Data Analysis Projects With Mysql Sqlite Postgresql And Sql Server Using Python Gui

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DATA ANALYSIS PROJECTS WITH MYSQL, SQLITE, POSTGRESQL, AND SQL SERVER USING PYTHON GUI

Author : Vivian Siahaan,Rismon Hasiholan Sianipar
Publisher : BALIGE PUBLISHING
Page : 1647 pages
File Size : 52,9 Mb
Release : 2022-10-26
Category : Computers
ISBN : 8210379456XXX

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DATA ANALYSIS PROJECTS WITH MYSQL, SQLITE, POSTGRESQL, AND SQL SERVER USING PYTHON GUI by Vivian Siahaan,Rismon Hasiholan Sianipar Pdf

PROJECT 1: FULL SOURCE CODE: POSTGRESQL AND DATA SCIENCE FOR PROGRAMMERS WITH PYTHON GUI 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. PROJECT 2: FULL SOURCE CODE: MYSQL FOR STUDENTS AND PROGRAMMERS WITH PYTHON GUI In this project, we provide you with a MySQL version of an Oracle sample database named OT which is based on a global fictitious company that sells computer hardware including storage, motherboard, RAM, video card, and CPU. The company maintains the product information such as name, description standard cost, list price, and product line. It also tracks the inventory information for all products including warehouses where products are available. Because the company operates globally, it has warehouses in various locations around the world. The company records all customer information including name, address, and website. Each customer has at least one contact person with detailed information including name, email, and phone. The company also places a credit limit on each customer to limit the amount that customer can owe. Whenever a customer issues a purchase order, a sales order is created in the database with the pending status. When the company ships the order, the order status becomes shipped. In case the customer cancels an order, the order status becomes canceled. In addition to the sales information, the employee data is recorded with some basic information such as name, email, phone, job title, manager, and hire date. 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, and day; 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 status, top 10 sales by status, 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 2016, amount feature over 2017, and amount payment in all years. PROJECT 3: ZERO TO MASTERY: THE COMPLETE GUIDE TO LEARNING SQLITE AND PYTHON GUI In this project, we provide you with the SQLite version of The Oracle Database Sample Schemas that provides a common platform for examples in each release of the Oracle Database. The sample database is also a good database for practicing with SQL, especially SQLite. The detailed description of the database can be found on: http://luna-ext.di.fc.ul.pt/oracle11g/server.112/e10831/diagrams.htm#insertedID0. The four schemas are a set of interlinked schemas. This set of schemas provides a layered approach to complexity: A simple schema Human Resources (HR) is useful for introducing basic topics. An extension to this schema supports Oracle Internet Directory demos; A second schema, Order Entry (OE), is useful for dealing with matters of intermediate complexity. Many data types are available in this schema, including non-scalar data types; The Online Catalog (OC) subschema is a collection of object-relational database objects built inside the OE schema; The Product Media (PM) schema is dedicated to multimedia data types; The Sales History (SH) schema is designed to allow for demos with large amounts of data. An extension to this schema provides support for advanced analytic processing. The HR schema consists of seven tables: regions, countries, locations, departments, employees, jobs, and job_histories. This book only implements HR schema, since the other schemas will be implemented in the next books. PROJECT 4: FULL SOURCE CODE: SQL SERVER FOR STUDENTS AND DATA SCIENTISTS WITH PYTHON GUI In this project, we provide you with the SQL SERVER version of SQLite sample database named chinook. The chinook sample database is a good database for practicing with SQL, especially PostgreSQL. The detailed description of the database can be found on: https://www.sqlitetutorial.net/sqlite-sample-database/. The sample database consists of 11 tables: The employee table stores employees data such as employee id, last name, first name, etc. It also has a field named ReportsTo to specify who reports to whom; customers table stores customers data; invoices & invoice_items tables: these two tables store invoice data. The invoice table stores invoice header data and the invoice_items table stores the invoice line items data; The artist table stores artists data. It is a simple table that contains only the artist id and name; The album table stores data about a list of tracks. Each album belongs to one artist. However, one artist may have multiple albums; The media_type table stores media types such as MPEG audio and AAC audio files; genre table stores music types such as rock, jazz, metal, etc; The track table stores the data of songs. Each track belongs to one album; playlist & playlist_track tables: The playlist table store data about playlists. Each playlist contains a list of tracks. Each track may belong to multiple playlists. The relationship between the playlist table and track table is many-to-many. The playlist_track table is used to reflect this relationship. 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, and day; the distribution of amount by year, quarter, month, week, day, and hour; the bottom/top 10 sales by employee, the bottom/top 10 sales by customer, the bottom/top 10 sales by customer, the bottom/top 10 sales by artist, the bottom/top 10 sales by genre, the bottom/top 10 sales by play list, the bottom/top 10 sales by customer city, the bottom/top 10 sales by customer city, the bottom/top 10 sales by customer city, the payment amount by month with mean and EWM, the average payment amount by every month, and amount payment in all years.

