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Introduzione ai database in Python

IntermedioLivello di competenza

Aggiornato 08/2024

In questo corso imparerai le basi dei database relazionali e come usarli.

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PythonData Manipulation

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Descrizione del corso

In questo corso imparerai le basi dell'uso di SQL con Python. Ti sarà utile perché i database sono ovunque e data scientist, analisti e ingegneri devono interagirci continuamente. Il toolkit SQL per Python, SQLAlchemy, offre un modo accessibile e intuitivo per interrogare, creare e scrivere su database essenziali, tra cui SQLite, MySQL e PostgreSQL.

Prerequisiti

Intermediate Python

1

Basics of Relational Databases

In this chapter, you’ll get acquainted with the fundamentals of relational databases and the relational model for database management. You will learn how to connect to a database and interact with it by writing basic SQL queries, both in raw SQL as well as SQLAlchemy, which provides a Pythonic way of interacting with databases.

Introduction to Databases

Relational model

Connecting to your database

Engines and connection strings

Autoloading Tables from a database

Viewing Table details

Introduction to SQL queries

Selecting data from a Table: raw SQL

Selecting data from a Table with SQLAlchemy

Handling a ResultSet

Congratulations!

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2

Applying Filtering, Ordering and Grouping to Queries

In this chapter, you will build on your database knowledge by writing more nuanced queries that allow you to filter, order, and count your data—all within the Pythonic framework provided by SQLAlchemy.

Filtering and targeting data

Connecting to a PostgreSQL database

Filter data selected from a Table - Simple

Filter data selected from a Table - Expressions

Filter data selected from a Table - Advanced

Ordering query results

Ordering by a single column

Ordering in descending order by a single column

Ordering by multiple columns

Counting, summing, and grouping data

Counting distinct data

Count of records by state

Determining the population sum by state

SQLAlchemy and pandas for visualization

ResultsSets and pandas DataFrames

From SQLAlchemy results to a plot

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3

Advanced SQLAlchemy Queries

In this chapter, you will learn to perform advanced—and incredibly useful—queries that enable you to interact with your data in powerful ways.

Calculating values in a query

Connecting to a MySQL database

Calculating a difference between two columns

Determining the overall percentage of women

SQL relationships

Automatic joins with an established relationship

More practice with joins

Working with hierarchical tables

Using alias to handle same table joined queries

Leveraging functions and group_bys with hierarchical data

Handling large ResultSets

Working on blocks of records

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4

Creating and Manipulating your own Databases

In the previous chapters, you interacted with existing databases and queried them in different ways. Now, you will learn how to build your own databases and keep them updated.

Creating databases and tables

Creating tables with SQLAlchemy

Constraints and data defaults

Inserting data into a table

Inserting a single row

Inserting multiple records at once

Loading a CSV into a table

Updating data in a table

Updating individual records

Updating multiple records

Correlated updates

Deleting data from a database

Deleting all the records from a table

Deleting specific records

Deleting a table completely

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5

Putting it all together

Bring together all of the skills you acquired in the previous chapters to work on a real-life project. From connecting to a database and populating it, to reading and querying it.

Census case study

Setup the engine and metadata

Create the table to the database

Populating the database

Reading the data from the CSV

Load data from a list into the Table

Querying the database

Determine the average age by population

Determine the percentage of population by gender and state

Determine the difference by state from the 2000 and 2008 censuses

Congratulations!

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Introduzione ai database in Python

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