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Intermediate SQL
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  • Intermediate SQL Sandbox

    👋 Welcome to your new workspace! You can use this interactive notebook to take notes, explore the course data, and practice your SQL skills!

    The films, people, reviews, and roles tables from Intermediate SQL are available for you to query in the SQL cell below! Click inside the cell and press "Run" to execute the pre-written query or write your own query!

    Note that the tables are stored in a schema named cinema. To access each table, you must add "cinema." before the table name (e.g., cinema.reviews).

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    DataFrameavailable as
    books
    variable
    -- Select all entries from the reviews table
    SELECT * 
    FROM cinema.films
    LIMIT 100

    Click "Add markdown" to add and edit text cells for notes, and "Add SQL" to continue practicing your queries!

    Intermediate SQL Interactive Cheat Sheet

    Below are some interactive examples of things you learned from the course. Bookmark this page as a reference and a place to experiment with queries!

    Filtering

    Use WHERE to filter records in a table.

    Spinner
    DataFrameavailable as
    df
    variable
    SELECT *
    FROM cinema.reviews
    WHERE imdb_score > 8.5

    Use AND and OR in combination with WHERE for more specific filtering.

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    DataFrameavailable as
    df
    variable
    SELECT *
    FROM cinema.films
    WHERE country = 'Germany'
    	AND release_year > 2010

    Use BETWEEN to filter for records within a specified range (inclusive).

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    DataFrameavailable as
    df
    variable
    SELECT *
    FROM cinema.films
    WHERE budget BETWEEN 1000000 AND 5000000

    Use LIKE and NOT LIKE to filter records for (or without) a pattern. The % wildcard matches one, zero, or many characters. The _ wildcard matches a single character.

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    DataFrameavailable as
    df
    variable
    SELECT *
    FROM cinema.films
    WHERE title LIKE '%Alien%'

    Use WHERE IN to filter for multiple conditions.

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    DataFrameavailable as
    df
    variable
    SELECT *
    FROM cinema.films
    WHERE release_year IN (1990, 2000)

    Use NULL in your queries to find or filter out records with missing values.

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    DataFrameavailable as
    df
    variable
    SELECT *
    FROM cinema.films
    WHERE budget IS NULL