DATA VISUALIZATION AND DATA ANALYTICS PROJECTS WITH MYSQL, SQLITE, POSTGRESQL, AND SQL SERVER USING PYTHON GUI

Author : Vivian Siahaan,Rismon Hasiholan Sianipar
Publisher : BALIGE PUBLISHING
Page : 1665 pages
File Size : 45,5 Mb
Release : 2022-10-26
Category : Computers
ISBN : 8210379456XXX

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DATA VISUALIZATION AND DATA ANALYTICS PROJECTS WITH MYSQL, SQLITE, POSTGRESQL, AND SQL SERVER USING PYTHON GUI by Vivian Siahaan,Rismon Hasiholan Sianipar Pdf

PROJECT 1: MYSQL FOR DATA ANALYSIS AND VISUALIZATION WITH PYTHON GUI In this project, you will use the Northwind database which is a sample database that was originally created by Microsoft and used as the basis for their tutorials in a variety of database products for decades. The Northwind database contains the sales data for a fictitious company called “Northwind Traders,” which imports and exports specialty foods from around the world. The Northwind database is an excellent tutorial schema for a small-business ERP, with customers, orders, inventory, purchasing, suppliers, shipping, employees, and single-entry accounting. The Northwind dataset includes sample data for the following: Suppliers: Suppliers and vendors of Northwind; Customers: Customers who buy products from Northwind; Employees: Employee details of Northwind traders; Products: Product information; Shippers: The details of the shippers who ship the products from the traders to the end-customers; Orders and Order_Details: Sales Order transactions taking place between the customers & the company. The Northwind sample database includes 11 tables and the table relationships are showcased in the following entity relationship diagram. 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 supplier, top 10 sales by supplier, bottom 10 sales by customer country, top 10 sales by customer country, bottom 10 sales by supplier country, top 10 sales by supplier country, average amount by month with mean and ewm, average amount by every month, amount feature over june 1997, amount feature over 1998, and all amount feature. PROJECT 2: FULL SOURCE CODE: THE COMPLETE GUIDE TO LEARNING POSTGRESQL AND DATA SCIENCE WITH PYTHON GUI In this project, we provide you with the PostgreSQL version of SQLite sample database named chinook. The chinook sample database is a good database for practicing with SQL, especially PostgreSQL. The detailed description of the database can be found on: https://www.sqlitetutorial.net/sqlite-sample-database/. The sample database consists of 11 tables: The employee table stores employees data such as employee id, last name, first name, etc. It also has a field named ReportsTo to specify who reports to whom; customers table stores customers data; invoices & invoice_items tables: these two tables store invoice data. The invoice table stores invoice header data and the invoice_items table stores the invoice line items data; The artist table stores artists data. It is a simple table that contains only the artist id and name; The album table stores data about a list of tracks. Each album belongs to one artist. However, one artist may have multiple albums; The media_type table stores media types such as MPEG audio and AAC audio files; genre table stores music types such as rock, jazz, metal, etc; The track table stores the data of songs. Each track belongs to one album; playlist & playlist_track tables: The playlist table store data about playlists. Each playlist contains a list of tracks. Each track may belong to multiple playlists. The relationship between the playlist table and track table is many-to-many. The playlist_track table is used to reflect this relationship. 