Streamlining Data Preparation with Pydantic: A 25-Minute Guide | Python Data Science Day

Описание: Embark on a 25-minute journey exploring the power of Pydantic in cleaning and preparing data for seamless integration into your Python projects. We'll delve into the versatile capabilities of Pydantic for data validation, type hinting, and structured data cleaning. From ensuring data consistency to handling missing values, Pydantic proves to be an invaluable tool in the data scientist's toolkit.

Chapters:
00:00 Streamlining Data Preparation with Pydantic
00:34 Pydantic overview
02:21 Why use Pydantic
05:15 Pydantic by the numbers
06:24 Core Concepts of Pydantic
10:50 Demo - GitHub Data Crawling ETL (Extract, Transfer, Load)
12:08 Fetching Data with GitHub API
12:56 Repository & Gist Pydantic Model
17:16 Follower & User Pydantic Model
20:26 Object initialization, serializing, dumping
23:39 Load into SQLite
25:38 Learn more and connect

Resources:
Github: https//github.com/hasanozdem1r
Survey https://aka.ms/Python/DataScienceDay/...
Python at Microsoft https://aka.ms/python
Cloud Skills Challenge - through April 15, 2024
https://aka.ms/Python/DataScienceDay/CSC
GitHub codespaces https://github.com/codespaces
VS Code Release notes https://code.visualstudio.com/updates

Featuring: Hasan Özdemir, Data Analyst, Getir (  / hasanozdem1r  )