Download or read book SQLITE QUERIES ANALYSIS AND VISUALIZATION WITH PYTHON written by Vivian Siahaan and published by BALIGE PUBLISHING. This book was released on 2022-06-01 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book SQLITE AND DATA SCIENCE QUERIES AND VISUALIZATION WITH PYTHON GUI written by Vivian Siahaan and published by BALIGE PUBLISHING. This book was released on 2022-06-15 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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/.

Download or read book SQLITE FOR DATA ANALYSIS AND VISUALIZATION WITH PYTHON GUI written by Vivian Siahaan and published by BALIGE PUBLISHING. This book was released on 2022-06-27 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book FOUR PROJECTS MySQL and SQLite For Data Science with Python GUI written by Vivian Siahaan and published by BALIGE PUBLISHING. This book was released on 2022-06-29 with total page 1583 pages. Available in PDF, EPUB and Kindle. Book excerpt: PROJECT 1: SQLITE AND DATA SCIENCE: QUERIES AND VISUALIZATION WITH PYTHON GUI 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/. PROJECT 2: MYSQL AND DATA SCIENCE: QUERIES AND VISUALIZATION WITH PYTHON GUI 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 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 MySQL from https://dev.mysql.com/doc/sakila/en/. PROJECT 3: 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 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.

Download or read book Python Data Persistence written by Lathkar Malhar and published by BPB Publications. This book was released on 2019-09-20 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designed to provide an insight into the SQL and MySQL database concepts using python Key features A practical approach Ample code examples A Quick Start Guide to Python for beginners Description Python is becoming increasingly popular among data scientists. However, analysis and visualization tools need to interact with the data stored in various formats such as relational and NOSQL databases.This book aims to make the reader proficient in interacting with databases such as MySQL, SQLite, MongoDB, and Cassandra.This book assumes that the reader has no prior knowledge of programming. Hence, basic programming concepts, key concepts of OOP, serialization and data persistence have been explained in such a way that it is easy to understand. NOSQL is an emerging technology. Using MongoDB and Cassandra, the two widely used NOSQL databases are explained in detail.The knowhow of handling databases using Python will certainly be helpful for readers pursuing a career in Data Science.What will you learn Python basics and programming fundamentals Serialization libraries pickle, CSV, JSON, and XML DB-AP and, SQLAlchemy Python with Excel documents Python with MongoDB and CassandraWho this book is forStudents and professionals who want to become proficient at database tools for a successful career in data science. Table of contents1. Getting Started2. Program Flow Control3. Structured Python4. Python - OOP5. File IO6. Object Serialization7. RDBMS Concepts8. Python DB-API9. Python - SQLAlchemy10. Python and Excel11. Python - PyMongo12. Python - CassandraAppendix A: Alternate Python ImplementationsAppendix B: Alternate Python DistributionsAppendix C: Built-in FunctionsAppendix D: Built-in ModulesAppendix E: Magic MethodsAppendix F: SQLite Dot CommandsAppendix G: ANSI SQL StatementsAppendix H: PyMongo API MethodsAppendix I: Cassandra CQL Shell Commands About the authorMalhar Lathkar is an Independent software professional / Programming technologies trainer/E-Learning Subject matter Expert. He is a of Director Institute of Programming Language Studies, having an academic experience of 33 years. His expertise is in Java, Python, C#, IoT, PHP, databases. His linkedIn: linkedin.com/in/malharlathkar His blog: indsport.blogspot.com