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, and day; the distribution of amount by year, quarter, month, week, day, and hour; the bottom/top 10 sales by employee, the bottom/top 10 sales by customer, the bottom/top 10 sales by customer, the bottom/top 10 sales by artist, the bottom/top 10 sales by genre, the bottom/top 10 sales by play list, the bottom/top 10 sales by customer city, the bottom/top 10 sales by customer city, the bottom/top 10 sales by customer city, the payment amount by month with mean and EWM, the average payment amount by every month, and amount payment in all years. PROJECT 3: FULL SOURCE CODE: SQL SERVER FOR DATA ANALYTICS AND VISUALIZATION WITH PYTHON GUI This book uses SQL SERVER version of MySQL-based Sakila sample database. It is a fictitious database designed to represent a DVD rental store. The 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. Detailed information about the database can be found on website: https://dev.mysql.com/doc/index-other.html. In this project, you will develop GUI using PyQt5 to: read SQL SERVER database and every table in it; read every actor in actor table, read every film in films table; 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 customers; plot which customer have least and most overdue days; plot which store have most sales; plot average payment amount by month with mean and EWM; and plot payment amount over June 2005. PROJECT 4: SQLITE FOR DATA ANALYSIS AND VISUALIZATION WITH PYTHON GUI In this project, you will use SQLite version of Northwind database which is a sample database that was originally created by Microsoft and used as the basis for their tutorials in a variety of database products for decades. The Northwind database contains the sales data for a fictitious company called “Northwind Traders,” which imports and exports specialty foods from around the world. The Northwind database is an excellent tutorial schema for a small-business ERP, with customers, orders, inventory, purchasing, suppliers, shipping, employees, and single-entry accounting. The Northwind dataset includes sample data for the following: Suppliers: Suppliers and vendors of Northwind; Customers: Customers who buy products from Northwind; Employees: Employee details of Northwind traders; Products: Product information; Shippers: The details of the shippers who ship the products from the traders to the end-customers; Orders and Order_Details: Sales Order transactions taking place between the customers & the company. The Northwind sample database includes 11 tables and the table relationships are showcased in the following entity relationship diagram. 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 SQLite 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 supplier, top 10 sales by supplier, bottom 10 sales by customer country, top 10 sales by customer country, bottom 10 sales by supplier country, top 10 sales by supplier country, average amount by month with mean and ewm, average amount by every month, amount feature over June 1997, amount feature over 1998, and all amount feature.

SQLITE AND DATA SCIENCE: QUERIES AND VISUALIZATION WITH PYTHON GUI

Author : Vivian Siahaan,Rismon Hasiholan Sianipar
Publisher : BALIGE PUBLISHING
Page : 428 pages
File Size : 42,6 Mb
Release : 2022-06-15
Category : Computers
ISBN : 8210379456XXX

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SQLITE AND DATA SCIENCE: QUERIES AND VISUALIZATION WITH PYTHON GUI by Vivian Siahaan,Rismon Hasiholan Sianipar Pdf

In this project, you will develop GUI with PyQt5 to: utilize Push Button, Combo Box, Table Widget, Line Edit, and Widget, read and create SQLite database and every table in it, 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 customer have least and most overdue days; plot which store have most sales; plot average payment amount by month with mean and EWM; and plot payment amount over June 2005. This project uses the 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 SQLite from https://dev.mysql.com/doc/sakila/en/.

FULL SOURCE CODE: SQL SERVER FOR STUDENTS AND DATA SCIENTISTS WITH PYTHON GUI

Author : Vivian Siahaan,Rismon Hasiholan Sianipar
Publisher : BALIGE PUBLISHING
Page : 442 pages
File Size : 50,5 Mb
Release : 2022-10-13
Category : Computers
ISBN : 8210379456XXX

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FULL SOURCE CODE: SQL SERVER FOR STUDENTS AND DATA SCIENTISTS WITH PYTHON GUI by Vivian Siahaan,Rismon Hasiholan Sianipar Pdf

