1483222FULL SOURCE CODE: POSTGRESQL AND DATA SCIENCE FOR PROGRAMMERS WITH PYTHON GUIhttps://www.gandhi.com.mx/full-source-code-postgresql-and-data-science-for-programmers-with-python-gui/phttps://gandhi.vtexassets.com/arquivos/ids/591778/5b842e1f-3dd6-44f8-9e90-681b031005e8.jpg?v=638335428138630000246246MXNBALIGE PUBLISHINGInStock/Ebooks/This project uses the PostgreSQL version of MySQL-based Sakila sample database which is a fictitious database designed to represent a DVD rental store. The tables of the database include film, film_category, actor, film_actor, customer, rental, payment and inventory among others. You can download the database from https://dev.mysql.com/doc/sakila/en/.In this project, you will write Python script to create every table and insert rows of data into each of them. You will develop GUI with PyQt5 to each table in the database. You will also create GUI to plot case distribution of film release year, film rating, rental duration, and categorize film length; plot rating variable against rental_duration variable in stacked bar plots; plot length variable against rental_duration variable in stacked bar plots; read payment table; plot case distribution of Year, Day, Month, Week, and Quarter of payment; plot which year, month, week, days of week, and quarter have most payment amount; read film list by joining five tables: category, film_category, film_actor, film, and actor; plot case distribution of top 10 and bottom 10 actors; plot which film title have least and most sales; plot which actor have least and most sales; plot which film category have least and most sales; plot case distribution of top 10 and bottom 10 overdue costumers; plot which store have most sales; plot average payment amount by month with mean and EWM; and plot payment amount over June 2005....1465217FULL SOURCE CODE: POSTGRESQL AND DATA SCIENCE FOR PROGRAMMERS WITH PYTHON GUI246246https://www.gandhi.com.mx/full-source-code-postgresql-and-data-science-for-programmers-with-python-gui/phttps://gandhi.vtexassets.com/arquivos/ids/591778/5b842e1f-3dd6-44f8-9e90-681b031005e8.jpg?v=638335428138630000InStockMXN99999DIEbook20221230005766581_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1230005766581_This project uses the PostgreSQL version of MySQL-based Sakila sample database which is a fictitious database designed to represent a DVD rental store. The tables of the database include film, film_category, actor, film_actor, customer, rental, payment and inventory among others. You can download the database from https://dev.mysql.com/doc/sakila/en/.In this project, you will write Python script to create every table and insert rows of data into each of them. You will develop GUI with PyQt5 to each table in the database. You will also create GUI to plot case distribution of film release year, film rating, rental duration, and categorize film length; plot rating variable against rental_duration variable in stacked bar plots; plot length variable against rental_duration variable in stacked bar plots; read payment table; plot case distribution of Year, Day, Month, Week, and Quarter of payment; plot which year, month, week, days of week, and quarter have most payment amount; read film list by joining five tables: category, film_category, film_actor, film, and actor; plot case distribution of top 10 and bottom 10 actors; plot which film title have least and most sales; plot which actor have least and most sales; plot which film category have least and most sales; plot case distribution of top 10 and bottom 10 overdue costumers; plot which store have most sales; plot average payment amount by month with mean and EWM; and plot payment amount over June 2005....1230005766581_BALIGE PUBLISHINGlibro_electonico_a697e430-d9ab-37bc-aa93-a6e2a4377459_1230005766581;1230005766581_1230005766581Rismon HasiholanInglésMéxicohttps://getbook.kobo.com/koboid-prod-public/f2ca928b-958d-498f-bb70-f76c6615d8f6-epub-196387cc-ca99-4995-a963-08f4f4453239.epub2022-09-19T00:00:00+00:00BALIGE PUBLISHING