Download or read book DATA VISUALIZATION AND DATA ANALYTICS PROJECTS WITH MYSQL SQLITE POSTGRESQL AND SQL SERVER USING PYTHON GUI written by Vivian Siahaan and published by BALIGE PUBLISHING. This book was released on 2022-10-26 with total page 1665 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Learn SQLite with Python written by Vivian Siahaan and published by SPARTA PUBLISHING. This book was released on 2019-09-29 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is SQLite-based python programming for database-driven desktop projects. Deliberately designed for various levels of programming skill, this book is suitable for students, engineers, and even researchers in various disciplines. There is no need for advanced programming experience, and school-level programming skills are needed. In the first chapter, you will learn to use several widgets in PyQt5: Display a welcome message; Use the Radio Button widget; Grouping radio buttons; Displays options in the form of a check box; and Display two groups of check boxes. In chapter two, you will learn to use the following topics: Using Signal / Slot Editor; Copy and place text from one Line Edit widget to another; Convert data types and make a simple calculator; Use the Spin Box widget; Use scrollbars and sliders; Using the Widget List; Select a number of list items from one Widget List and display them on another Widget List widget; Add items to the Widget List; Perform operations on the Widget List; Use the Combo Box widget; Displays data selected by the user from the Calendar Widget; Creating a hotel reservation application; and Display tabular data using Table Widgets. In chapter three, you will learn: How to create the initial three tables project in the School database: Teacher, Class, and Subject tables; How to create database configuration files; How to create a Python GUI for inserting and editing tables; How to create a Python GUI to join and query the three tables. In chapter four, you will learn how to: Create a main form to connect all forms; Create a project will add three more tables to the school database: Student, Parent, and Tuition tables; Create a Python GUI for inserting and editing tables; Create a Python GUI to join and query over the three tables. In chapter five, you will join the six classes, Teacher, TClass, Subject, Student, Parent, and Tuition and make queries over those tables. In chapter six, you will create dan configure database. In this chapter, you will create Suspect table in crime database. This table has eleven columns: suspect_id (primary key), suspect_name, birth_date, case_date, report_date, suspect_ status, arrest_date, mother_name, address, telephone, and photo. You will also create GUI to display, edit, insert, and delete for this table. In chapter seven, you will create a table with the name Feature_Extraction, which has eight columns: feature_id (primary key), suspect_id (foreign key), feature1, feature2, feature3, feature4, feature5, and feature6. The six fields (except keys) will have VARBINARY(MAX) data type. You will also create GUI to display, edit, insert, and delete for this table. In chapter eight, you will create two tables, Police and Investigator. The Police table has six columns: police_id (primary key), province, city, address, telephone, and photo. The Investigator table has eight columns: investigator_id (primary key), investigator_name, rank, birth_date, gender, address, telephone, and photo. You will also create GUI to display, edit, insert, and delete for both tables. In the last chapter, you will create two tables, Victim and Case_File. The Victim table has nine columns: victim_id (primary key), victim_name, crime_type, birth_date, crime_date, gender, address, telephone, and photo. The Case_File table has seven columns: case_file_id (primary key), suspect_id (foreign key), police_id (foreign key), investigator_id (foreign key), victim_id (foreign key), status, and description. You will create GUI to display, edit, insert, and delete for both tables as well.

Download or read book SQLite For Beginners written by Vivian Siahaan and published by SPARTA PUBLISHING. This book was released on 2019-09-29 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is SQLite-based python programming. Deliberately designed for various levels of programming skill, this book is suitable for students, engineers, and even researchers in various disciplines. There is no need for advanced programming experience, and school-level programming skills are needed. In the first chapter, you will learn to use several widgets in PyQt5: Display a welcome message; Use the Radio Button widget; Grouping radio buttons; Displays options in the form of a check box; and Display two groups of check boxes. In chapter two, you will learn to use the following topics: Using Signal / Slot Editor; Copy and place text from one Line Edit widget to another; Convert data types and make a simple calculator; Use the Spin Box widget; Use scrollbars and sliders; Using the Widget List; Select a number of list items from one Widget List and display them on another Widget List widget; Add items to the Widget List; Perform operations on the Widget List; Use the Combo Box widget; Displays data selected by the user from the Calendar Widget; Creating a hotel reservation application; and Display tabular data using Table Widgets. In third chapter, you will learn: How to create the initial three tables project in the School database: Teacher, Class, and Subject tables; How to create database configuration files; How to create a Python GUI for inserting and editing tables; How to create a Python GUI to join and query the three tables. In fourth chapter, you will learn how to: Create a main form to connect all forms; Create a project will add three more tables to the school database: Student, Parent, and Tuition tables; Create a Python GUI for inserting and editing tables; Create a Python GUI to join and query over the three tables. In the last chapter, you will join the six classes, Teacher, TClass, Subject, Student, Parent, and Tuition and make queries over those tables.

Download or read book FIVE PROJECTS SQLITE AND PYTHON GUI FOR DATA ANALYSIS written by Vivian Siahaan and published by BALIGE PUBLISHING. This book was released on 2022-11-03 with total page 1862 pages. Available in PDF, EPUB and Kindle. Book excerpt: PROJECT 1: FULL SOURCE CODE: PRACTICAL DATA SCIENCE WITH SQLITE AND PYTHON GUI In this project, we provide you with the SQLite sample database named chinook. The chinook sample database is a good database for practicing with SQL, especially SQLite. The detailed description of the database can be found on: https://www.sqlitetutorial.net/sqlite-sample-database/. There are 11 tables in the chinook sample database: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 2: FULL SOURCE CODE: SQLITE FOR STUDENTS AND PROGRAMMERS WITH PYTHON GUI In this project, we provide you with a SQLITE 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. You can find the detailed structures of the database: https://www.oracletutorial.com/getting-started/oracle-sample-database/. 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: SQLITE FOR DATA ANALYST AND DATA SCIENTIST WITH PYTHON GUI 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 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. 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. PROJECT 5: 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.

