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Data Collection and Processing with Python

Approx. 16 hours to complete

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Course Summary

This course teaches students how to collect and process data using Python. Students will learn how to use popular libraries such as BeautifulSoup, requests, and pandas to extract data from websites and APIs, clean and preprocess the data, and store it in various formats.

Key Learning Points

Learn how to collect and process data using Python
Use popular libraries such as BeautifulSoup and pandas
Extract data from websites and APIs, clean and preprocess it, and store it in various formats

Job Positions & Salaries of people who have taken this course might have

- USA: $62,500
- India: ₹6,00,000
- Spain: €24,500
- USA: $62,500
- India: ₹6,00,000
- Spain: €24,500
- USA: $113,000
- India: ₹11,00,000
- Spain: €45,000
- USA: $62,500
- India: ₹6,00,000
- Spain: €24,500
- USA: $113,000
- India: ₹11,00,000
- Spain: €45,000
- USA: $75,000
- India: ₹7,20,000
- Spain: €29,000

Learning Outcomes

Understand the basics of web scraping and data collection
Be able to use popular Python libraries for data processing
Be able to clean and preprocess data and store it in various formats

Prerequisites or good to have knowledge before taking this course

Basic knowledge of Python programming
Access to a computer with internet connection

Course Difficulty Level

Intermediate

Course Format

Self-paced
Online
Video Lectures

Similar Courses

Python for Data Science
Data Analysis with Python
Applied Data Science with Python

Notable People in This Field

Guido van Rossum
Jake VanderPlas
Andrew Ng

Related Books

Description

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.

Outline

Nested Data and Nested Iteration
Introduction to the Specialization
How to Use the Interactive Textbook
Introduction - Nested Data
Nested Lists
Nested Dictionaries
JSON Format and the JSON Module
Conclusion - Nested Data
Introduction - Nested Iteration
Nested Iteration
Structuring Nested Data
Shallow Copies
Deep Copies
Extracting from Nested Data
A Worked Example of Nested Iteration
Conclusion - Nested Iteration
Syllabus
Help Us Learn More About You!
Introduction: Nested Data and Nested Iteration
Nested Dictionaries
Processing JSON Results
Nested Iteration
Structuring Nested Data
Deep and Shallow Copies
Extracting from Nested Data
Optional - What Did You Use to Practice This Week?

Map, Filter, and List Comprehensions
Introduction - Map and Filter
Map
Filter
Conclusion - Map and Filter
Introduction - List Comprehensions
List Comprehensions
List Comprehensions Example 1
List Comprehensions Example 2
Conclusion - List Comprehensions
Introduction - Zip
Zip
The Hangman Blanked Function
Conclusion - Zip
Introduction: Map, Filter, List Comprehensions, and Zip
Map
Filter
List Comprehensions
Zip
Optional - What Did You Use to Practice This Week?

Internet APIs
Introduction - REST APIs
URLs, Domain Names, and IP Addresses
Routing
HTTP: Behind the Scenes
URL Query Parameters
REST API URLs
The requests Module
Conclusion - REST APIs
Introduction - Using REST APIs
Generating URLs with requests.get
Reading API Documentation: Datamuse
Debugging Calls to requests.get
Caching Response Content
The requests_with_caching Module
Conclusion - Using REST APIs
Introduction - Practice with REST APIs
iTunes API
flickr API
Conclusion - Practice with REST APIs
Fun with the Google Places API
Introduction - Final Course Project
The Internet: Behind the Scenes
Anatomy of URLs
The HTTP Protocol
Using REST APIs
Fetching a Page
Generating URLs with requests.get
Figuring Out How to Use a REST API
Debugging Calls to requests.get
Caching Response Content
Searching for Media on iTunes
Searching for tags on Flickr
Unicode for Non-English Characters
Course Feedback
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Summary of User Reviews

Users have praised the course for its comprehensive coverage of data collection and processing with Python. One key aspect that many users found good was the instructor's clear explanations and helpful examples.

Pros from User Reviews

Comprehensive coverage of data collection and processing with Python
Clear explanations and helpful examples from the instructor
Hands-on assignments and quizzes to reinforce concepts
Useful resources and tools provided throughout the course

Cons from User Reviews

Some users found the pace of the course to be too slow
Limited interaction with other students
Not suitable for advanced users looking for more in-depth content

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