In this project, we provide you with the SQL SERVER version of SQLite sample database named chinook. The chinook sample database is a good database for practicing with SQL, especially PostgreSQL. The detailed description of the database can be found on: https://www.sqlitetutorial.net/sqlite-sample-database/. The sample database consists of 11 tables: The employee table stores employees data such as employee id, last name, first name, etc. It also has a field named ReportsTo to specify who reports to whom; customers table stores customers data; invoices & invoice_items tables: these two tables store invoice data. The invoice table stores invoice header data and the invoice_items table stores the invoice line items data; The artist table stores artists data. It is a simple table that contains only the artist id and name; The album table stores data about a list of tracks. Each album belongs to one artist. However, one artist may have multiple albums; The media_type table stores media types such as MPEG audio and AAC audio files; genre table stores music types such as rock, jazz, metal, etc; The track table stores the data of songs. Each track belongs to one album; playlist & playlist_track tables: The playlist table store data about playlists. Each playlist contains a list of tracks. Each track may belong to multiple playlists. The relationship between the playlist table and track table is many-to-many. The playlist_track table is used to reflect this relationship. 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, and day; the distribution of amount by year, quarter, month, week, day, and hour; the bottom/top 10 sales by employee, the bottom/top 10 sales by customer, the bottom/top 10 sales by customer, the bottom/top 10 sales by artist, the bottom/top 10 sales by genre, the bottom/top 10 sales by play list, the bottom/top 10 sales by customer city, the bottom/top 10 sales by customer city, the bottom/top 10 sales by customer city, the payment amount by month with mean and EWM, the average payment amount by every month, and amount payment in all years.

FULL SOURCE CODE: POSTGRESQL AND DATA SCIENCE FOR PROGRAMMERS WITH PYTHON GUI

Author : Vivian Siahaan,Rismon Hasiholan Sianipar
Publisher : BALIGE PUBLISHING
Page : 496 pages
File Size : 41,6 Mb
Release : 2022-09-19
Category : Computers
ISBN : 8210379456XXX

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FULL SOURCE CODE: POSTGRESQL AND DATA SCIENCE FOR PROGRAMMERS WITH PYTHON GUI by Vivian Siahaan,Rismon Hasiholan Sianipar Pdf

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.

SQLITE QUERIES, ANALYSIS, AND VISUALIZATION WITH PYTHON

Author : Vivian Siahaan,Rismon Hasiholan Sianipar
Publisher : BALIGE PUBLISHING
Page : 48 pages
File Size : 51,8 Mb
Release : 2022-06-01
Category : Computers
ISBN : 8210379456XXX

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SQLITE QUERIES, ANALYSIS, AND VISUALIZATION WITH PYTHON by Vivian Siahaan,Rismon Hasiholan Sianipar Pdf

Sakila for SQLite is a part of the sakila-sample-database-ports project intended to provide ported versions of the original MySQL database for other database systems, including: Oracle, SQL Server, SQLite, Interbase/Firebird, and Microsoft Access. Sakila for SQLite is a port of the Sakila example database available for MySQL, which was originally developed by Mike Hillyer of the MySQL AB documentation team. The project is designed to help database administrators to decide which database to use for development of new products. In this project, you will: read sqlite database and every table in it; read every actor in actor table, read every film in films table; 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 customer have least and most overdue days; plot which store have most sales; plot average payment amount by month with mean and EWM; and plot payment amount over June 2005.

FULL SOURCE CODE: POSTGRESQL FOR DATA SCIENTISTS AND DATA ANALYSTS WITH PYTHON GUI

Author : Vivian Siahaan,Rismon Hasiholan Sianipar
Publisher : BALIGE PUBLISHING
Page : 360 pages
File Size : 54,6 Mb
Release : 2022-09-06
Category : Computers
ISBN : 8210379456XXX

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FULL SOURCE CODE: POSTGRESQL FOR DATA SCIENTISTS AND DATA ANALYSTS WITH PYTHON GUI by Vivian Siahaan,Rismon Hasiholan Sianipar Pdf

In this project, we will use the PostgreSQL version of SQL Server based BikeStores as a sample database to help you work with PostgreSQL quickly and effectively. The detailed structure of database can be found at: https://www.sqlservertutorial.net/sql-server-sample-database/. The stores table includes the store’s 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. The categories table stores the bike’s categories such as children bicycles, comfort bicycles, and electric bikes. The products table stores the product’s 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. The customers table stores customer’s information including first name, last name, phone, email, street, city, state, zip code, and photo path. The orders table stores the sales order’s 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. 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.

