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DATA SCIENCE USING JDBC AND POSTGRESQL WITH OBJECT-ORIENTED APPROACH AND APACHE NETBEANS IDE - Vivian Siahaan

DATA SCIENCE USING JDBC AND POSTGRESQL WITH OBJECT-ORIENTED APPROACH AND APACHE NETBEANS IDE

By: Vivian Siahaan, Rismon Hasiholan Sianipar

eBook | 10 May 2023

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This book uses the PostgreSQL-version of Sakila sample database which is a fictitious database designed to represent a DVD rental store. The 15 tables of the database include film, film_category, actor, customer, rental, payment and inventory among others. The Sakila sample database is intended to provide a standard schema that can be used for examples in books, tutorials, articles, samples, and so forth. You can download the sample database from https://viviansiahaan.blogspot.com/2023/05/data-science-using-jdbc-and-postgresql.html.

In this project, you will design the form for every table and you will plot: top 10 film distribution by release year; top 10 film distribution by rating; top 10 film distribution by rental duration; top 10 film distribution by language; film distribution by categorized rental rate; film distribution by categorized length; film distribution by categorized replacement cost; top 10 film distribution by actor name; top 10 actor name distribution by average rental rate; top 10 actor name distribution by average replacement cost; film distribution by rating; rating distribution by average rental rate; rating distribution by average replacement cost; top 10 film distribution by category name, category distribution by average replacement cost; category distribution by average rental rate; category distribution by length; top 10 city distribution by country; top 10 address distribution by district, top 10 address distribution by country; top 10 address distribution by city; top 10 address distribution by district; top 10 address distribution by country; top 10 address distribution by city; top 10 inventory distribution by release year; top 10 inventory distribution by film rating; top 10 inventory distribution by film language; top 10 inventory distribution by film rental duration; top 10 inventory distribution by city; top 10 inventory distribution by country; top 10 customer distribution by country; and so on.

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