey,Sales,OX9 9ZB,Oxford
Peter,Tucker,Sales,OX9 9ZB,Oxford
David,Bernstein,Sales,OX9 9ZB,Oxford
Peter,Hall,Sales,OX9 9ZB,Oxford
Christopher,Olsen,Sales,OX9 9ZB,Oxford
Nanette,Cambrault,Sales,OX9 9ZB,Oxford
Oliver,Tuvault,Sales,OX9 9ZB,Oxford
Janette,King,Sales,OX9 9ZB,Oxford
Patrick,Sully,Sales,OX9 9ZB,Oxford
Allan,McEwen,Sales,OX9 9ZB,Oxford
Lindsey,Smith,Sales,OX9 9ZB,Oxford
Louise,Doran,Sales,OX9 9ZB,Oxford
Sarath,Sewall,Sales,OX9 9ZB,Oxford
Clara,Vishney,Sales,OX9 9ZB,Oxford
Danielle,Greene,Sales,OX9 9ZB,Oxford
Mattea,Marvins,Sales,OX9 9ZB,Oxford
David,Lee,Sales,OX9 9ZB,Oxford
Sundar,Ande,Sales,OX9 9ZB,Oxford
Amit,Banda,Sales,OX9 9ZB,Oxford
Lisa,Ozer,Sales,OX9 9ZB,Oxford
Harrison,Bloom,Sales,OX9 9ZB,Oxford
Tayler,Fox,Sales,OX9 9ZB,Oxford
William,Smith,Sales,OX9 9ZB,Oxford
Elizabeth,Bates,Sales,OX9 9ZB,Oxford
Sundita,Kumar,Sales,OX9 9ZB,Oxford
Ellen,Abel,Sales,OX9 9ZB,Oxford
Alyssa,Hutton,Sales,OX9 9ZB,Oxford
Jonathon,Taylor,Sales,OX9 9ZB,Oxford
Jack,Livingston,Sales,OX9 9ZB,Oxford
Charles,Johnson,Sales,OX9 9ZB,Oxford
Winston,Taylor,Shipping,South San Francisco,California
Jean,Fleaur,Shipping,South San Francisco,California
Martha,Sullivan,Shipping,South San Francisco,California
Girard,Geoni,Shipping,South San Francisco,California
Nandita,Sarchand,Shipping,South San Francisco,California
Alexis,Bull,Shipping,South San Francisco,California
Julia,Dellinger,Shipping,South San Francisco,California
Anthony,Cabrio,Shipping,South San Francisco,California
Kelly,Chung,Shipping,South San Francisco,California
Jennifer,Dilly,Shipping,South San Francisco,California
Timothy,Gates,Shipping,South San Francisco,California
Randall,Perkins,Shipping,South San Francisco,California
Sarah,Bell,Shipping,South San Francisco,California
Britney,Everett,Shipping,South San Francisco,California
Samuel,McCain,Shipping,South San Francisco,California
Vance,Jones,Shipping,South San Francisco,California
Alana,Walsh,Shipping,South San Francisco,California
Kevin,Feeney,Shipping,South San Francisco,California
Donald,OConnell,Shipping,South San Francisco,California
Douglas,Grant,Shipping,South San Francisco,California
Jennifer,Whalen,Administration,Seattle,Washington
Michael,Hartstein,Marketing,Toronto,Ontario
Pat,Fay,Marketing,Toronto,Ontario
Susan,Mavris,Human Resources,London,
Hermann,Baer,Public Relations,Munich,Bavaria
Shelley,Higgins,Accounting,Seattle,Washington
William,Gietz,Accounting,Seattle,Washington