DATA VISUALIZATION AND DATA ANALYTICS USING JDBC AND SQLITE WITH OBJECT-ORIENTED APPROACH AND APACHE NETBEANS IDE

Author : Vivian Siahaan
Publisher : BALIGE PUBLISHING
Page : 523 pages
File Size : 45,6 Mb
Release : 2023-03-26
Category : Computers
ISBN : 8210379456XXX

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DATA VISUALIZATION AND DATA ANALYTICS USING JDBC AND SQLITE WITH OBJECT-ORIENTED APPROACH AND APACHE NETBEANS IDE by Vivian Siahaan Pdf

In this project, we developed data visualization and data analytics with step by step implementation of JDBC/SQLITE using object-oriented approach. We uses the SQLite version of BikeStores database as a sample database to help you work with SQLite quickly and effectively. You can download the sample database from https://viviansiahaan.blogspot.com/2023/03/my-book-data-visualization-and-data.html. In this project, we plotted: the bar chart that displays the distribution of products by category; the pie chart that displays the distribution of products by brand; the distribution of stores by city; the distribution of stores by state; the top 10 stock distributions by category name; the top 10 stock distributions by brand name; the top 10 stock distributions by store name; the top 10 stock distributions by city; the customer distribution by state; the customer distribution by city; the bar chart distribution of staff by state; the bar chart distribution of staff by city; the bar chart that shows the distribution of orders based on the store name; the pie chart that shows the distribution of orders based on the customer name; the pie chart showing the order distribution by store city; the pie chart showing the order distribution by store state; the pie chart showing the order distribution by customer city; the pie chart showing the order distribution by customer state; the pie chart sales distribution by staff name; the pie chart sales distribution by brand name; the pie chart sales distribution by customer city; the pie chart sales distribution by customer state; the pie chart sales distribution by store city; the pie chart sales distribution by store state; the pie chart sales distribution by product name; the pie chart sales distribution by category name; pie chart sales distribution by customer name; and the pie chart sales distribution by store name. The stores table includes the store’s 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. The categories table stores the bike’s categories such as children bicycles, comfort bicycles, and electric bikes. The products table stores the product’s 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. The customers table stores customer’s information including first name, last name, phone, email, street, city, state, zip code, and photo path. The orders table stores the sales order’s 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.

Programming for Data Science

Author : Erick Thompson
Publisher : Unknown
Page : 612 pages
File Size : 41,9 Mb
Release : 2020-10-28
Category : Electronic
ISBN : 9798554981258

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Programming for Data Science by Erick Thompson Pdf

