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weather-logs-in-sql

Design and create a database for scraping All books for each category using DB Browser for sqllite from this web site (http://books.toscrape.com/)

1- create books & categories table 2- create notebook to scrap data and save data in the database 3- create another notebook to answer some questions using SQL Language 01) Write a sql query to get books that has rate >=3 and has 'Mr' in its name. 02) Write a sql query to get books that has rate >=3 or price > 20. 03) Write a sql query to get books that has rate not 3. 04) Write a sql query to get books that has price between 10 and 40 and has rate 3 or 4 or 1. 05) Write a sql query to get the top 5 most expensive books (order books desc with price column and then limit the result to the first 5). 06) Write a sql query to get the 3rd 10 books in the books table order first by rate desc and then by price asc. 07) Write a sql query to add a new category in categories table and add 5 books to this category in books table with title, rate and price. 08) Write a sql query to update book's rate to 3 that thier price < 20£. 09) Write a sql query to delete all books that have price > 50£ and has rate <= 2. 10) Write a sql query to count the number of books that have 'Secret' in thier names and price between 10£ and 25£. 11) Write a sql query to get the minimum & maximum price for all the books that have rate 5. 12) Write a sql query to calculate the avg price for all the books that have rate 5. 13) Write a sql query to sum all book's price that have rate 2 and price between 10 and 40 14) Write a sql query to join both books & categories table into one new table containing book_name & category_name & book_rate and book_price. 15) Write a sql query to calculate how many books each rate has and have price between 20£ and 30£. 16) Write a sql query to calculate how many books each category has having count > 10. 17) Write a sql query to get all books with category_name='Music' using subquery. 4- Export Database to CSV File and use pandas to read this CSV.

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