python-sql-lessons/SQL/labs/solutions/Realty

Realty

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Title: Realty
Source: WDI-Skywalker (2015)
Modified by: Karolin Rafalski, Thom Page
Competencies: SQL queries, aggregation

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Learning Objectives

• Practice creating a database from the command line
• Practice seeding a database using SQL
• Practice using the Command Line API of postgresql
• Practice querying a database using SQL

Activity

Step 1 - Create a new database

• Create a new database called realty_db.

Step 2 - Create a Schema

• Use the given schema file named realty_schema.sql and create tables in your realty database which should model Apartments, Offices and Storefronts. They should have the following properties:

  An Apartment should have:

  • id - serial primary key
  • apartment_number - integer
  • bedrooms - integer
  • bathrooms - integer
  • address - varchar
  • tenant - varchar
  • occupied - boolean
  • sq_ft - integer
  • price - integer

  An Office should have:

  • id - serial primary key
  • office_number - integer
  • floors - integer
  • sq_ft - integer
  • cubicles - integer
  • bathrooms - integer
  • address - varchar
  • company - varchar
  • occupied - boolean
  • price - integer

  A Storefront should have:

  • address - varchar
  • occupied - boolean
  • price - integer
  • kitchen - boolean
  • sq_ft - integer
  • owner - varchar
  • outdoor_seating - boolean

• Load the seed file into your database from the command line. Use the psql shell to inspect your schema.

Step 3 - Define a seed file and seed your database

• In a SQL file named realty_seed.sql, write the proper INSERT commands that will add new entries into your apartment, office and storefront tables. You should create at least 3 entries for each table. Vary the attributes of each entry so no two are alike. From the command line, load this seed file into your database.

Step 4 - Queries

• In the given realty.sql file, write the SQL commands you would use to retrieve the following information from your database. Test each command in PSQL to make sure it is correct:

  • The average square footage of all offices.
  • The total number of apartments.
  • The apartments where there is no tenant
  • The names of all of the companies
  • The number of cubicles and bathrooms in the 3rd office
  • The storefronts that have kitchens
  • The storefront with the highest square footage and outdoor seating
  • The office with the lowest number of cubicles
  • The office with the most cubicles and bathrooms