Do you want to master the era of data economy? Do you want to learn the top programming languages for data science? If yes, then keep reading! One of the core elements of economic growth in the twenty-first century is the data economy. We are all required to educate ourselves about a paradigm that represents only the very beginning of a genuine industrial revolution, this time driven by data. Data we generate, store, share, analyze, data that describes us, pinpoints where we are, reveals our tastes and preferences, our opinions and also those of our network of family and friends. Data has become a crucial input for any economic process. There is more data being produced daily these days than there was ever produced in even the past centuries! In such a scenario, Data Science is obviously a very popular field as it is important to analyze and process this data to obtain useful insights. According to an IBM report published on Forbes, data science has been ranked the best job in tech for the last 3 years. But in order to be able to assess and analyze the data gathered, you need the best data science tools and skills. In this beginners and practical guide, you are going to learn the best programming language for data science in 2020, the mostly used by other data scientists and that employers are constantly looking. This is a complete guide, with 4 Books in 1: Python crash course Python for data analysis Java programming for beginners SQL for beginners Python is one of the best programming languages for data science because of its capacity for statistical analysis, data modeling, and easy readability. Another reason for this huge success of Python in Data Science is its extensive library support for data science and analytics. There are many Python libraries that contain a host of functions, tools, and methods to manage and analyze data. Each of these libraries has a particular focus with some libraries managing image and textual data, data mining, neural networks, data visualization, and so on. Java is one of the oldest languages used for enterprise development. Most of the popular Big Data frameworks/tools on the likes of Spark, Flink, Hive, Spark and Hadoop are written in Java. It has a great number of libraries and tools for Machine Learning and Data Science. Some of them being to solve most of your ML or data science problems. SQL is a language specifically created for managing and retrieving the data stored in a relational database management system. This language is extremely important for data science as it deals primarily with data. The main role of data scientists is to convert the data into actionable insights and so they need SQL to retrieve the data to and from the database when required. There are many popular SQL databases that data scientists can use such as SQLite, MySQL, Oracle and Microsoft SQL Server. BigQuery, in particular, is a data warehouse that can manage data analysis over petabytes of data and enable super fats SQL queries. Each of these languages come with their benefits, often offering better and faster results when compared with others. The domain of Data Science is exceedingly vast and can often demand a different set of tools for various tasks. Equipping yourself with more than one programming language can guarantee to help you overcome unique challenges while dealing with the data. If you are a budding Data Scientist, you should start with the programming languages mentioned above as they are the most in-demand languages right now. Ready to get started? Click the BUY NOW button!

SQL in a Nutshell

Author : Kevin Kline,Brand Hunt,Daniel Kline
Publisher : "O'Reilly Media, Inc."
Page : 714 pages
File Size : 50,5 Mb
Release : 2004-09-24
Category : Computers
ISBN : 9781449378936

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SQL in a Nutshell by Kevin Kline,Brand Hunt,Daniel Kline Pdf

SQL in a Nutshell applies the eminently useful "Nutshell" format to Structured Query Language (SQL), the elegant--but complex--descriptive language that is used to create and manipulate large stores of data. For SQL programmers, analysts, and database administrators, the new second edition of SQL in a Nutshell is the essential date language reference for the world's top SQL database products. SQL in a Nutshell is a lean, focused, and thoroughly comprehensive reference for those who live in a deadline-driven world.This invaluable desktop quick reference drills down and documents every SQL command and how to use it in both commercial (Oracle, DB2, and Microsoft SQL Server) and open source implementations (PostgreSQL, and MySQL). It describes every command and reference and includes the command syntax (by vendor, if the syntax differs across implementations), a clear description, and practical examples that illustrate important concepts and uses. And it also explains how the leading commercial and open sources database product implement SQL. This wealth of information is packed into a succinct, comprehensive, and extraordinarily easy-to-use format that covers the SQL syntax of no less than 4 different databases.When you need fast, accurate, detailed, and up-to-date SQL information, SQL in a Nutshell, Second Edition will be the quick reference you'll reach for every time. SQL in a Nutshell is small enough to keep by your keyboard, and concise (as well as clearly organized) enough that you can look up the syntax you need quickly without having to wade through a lot of useless fluff. You won't want to work on a project involving SQL without it.

Learning MySQL

Author : Seyed Tahaghoghi,Hugh E. Williams
Publisher : "O'Reilly Media, Inc."
Page : 620 pages
File Size : 52,8 Mb
Release : 2007-11-28
Category : Computers
ISBN : 9780596008642

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Learning MySQL by Seyed Tahaghoghi,Hugh E. Williams Pdf

This new book in the popular Learning series offers an easy-to-use resource for newcomers to the MySQL relational database. This tutorial explains in plain English how to set up MySQL and related software from the beginning, and how to do common tasks.

