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Rismon Hasiholan
SQLITE FOR DATA ANALYST AND DATA SCIENTIST WITH PYTHON GUI
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1531797SQLITE FOR DATA ANALYST AND DATA SCIENTIST WITH PYTHON GUIhttps://www.gandhi.com.mx/sqlite-for-data-analyst-and-data-scientist-with-python-gui-1/phttps://gandhi.vtexassets.com/arquivos/ids/617594/6247c3ef-df79-4f5b-a152-1179afdef0ca.jpg?v=638335527527930000246246MXNBALIGE PUBLISHINGInStock/Ebooks/1513277SQLITE FOR DATA ANALYST AND DATA SCIENTIST WITH PYTHON GUI246246https://www.gandhi.com.mx/sqlite-for-data-analyst-and-data-scientist-with-python-gui-1/phttps://gandhi.vtexassets.com/arquivos/ids/617594/6247c3ef-df79-4f5b-a152-1179afdef0ca.jpg?v=638335527527930000InStockMXN99999DIEbook20221230005662821_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1230005662821_<p>In this project, we will use the SQLite version of BikeStores database as a sample database to help you work with MySQL quickly and effectively. The stores table includes the stores information. Each store has a store name, contact information such as phone and email, and an address including street, city, state, and zip code. The staffs table stores the essential information of staffs including first name, last name. It also contains the communication information such as email and phone. A staff works at a store specified by the value in the store_id column. A store can have one or more staffs. A staff reports to a store manager specified by the value in the manager_id column. If the value in the manager_id is null, then the staff is the top manager. If a staff no longer works for any stores, the value in the active column is set to zero.</p><p>The categories table stores the bikes categories such as children bicycles, comfort bicycles, and electric bikes. The products table stores the products information such as name, brand, category, model year, and list price. Each product belongs to a brand specified by the brand_id column. Hence, a brand may have zero or many products. Each product also belongs a category specified by the category_id column. Also, each category may have zero or many products.</p><p>The customers table stores customers information including first name, last name, phone, email, street, city, state, zip code, and photo path. The orders table stores the sales orders header information including customer, order status, order date, required date, shipped date. It also stores the information on where the sales transaction was created (store) and who created it (staff). Each sales order has a row in the sales_orders table. A sales order has one or many line items stored in the order_items table. The order_items table stores the line items of a sales order. Each line item belongs to a sales order specified by the order_id column. A sales order line item includes product, order quantity, list price, and discount. The stocks table stores the inventory information i.e. the quantity of a particular product in a specific store.</p><p>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 order date by year, quarter, month, week, day, and hour; the distribution of amount by year, quarter, month, week, day, and hour; the distribution of bottom 10 sales by product, top 10 sales by product, bottom 10 sales by customer, top 10 sales by customer, bottom 10 sales by category, top 10 sales by category, bottom 10 sales by brand, top 10 sales by brand, bottom 10 sales by customer city, top 10 sales by customer city, bottom 10 sales by customer state, top 10 sales by customer state, average amount by month with mean and EWM, average amount by every month, amount feature over June 2017, amount feature over 2018, and all amount feature.</p>1230005662821_BALIGE PUBLISHINGlibro_electonico_43611c30-a76a-3071-b566-918d0177571d_1230005662821;1230005662821_1230005662821Rismon HasiholanInglésMéxicohttps://getbook.kobo.com/koboid-prod-public/f2ca928b-958d-498f-bb70-f76c6615d8f6-epub-ac6c4ea9-ff7e-46c8-8ee1-a7ba7f5c07f8.epub2022-07-09T00:00:00+00:00BALIGE PUBLISHING