Course · Intermediate

APIs and Web Scraping in Python for Data Science

In this course, you'll learn key Python skills such as handling JSON data, authenticating APIs, understanding rate limits, and utilizing optional query parameters. As you progress, you'll gain crucial skills in extracting and analyzing data from web pages. You'll also learn how to integrate API data with Pandas for comprehensive analysis and visualization. Whether you're new to Python or looking to level up your skills, this course offers a practical learning experience, delivering you the tools needed to tackle real-world data challenges.

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  • Intermediate friendly
  • 5 hrs
  • 5 lessons
  • 1 project
  • Premium

Course overview

Develop practical skills for collecting, extracting, and analyzing web data using Python APIs, web scraping, and real-world datasets.

What's inside

5 lessons · 1 project

  • 01
    APIs and the Requests Library

    <p>This lesson introduces the term API (Application Programming Interface) and explains how it is used in Python. We discuss the <span style="color: rgb(235,87,87);background-color: rgba(135,131,120,0.15);font-size: 85%;">requests</span> library as an option for executing API endpoint calls, as well as the GET and POST endpoints and how they differ. Additionally, we explain JSON so you can understand how data is returned within a request response. By the end of the lesson, you will be able to make simple API calls using the <span style="color: rgb(235,87,87);background-color: rgba(135,131,120,0.15);font-size: 85%;">requests</span> library.&nbsp;</p>

    71 min
  • 02
    Optional Query Parameters and Data Filtering

    <p>Learn how to use optional query parameters to refine your API data requests.</p>

    89 min
  • 03
    Authentication, API Keys, and Rate Limits

    <p>Explore the concepts of authentication and rate limits in API usage, and learn how to handle them effectively.</p>

    45 min
  • 04
    Web Scraping

    <p>Introduce the concept of web scraping and learn how to extract data from web pages.</p>

    84 min
  • 05
    Integrating APIs with Pandas for Data Wrangling

    <p>Learn how to Integrate APIs and web scraping with Pandas for Data Wrangling.</p>

    59 min
  • 06
    Guided Project: Exploring Financial Data using Nasdaq Data Link API Project

    For this project, you'll become a financial analyst exploring real-world economic data. You'll use Python to interact with the NASDAQ Data Link API, retrieve financial datasets, then apply Pandas for data wrangling. By visualizing market trends, you'll develop insights and analytical skills essential for this role.

    37 min

Part of these paths

Career path
Data Analyst in Python
144 hrs · 27 courses
Career path
Data Scientist in Python Certificate Program
171 hrs · 38 courses

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Aaron Melton
Aaron Melton
Business Analyst at Aditi Consulting

Dataquest starts at the most basic level, so a beginner can understand the concepts. I tried learning to code before, using Codecademy and Coursera. I struggled because I had no background in coding, and I was spending a lot of time Googling. Dataquest helped me actually learn.

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Jessica Ko
Machine Learning Engineer at Twitter

I liked the interactive environment on Dataquest. The material was clear and well organized. I spent more time practicing then watching videos and it made me want to keep learning.

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Victoria E. Guzik
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