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!

Introduction and lists

Manipulating lists for fun and profit

Looping over lists

Meet the tuples

Data type usage

Using and unpacking tuples

Making tuples by accident

Strings

Formatted String Literals ("f" strings)

Combining multiple strings

Finding strings in other strings

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.

Tipe data numerik

Opsi

Integer

Float

Decimal

Memilih kapan menggunakan integer dan float

Mencetak float

Pembagian dengan integer dan float

Boolean - Tipe data logis

Lebih dari sekadar true dan false

Perbandingan

Truthy, True, Falsey, dan False

Set (data tak berurutan dengan operasi logika yang dioptimalkan)

Menentukan selisih himpunan

Menemukan seluruh data dan data yang tumpang tindih antar set

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

Apakah Anda sudah menguasai dasar-dasar pemrograman Python dan ingin melangkah lebih jauh? Maka kursus ini cocok untuk Anda. Di sini, Anda akan mengonsolidasikan dan mempraktikkan pengetahuan tentang list, dictionary, tuple, set, dan date time. Anda akan melihat relevansinya saat bekerja dengan banyak data nyata dan bagaimana memanfaatkan beberapa di antaranya secara bersamaan untuk menyelesaikan masalah bertahap, termasuk studi kasus mendalam menggunakan data transportasi wilayah metropolitan Chicago. Anda juga akan mempelajari cara menggunakan banyak objek dalam modul Python Collections, yang memungkinkan Anda menyimpan dan memanipulasi data untuk beragam tujuan. Setelah mengikuti kursus ini, Anda akan siap menghadapi banyak tantangan data secara Pythonic.

Python Toolbox

Tipe Data di Python

Perkuat dan perluas pemahaman Anda tentang tipe data Python seperti daftar, kamus, dan tuple, dan manfaatkan mereka untuk memecahkan masalah Data Science.

Pengembang Python Tingkat Menengah

Dasar-Dasar Pemrograman Python

Instructor

Membuat set

Memodifikasi set

Memperbarui set

Menghapus data dari set

Operasi set - kemiripan

Operasi set - perbedaan

Ayo berlatih!

Numeric Data Types, Booleans, and Sets - Set (data tak berurutan dengan operasi logika yang dioptimalkan)

Set (data tak berurutan dengan operasi logika yang dioptimalkan)

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