DATA SCIENCE USING JDBC AND MYSQL WITH OBJECT-ORIENTED APPROACH AND APACHE NETBEANS IDE / Najlacnejšie knihy
DATA SCIENCE USING JDBC AND MYSQL WITH OBJECT-ORIENTED APPROACH AND APACHE NETBEANS IDE

Code: 50992128

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

by Rismon Hasiholan Sianipar, Vivian Siahaan

This book uses the 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 oth ... more

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Book synopsis

This book uses the 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.

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 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; top 10 customer distribution by city; top 10 customer distribution by district; top 10 customer distribution by store country; top 10 customer distribution by store city; top 10 customer distribution by store district; top 10 staff distribution by country; top 10 staff distribution by city; rental distribution by year of rental date; rental distribution by month of rental date; 10 rental distribution by week of rental date; rental distribution by day of rental date; rental distribution by quarter of rental date; rental distribution by film release year; rental distribution by film duration; rental distribution by film rating; top 10 rental distribution by staff name; rental distribution by film language; top 10 rental distribution by film title; rental distribution by customer active; top 10 rental distribution by film category; top 10 rental distribution by actor name; top 10 rental distribution by customer name; top 10 rental distribution by customer city; top 10 rental distribution by customer country, top 10 rental distribution by customer district; payment distribution by year of payment date; payment distribution by month of payment date; top 10 payment distribution by week of payment date; payment distribution by day of payment date; payment distribution by quarter of payment date; payment distribution by film release year; payment distribution by film duration; payment distribution by film rating; top 10 payment distribution by staff name; payment distribution by film language; top 10 payment distribution by film title; payment distribution by customer active; top 10 payment distribution by film category; top 10 payment distribution by actor name; top 10 payment distribution by customer name; top 10 payment distribution by customer city; top 10 payment distribution by customer country; and top 10 payment distribution by customer district.

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