Relational Database Systems

Author : Jitendra Patel
Publisher : eBookIt.com
Page : 633 pages
File Size : 54,9 Mb
Release : 2012-12
Category : Computers
ISBN : 9781456611743

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Relational Database Systems by Jitendra Patel Pdf

This book is specially written for students of Computer Engineering (CE) and Information Technology. Also every one with interest in Database Management System can refer this book to get the knowledge about RDBMS. It covers virtually most of core features and some of the advanced features of RDBMS for administrator development including more than hands on examples tested through Oracle 9i. Most of code samples are presented in easy to use through Oracle. Throughout the book most of the features are explained through syntax and examples to develop state-of-the-art Database using advanced concepts like E.R. Modeling, Normalization, Transaction management, Security and other authentication features.

MySQL Crash Course

Author : Ben Forta
Publisher : Addison-Wesley Professional
Page : 635 pages
File Size : 49,9 Mb
Release : 2023-11-02
Category : Computers
ISBN : 9780138223168

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MySQL Crash Course by Ben Forta Pdf

MySQL is one of the most popular database management systems available, powering everything from Internet powerhouses to individual corporate databases to simple end-user applications, and everything in between. This book will teach you all you need to know to be immediately productive with the latest version of MySQL. By working through 30 highly focused hands-on lessons, your MySQL Crash Course will be both easier and more effective than you'd have thought possible. Learn How To Retrieve and Sort Data Filter Data Using Comparisons, Regular Expressions, Full Text Search, and Much More Join Relational Data Create and Alter Tables Insert, Update, and Delete Data Leverage the Power of Stored Procedures and Triggers Use Views and Cursors Manage Transactional Processing Create User Accounts and Manage Security via Access Control

Learning MySQL and MariaDB

Author : Russell J.T. Dyer
Publisher : "O'Reilly Media, Inc."
Page : 408 pages
File Size : 53,6 Mb
Release : 2015-03-30
Category : Computers
ISBN : 9781449362874

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Learning MySQL and MariaDB by Russell J.T. Dyer Pdf

"With an easy, step-by-step approach, this guide shows beginners how to install, use, and maintain the world's most popular open source database: MySQL. You'll learn through real-world examples and many practical tips, including information on how to improve database performance. Database systems such as MySQL help data handling for organizations large and small handle data, providing robust and efficient access in ways not offered by spreadsheets and other types of data stores. This book is also useful for web developers and programmers interested in adding MySQL to their skill sets. Topics include: Installation and basic administration ; Introduction to databases and SQL ; Functions, subqueries, and other query enhancements ; Improving database performance ; Accessing MySQL from popular languages"--

SQL for Data Scientists

Author : Renee M. P. Teate
Publisher : John Wiley & Sons
Page : 400 pages
File Size : 45,8 Mb
Release : 2021-08-17
Category : Computers
ISBN : 9781119669395

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SQL for Data Scientists by Renee M. P. Teate Pdf

Jump-start your career as a data scientist—learn to develop datasets for exploration, analysis, and machine learning SQL for Data Scientists: A Beginner's Guide for Building Datasets for Analysis is a resource that’s dedicated to the Structured Query Language (SQL) and dataset design skills that data scientists use most. Aspiring data scientists will learn how to how to construct datasets for exploration, analysis, and machine learning. You can also discover how to approach query design and develop SQL code to extract data insights while avoiding common pitfalls. You may be one of many people who are entering the field of Data Science from a range of professions and educational backgrounds, such as business analytics, social science, physics, economics, and computer science. Like many of them, you may have conducted analyses using spreadsheets as data sources, but never retrieved and engineered datasets from a relational database using SQL, which is a programming language designed for managing databases and extracting data. This guide for data scientists differs from other instructional guides on the subject. It doesn’t cover SQL broadly. Instead, you’ll learn the subset of SQL skills that data analysts and data scientists use frequently. You’ll also gain practical advice and direction on "how to think about constructing your dataset." Gain an understanding of relational database structure, query design, and SQL syntax Develop queries to construct datasets for use in applications like interactive reports and machine learning algorithms Review strategies and approaches so you can design analytical datasets Practice your techniques with the provided database and SQL code In this book, author Renee Teate shares knowledge gained during a 15-year career working with data, in roles ranging from database developer to data analyst to data scientist. She guides you through SQL code and dataset design concepts from an industry practitioner’s perspective, moving your data scientist career forward!