Download or read book Practical Data Analysis Using Jupyter Notebook written by Marc Wintjen and published by Packt Publishing Ltd. This book was released on 2020-06-19 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understand data analysis concepts to make accurate decisions based on data using Python programming and Jupyter Notebook Key FeaturesFind out how to use Python code to extract insights from data using real-world examplesWork with structured data and free text sources to answer questions and add value using dataPerform data analysis from scratch with the help of clear explanations for cleaning, transforming, and visualizing dataBook Description Data literacy is the ability to read, analyze, work with, and argue using data. Data analysis is the process of cleaning and modeling your data to discover useful information. This book combines these two concepts by sharing proven techniques and hands-on examples so that you can learn how to communicate effectively using data. After introducing you to the basics of data analysis using Jupyter Notebook and Python, the book will take you through the fundamentals of data. Packed with practical examples, this guide will teach you how to clean, wrangle, analyze, and visualize data to gain useful insights, and you'll discover how to answer questions using data with easy-to-follow steps. Later chapters teach you about storytelling with data using charts, such as histograms and scatter plots. As you advance, you'll understand how to work with unstructured data using natural language processing (NLP) techniques to perform sentiment analysis. All the knowledge you gain will help you discover key patterns and trends in data using real-world examples. In addition to this, you will learn how to handle data of varying complexity to perform efficient data analysis using modern Python libraries. By the end of this book, you'll have gained the practical skills you need to analyze data with confidence. What you will learnUnderstand the importance of data literacy and how to communicate effectively using dataFind out how to use Python packages such as NumPy, pandas, Matplotlib, and the Natural Language Toolkit (NLTK) for data analysisWrangle data and create DataFrames using pandasProduce charts and data visualizations using time-series datasetsDiscover relationships and how to join data together using SQLUse NLP techniques to work with unstructured data to create sentiment analysis modelsDiscover patterns in real-world datasets that provide accurate insightsWho this book is for This book is for aspiring data analysts and data scientists looking for hands-on tutorials and real-world examples to understand data analysis concepts using SQL, Python, and Jupyter Notebook. Anyone looking to evolve their skills to become data-driven personally and professionally will also find this book useful. No prior knowledge of data analysis or programming is required to get started with this book.

Download or read book Data Analysis and Visualization Using Python written by Ossama Embarak and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Look at Python from a data science point of view and learn proven techniques for data visualization as used in making critical business decisions. Starting with an introduction to data science with Python, you will take a closer look at the Python environment and get acquainted with editors such as Jupyter Notebook and Spyder. After going through a primer on Python programming, you will grasp fundamental Python programming techniques used in data science. Moving on to data visualization, you will see how it caters to modern business needs and forms a key factor in decision-making. You will also take a look at some popular data visualization libraries in Python. Shifting focus to data structures, you will learn the various aspects of data structures from a data science perspective. You will then work with file I/O and regular expressions in Python, followed by gathering and cleaning data. Moving on to exploring and analyzing data, you will look at advanced data structures in Python. Then, you will take a deep dive into data visualization techniques, going through a number of plotting systems in Python. In conclusion, you will complete a detailed case study, where you'll get a chance to revisit the concepts you've covered so far. What You Will Learn Use Python programming techniques for data science Master data collections in Python Create engaging visualizations for BI systems Deploy effective strategies for gathering and cleaning data Integrate the Seaborn and Matplotlib plotting systems Who This Book Is For Developers with basic Python programming knowledge looking to adopt key strategies for data analysis and visualizations using Python.--Provided by publisher.

