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Intermediate SQL Queries

Here you can access every table used in the course. To access each table, you will need to specify the cinema schema in your queries (e.g., cinema.reviews for the reviews table.

Note: When using sample integrations such as those that contain course data, you have read-only access. You can run queries, but cannot make any changes such as adding, deleting, or modifying the data (e.g., creating tables, views, etc.).

Take Notes

Add notes about the concepts you've learned and SQL cells with queries you want to keep.

SELECT COUNT(*) AS row_count FROM people;

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DataFrameas
movie_info
variable
-- Add your own queries here
SELECT *
FROM cinema.reviews
LIMIT 5

Explore Datasets

Use the tables to explore the data and practice your skills!

  • Select the film_id, imdb_score, and num_votes in the reviews table.
    • Filter your results for records where:
      • The imdb_score is greater than 8.
      • The number of votes (num_votes) is more than 1 million (1000000).
  • Return the average cost to make a movie (budget) by the country of origin in the films table.
    • Exclude NULL values in the budget column.
    • Order your results by the average budget in descending order.
  • Return the language, total budget (aliased as total_budget), and total gross (aliased as total_gross) from the films table.
    • Filter the records for films with a duration greater than 90.
    • Only include languages where the total gross is over 1 million (1000000).
    • Order your results by the total gross in descending order.
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DataFrameas
df
variable
-- Simple filtering of numeric values
-- As you learned in the previous exercise, the WHERE clause can also be used to filter numeric records, such as years or ages.
-- For example, the following query selects all details for films with a budget over ten thousand dollars:

SELECT *
FROM cinema.films
WHERE budget > 10000;
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DataFrameas
df1
variable