This chapter will introduce you to the fundamental Python data types - lists, sets, and strings. These data containers are critical as they provide the basis for storing and looping over ordered data. To make things interesting, you'll apply what you learn about these types to answer questions about the New York Baby Names dataset!

Introduzione e liste

Manipolare le liste per divertimento e vantaggio

Iterare sulle liste

Incontra le tuple

Uso dei tipi di dato

Usare e scompattare le tuple

Creare tuple per sbaglio

Stringhe

Letterali di stringa formattati (stringhe "f")

Combinare più stringhe

Trovare stringhe dentro altre stringhe

Fundamental Sequence Data Types

At the root of all things Python is a dictionary. Herein, you'll learn how to use them to safely handle data that can viewed in a variety of ways to answer even more questions about the New York Baby Names dataset. You'll explore how to loop through data in a dictionary, access nested data, add new data, and come to appreciate all of the wonderful capabilities of Python dictionaries.

Using dictionaries

Creating and looping through dictionaries

Safely finding by key

Altering dictionaries

Adding and extending dictionaries

Popping and deleting from dictionaries

Pythonically using dictionaries

Working with dictionaries more pythonically

Checking dictionaries for data

Mixed data types in dictionaries

Dealing with nested dictionaries

Dealing with nested mixed types

Dictionaries - The Root of Python

Let's take a step away from dictionaries and look at some other common numeric and boolean data types along with sets.

Numeric data types

Choosing when to use integers and floats

Printing floats

Division with integers and floats

Booleans - The logical data type

More than just true and false

Comparisons

Truthy, True, Falsey, and False

Sets (unordered data with optimized logic operations)

Determining set differences

Finding all the data and the overlapping data between sets

Numeric Data Types, Booleans, and Sets

Some data types are composites of other data types and give me even more capabilities than a fundamental data type.  Let's explore a few complex types from the collections module and data classes.

Counting made easy

Using Counter on lists

Finding most common elements

Dictionaries of unknown structure - Defaultdict

Creating dictionaries of an unknown structure

Safely appending to a key's value list

What do you mean I don't have any class? Namedtuple

Creating namedtuples for storing data

Leveraging attributes on namedtuples

Dataclasses

Creating a dataclass

Using dataclasses

Wrap-up

Advanced Data Types

Baby names

Chicago crime

CTA daily station totals

CTA daily summary totals

Hai già dimestichezza con le basi di Python ma vuoi fare un passo avanti? Allora questo corso fa per te. Qui consoliderai e metterai in pratica la tua conoscenza di liste, dizionari, tuple, insiemi e date/ora. Vedrai quanto sono utili lavorando con molti dati reali e come combinarne diversi per risolvere problemi a più passaggi, incluso un caso di studio esteso con i dati del trasporto dell’area metropolitana di Chicago. Imparerai anche a usare molti oggetti del modulo Python Collections, che ti permetteranno di archiviare e manipolare i tuoi dati per vari scopi. Dopo questo corso, sarai pronto ad affrontare molte sfide sui dati in modo “pythonic”.

Python Toolbox

Tipi di dati in Python

Metti alla prova e amplia le tue conoscenze sui tipi di dati Python come liste, dizionari e tuple, e usali per risolvere problemi di scienza dei dati.

Sviluppatore Python associato

Fondamenti di programmazione Python

Uso dei tipi di dato

Tipi di dati in Python

Esercizio pratico interattivo