Download or read book DATA ANALYSIS PROJECTS WITH MYSQL SQLITE POSTGRESQL AND SQL SERVER USING PYTHON GUI written by Vivian Siahaan and published by BALIGE PUBLISHING. This book was released on 2022-10-26 with total page 1647 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book DATA SCIENCE WITH MYSQL SQLITE POSTGRESQL AND SQL SERVER USING PYTHON GUI written by Vivian Siahaan and published by BALIGE PUBLISHING. This book was released on 2022-10-03 with total page 1667 pages. Available in PDF, EPUB and Kindle. Book excerpt: Book 1: MYSQL AND DATA SCIENCE: QUERIES AND VISUALIZATION WITH PYTHON GUI 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 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 MySQL from https://dev.mysql.com/doc/sakila/en/. Book 2: SQLITE FOR DATA ANALYST AND DATA SCIENTIST WITH PYTHON GUI 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 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. Book 3: ZERO TO MASTERY: THE COMPLETE GUIDE TO LEARNING POSTGRESQL WITH PYTHON GUI This book uses the PostgreSQL version of MySQL-based Northwind database. The Northwind database 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 database has since been ported to a variety of non-Microsoft databases, including PostgreSQL. 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; and Orders and Order_Details: Sales Order transactions taking place between the customers & the company. 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. Book 4: ZERO TO MASTERY: THE COMPLETE GUIDE TO LEARNING SQL SERVER AND DATA SCIENCE WITH PYTHON GUI In this project, we provide you with a SQL SERVER 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.

Download or read book Python and SQLite Development written by Agus Kurniawan and published by PE Press. This book was released on 2021-01-30 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is designed for anyone who wants to learn SQLite database programming Python 3. The book covers database programming for SQLite with the following highlight topics: * Setting up Development Environment * Setting Started - Python and SQLite * SQLite Shell * CRUD (Create, Read, Update, Delete) Operations * Working with Image and Blob Data * Transaction * Python, SQLite and Pandas

Download or read book Hands On Data Analysis with Pandas written by Stefanie Molin and published by Packt Publishing Ltd. This book was released on 2019-07-26 with total page 702 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get to grips with pandas—a versatile and high-performance Python library for data manipulation, analysis, and discovery Key FeaturesPerform efficient data analysis and manipulation tasks using pandasApply pandas to different real-world domains using step-by-step demonstrationsGet accustomed to using pandas as an effective data exploration toolBook Description Data analysis has become a necessary skill in a variety of positions where knowing how to work with data and extract insights can generate significant value. Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will learn how to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding chapters, you will explore some applications of anomaly detection, regression, clustering, and classification, using scikit-learn, to make predictions based on past data. By the end of this book, you will be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. What you will learnUnderstand how data analysts and scientists gather and analyze dataPerform data analysis and data wrangling in PythonCombine, group, and aggregate data from multiple sourcesCreate data visualizations with pandas, matplotlib, and seabornApply machine learning (ML) algorithms to identify patterns and make predictionsUse Python data science libraries to analyze real-world datasetsUse pandas to solve common data representation and analysis problemsBuild Python scripts, modules, and packages for reusable analysis codeWho this book is for This book is for data analysts, data science beginners, and Python developers who want to explore each stage of data analysis and scientific computing using a wide range of datasets. You will also find this book useful if you are a data scientist who is looking to implement pandas in machine learning. Working knowledge of Python programming language will be beneficial.

Download or read book SQL Pocket Guide written by Alice Zhao and published by "O'Reilly Media, Inc.". This book was released on 2021-08-26 with total page 247 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you use SQL in your day-to-day work as a data analyst, data scientist, or data engineer, this popular pocket guide is your ideal on-the-job reference. You'll find many examples that address the language's complexities, along with key aspects of SQL used in Microsoft SQL Server, MySQL, Oracle Database, PostgreSQL, and SQLite. In this updated edition, author Alice Zhao describes how these database management systems implement SQL syntax for both querying and making changes to a database. You'll find details on data types and conversions, regular expression syntax, window functions, pivoting and unpivoting, and more. Quickly look up how to perform specific tasks using SQL Apply the book's syntax examples to your own queries Update SQL queries to work in five different database management systems NEW: Connect Python and R to a relational database NEW: Look up frequently asked SQL questions in the "How Do I?" chapter

Download or read book THREE PROJECTS SQL SERVER AND PYTHON GUI FOR DATA ANALYSIS written by Vivian Siahaan and published by BALIGE PUBLISHING. This book was released on 2022-11-08 with total page 1344 pages. Available in PDF, EPUB and Kindle. Book excerpt: PROJECT 1: 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. PROJECT 2: 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 3: ZERO TO MASTERY: THE COMPLETE GUIDE TO LEARNING SQL SERVER AND DATA SCIENCE WITH PYTHON GUI In this project, we provide you with a SQL SERVER 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.