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Data Collection and Processing with Python
  • Level Professional
  • المدة 16 ساعات hours
  • الطبع بواسطة University of Michigan
  • Offered by

عن

This course teaches you to fetch and process data from services on the Internet. It covers Python list comprehensions and provides opportunities to practice extracting from and processing deeply nested data. You'll also learn how to use the Python requests module to interact with REST APIs and what to look for in documentation of those APIs. For the final project, you will construct a "tag recommender" for the flickr photo sharing site. The course is well-suited for you if you have already taken the "Python Basics" and "Python Functions, Files, and Dictionaries" courses (courses 1 and 2 of the Python 3 Programming Specialization). If you are already familiar with Python fundamentals but want practice at retrieving and processing complex nested data from Internet services, you can also benefit from this course without taking the previous two. This is the third of five courses in the Python 3 Programming Specialization.

الوحدات

Welcome to Data Collection and Processing with Python!

    • 5 Videos
    • 3 Readings
    • 1 Lab
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1 Labs

  • (Optional) Getting Started with Jupyter Notebooks

5 Videos

  • Introduction to the Specialization
  • What’s New? Updates and Improvements in the Second Edition
  • Welcome to Python Data Collection and Processing with Python
  • (Optional) How to Use the Interactive Textbook
  • Executing Python in the Jupyter Environment

3 Readings

  • Syllabus
  • A note to learners who have not taken the updated course 2 - Functions, Files and Dictionaries
  • Help Us Learn More About You!

Nested Data and Nested Iteration

    • 5 Videos
    • 4 ExternalTool
    • 1 Lab
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4 External Tool

  • Use the Runestone Practice Tool
  • Introduction: Nested Data and Nested Iteration
  • Nested Dictionaries
  • Processing JSON Results

1 Labs

  • (Optional) JavaScript Object Notation (JSON)

5 Videos

  • Introduction - Nested Data
  • Nested Lists
  • Nested Dictionaries
  • JSON Format and the JSON Module
  • Conclusion - Nested Data

Nested Iteration

    • 8 Videos
    • 4 ExternalTool
    • 1 Programming
    • 1 Assignment
Show info about module content

1 Programming

  • Assessment - Nested Data and Nested Iteration

1 Assignment

  • Optional - What Did You Use to Practice This Week?

4 External Tool

  • Nested Iteration
  • Structuring Nested Data
  • Deep and Shallow Copies
  • Extracting from Nested Data

8 Videos

  • Introduction - Nested Iteration
  • Nested Iteration
  • Structuring Nested Data
  • Shallow Copies
  • Deep Copies
  • Extracting from Nested Data
  • A Worked Example of Nested Iteration
  • Conclusion: Nested Data and Nested Iteration

Map and Filter

    • 4 Videos
    • 4 ExternalTool
    • 1 Lab
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4 External Tool

  • Use the Runestone Practice Tool
  • Introduction: Map, Filter, List Comprehensions, and Zip
  • Map
  • Filter

1 Labs

  • (Optional) Map and Filter

4 Videos

  • Introduction - Map and Filter
  • Map
  • Filter
  • Conclusion - Map and Filter

List Comprehensions

    • 5 Videos
    • 1 ExternalTool
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1 External Tool

  • List Comprehensions

5 Videos

  • Introduction - List Comprehensions
  • List Comprehensions
  • List Comprehensions Example 1
  • List Comprehensions Example 2
  • Conclusion - List Comprehensions

Zip

    • 4 Videos
    • 1 ExternalTool
    • 2 Lab
    • 1 Programming
    • 1 Assignment
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1 Programming

  • Assessment - More on Accumulation

1 Assignment

  • Optional - What Did You Use to Practice This Week?

1 External Tool

  • Zip

2 Labs

  • An Example Using Zip
  • (Optional) Review and List Comprehensions Warmup

4 Videos

  • Introduction - Zip
  • Zip
  • An Example Using Zip
  • Conclusion - Zip

Requesting Data from the Internet

    • 9 Videos
    • 6 ExternalTool
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6 External Tool

  • Use the Runestone Practice Tool
  • The Internet: Behind the Scenes
  • Anatomy of URLs
  • The HTTP Protocol
  • Using REST APIs
  • Fetching a Page

9 Videos

  • Introduction - REST APIs
  • URLs, Domain Names, and IP Addresses
  • Routing
  • HTTP: Behind the Scenes
  • URL Query Parameters
  • REST API URLs
  • The requests Module
  • Generating URLs with requests.get
  • Conclusion - REST APIs

Using REST APIs

    • 6 Videos
    • 3 ExternalTool
    • 2 Lab
Show info about module content

3 External Tool

  • Figuring Out How to Use a REST API
  • Debugging Calls to requests.get
  • Caching Response Content

2 Labs

  • (Optional) REST APIs
  • (Optional) Request Data with Cache

6 Videos

  • Introduction - Using REST APIs
  • Reading API Documentation: Datamuse
  • Debugging Calls to requests.get
  • Caching Response Content
  • The requests_with_caching Module
  • Conclusion - Using REST APIs

Practice with REST APIs

    • 4 Videos
    • 3 ExternalTool
Show info about module content

3 External Tool

  • Searching for Media on iTunes
  • Searching for tags on Flickr
  • Unicode for Non-English Characters

4 Videos

  • Introduction - Practice with REST APIs
  • iTunes API
  • flickr API
  • Conclusion - Practice with REST APIs

Way of the Programmer

    • 5 Videos
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5 Videos

  • Fun with the Google Places API
  • Running Python in Hosted Systems
  • Creating Your Own API - Part 1
  • Creating Your Own API - Part 2
  • Creating Your Own API - Part 3

Data Collection and Processing with Python - Final Course Project

    • 1 Videos
    • 1 Programming
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1 Programming

  • Project - OMDB and Dad Joke Mashup

1 Videos

  • Introduction - Final Course Project

Course Feedback

    • 2 Readings
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2 Readings

  • Course Feedback
  • Keep Learning with Michigan Online

Auto Summary

Discover how to fetch and process data using Python in this comprehensive course on Data Collection and Processing with Python. Ideal for learners with a background in Python basics, this course dives into list comprehensions, handling nested data, and using the requests module for REST APIs. You'll build a tag recommender for Flickr as a final project. Offered by Coursera, this 960-minute course is part of the Python 3 Programming Specialization and is available through Starter, Professional, and Paid subscriptions. Perfect for IT and computer science professionals looking to enhance their data processing skills.

Paul Resnick
Instructor

Paul Resnick